Information processing systems, methods, and programs

Abstract

Regarding the type of source of the components measured by the measuring device, information is obtained based on the results of measurements taken by a measuring device that is not fixed in a single location. [Solution] The information processing system obtains result information regarding the measurement results of a measuring device for components generated from a source or substances released from said source for the components generated from said source, for measurements taken by the same measuring device at multiple locations where the same measuring device is located. It also obtains type result information regarding the measurement results of components generated from a predetermined type of source or substances released from said source for the components generated by the measuring device. Based on the result information and type result information related to the measurements taken by the same measuring device at the multiple locations, the system outputs information regarding the type identified for the source that is the subject of the measurement.

Description

Technical Field

[0001] The present disclosure relates to an information processing system, method, and program.

Background Art

[0002] Patent Document 1 describes that a sample gas to be measured is introduced into a column of a GC unit to temporally separate each odor component, and then introduced in parallel to an odor identification unit using an MS unit and an odor sensor. Further, Patent Document 1 describes that a data processing unit creates a chromatogram and a mass spectrum based on a detection signal obtained by a detector of the MS unit, and calculates the similarity of each odor component to a standard odor, the contribution degree of the odor index, etc. based on a detection signal obtained by a detection circuit of the odor identification unit. Further, Patent Document 1 describes that a similarity radar chart etc. of the component is displayed on the screen of a display unit in association with a peak appearing in the chromatogram.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, there is a technique in which a measuring device installed at a single position measures components generated based on a generation source, and identifies the components from the measurement results. However, regarding the type of the generation source related to the measured components, sufficient consideration has not been given to obtaining information according to the measurement results by a measuring device that is not fixed at a single position. An object of the present disclosure is to obtain information according to the measurement results by a measuring device that is not fixed at a single position, regarding the type of the generation source related to the components measured by the measuring device.

Means for Solving the Problems

[0005] The information processing system disclosed herein comprises one or more processors, the one or more processors acquire result information regarding the results of measurements of components generated from a source or substances released from said source by a measuring device for said components, for measurements performed by a single measuring device at multiple locations where the single measuring device is located, acquire type result information regarding the results of measurements performed by the measuring device for components generated from a predetermined type of source or substances released from said source, and output information regarding the type identified for the source that is the subject of the measurement related to the result information, in accordance with the result information and type result information related to the measurements performed by the single measuring device at the multiple locations. [Effects of the Invention]

[0006] According to this disclosure, information regarding the type of source of a component measured by a measuring device can be obtained in accordance with the results of measurements taken by a measuring device that is not fixed in a single location. [Brief explanation of the drawing]

[0007] [Figure 1] This diagram shows an example of the overall configuration of the support system. [Figure 2] This figure shows an example of the hardware configuration of the management server, administrator terminal, and user terminal. [Figure 3] This diagram shows an example of the functional configuration of the management server. [Figure 4] This figure shows an example of a sensing means management table. [Figure 5] This figure shows an example of a category management table. [Figure 6] This figure shows an example of a notification target management table. [Figure 7] This figure shows an example of an individual management table. [Figure 8] This is a diagram showing the results management table. [Figure 9] It is a diagram showing an example of an individual number management table. [Figure 10] It is a diagram showing an example of a user management table. [Figure 11] It is a diagram showing an example of a graph generated by a graph generation unit. [Figure 12] It is a diagram showing an example of a concept in which a management server identifies the type of a source of generation. [Figure 13] It is a diagram showing an example of a concept in which a management server identifies an individual of a source of generation. [Figure 14] (A) and (B) are diagrams showing an example of a mode setting screen. [Figure 15] It is a flowchart diagram showing the flow of fixed notification processing. [Figure 16] It is a flowchart diagram showing the flow of fixed notification processing. [Figure 17] It is a flowchart diagram showing the flow of result output processing. [Figure 18] It is a flowchart diagram showing the flow of result output processing. [Figure 19] It is a flowchart diagram showing the flow of deletion processing. [Figure 20] It is a diagram showing the concept of a method by which a comparison unit determines combination conditions. [Figure 21] (A) and (B) are diagrams showing an example of a notification screen. [Figure 22] (A) and (B) are diagrams showing an example of a notification screen. [Figure 23] (A) and (B) are diagrams showing an example of a notification screen. [Figure 24] (C) and (D) are diagrams showing an example of a notification screen. [Figure 25] (E) is a diagram showing an example of a notification screen. [Figure 26] (A) and (B) are diagrams showing an example of a notification screen. [Figure 27] (C) and (D) are diagrams showing an example of a notification screen. [Figure 28](E) and (F) are diagrams showing examples of notification screens. [Figure 29] This figure shows an example of notification screen 300. [Figure 30] (A) and (B) are diagrams showing examples of notification screens. [Figure 31] (E) is a diagram showing an example of a notification screen. [Figure 32] This is a flowchart illustrating the process of processing mobile phone notifications. [Figure 33] This is a flowchart illustrating the process of processing mobile phone notifications. [Figure 34] This is a flowchart illustrating the process of processing mobile phone notifications. [Figure 35] (A) through (C) are diagrams illustrating an example of a method for identifying regions in which the relevant specific unit can improve measurement accuracy. [Figure 36] This is a flowchart illustrating the flow of administrator output processing. [Figure 37] (A) and (B) are diagrams showing examples of administrator notification screens. [Figure 38] (C) and (D) are diagrams showing examples of administrator notification screens. [Figure 39] Figures (E) and (F) show examples of administrator notification screens. [Figure 40] (A) and (B) are diagrams showing examples of notification screens. [Figure 41] This is a flowchart illustrating the process of notifying the population count. [Figure 42] (A) is a diagram showing an example of the population count notification screen, and (B) is a diagram showing an example of the population count screen. [Figure 43] (C) and (D) are diagrams showing examples of population count screens. [Figure 44] (E) is a diagram showing an example of a population count screen. [Figure 45] (A) is a diagram showing an example of the population count notification screen, and (B) is a diagram showing an example of the population count screen. [Figure 46] (C) is a diagram showing an example of a population count screen. [Figure 47] (A) is a diagram showing an example of the population count notification screen, and (B) is a diagram showing an example of the population count screen. [Figure 48] (C) is a diagram showing an example of a population count screen. [Figure 49] (A) and (B) are diagrams showing examples of notification screens as variations. [Modes for carrying out the invention]

[0008] The present disclosure will be described in detail below with reference to the attached drawings. Figure 1 shows an example of the overall configuration of support system 1. Support System 1, as an example of an information processing system, is a system that helps users understand information about a detected object S by detecting the object S and notifying the user of information about the detected object S. Examples of detected objects S include living organisms and non-living objects. Examples of living organisms include animals, plants, and fungi. Examples of animals include primates such as humans, mammals such as bears, birds such as crows, reptiles such as turtles, and insects such as beetles. Examples of objects include landmines, narcotics, and stimulants. However, the detected object S may be different from any of the above, as long as it can be detected by Support System 1. The detected object S may also be a combination of the above-mentioned detection targets. Information about the detected object that is notified to the user may include, for example, information indicating the type of detected object, information indicating the individual detected object, information indicating the location of the detected object, and information indicating the number of detected objects.

[0009] Support system 1 comprises a sensor 10, a management server 20, an administrator terminal 30, a user terminal 40, a camera 50, and a wind direction and speed meter 60. The sensor 10, the management server 20, the camera 50, and the wind direction and speed meter 60 are each connected via a network 70. The management server 20, the administrator terminal 30, and the user terminal 40 are also each connected via the network 70.

[0010] Sensor 10, as an example of a measuring device, measures components generated from the object to be detected S. Examples of components measured by sensor 10 include volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), and gaseous components. In other words, the components measured by sensor 10 are components that are recognized by humans as odors. Examples of gaseous components include gases containing inorganic compounds, gases generated by the metabolism of living organisms, gases generated by fermentation, and gases generated by decomposition. Components generated from the object to be detected S include components generated with the object to be detected S as the source, and components generated with substances released from the object to be detected S as the source. Examples of components generated with the object to be detected S as the source include components generated as body odor, and components generated from the surface or inside the body of the object to be detected S. Furthermore, substances emitted from the detected object S include, for example, breath, sebum, secretions, feces, urine, saliva, sweat, hair, feathers, skin flakes, scales, bodily fluids, other excretions, substances detached from the detected object S, and substances attached to the detected object S. It should be added that substances emitted from the detected object S include not only substances that are expelled from the detected object S and exist separately from it, but also substances that are emitted from the detected object S and remain on its surface. Also, components generated as body odor can be considered as components originating from the detected object S, or as components generated from substances emitted from the detected object S. The aforementioned body odor, breath, sebum, secretions, substances originating from the body surface or inside the body of the detected subject S, feces, urine, saliva, sweat, hair, feathers, skin fragments, scales, bodily fluids, other excretions, substances detached from the detected subject S, and substances attached to the detected subject S are not components themselves, but they contain components and can be considered as media for the release of components into the air. Furthermore, the sensor 10 may have a suction means, such as a suction pump, for aspirating components.

[0011] Sensor 10 performs measurements continuously. When sensor 10 measures a new component, it transmits result information, which is information indicating the latest measurement result, to the management server 20, associating it with date and time information indicating the date and time the measurement was performed and identification information identifying the sensor 10 that performed the measurement. The result information transmitted from sensor 10 may include the measured value, the change in the measured value over time, or feature quantities extracted from these. Sensor 10 also transmits the above information to the management server 20 periodically. The period during which sensor 10 transmits information to the management server 20 may be any time. Furthermore, sensor 10 does not need to transmit periodically if it repeatedly transmits information to the management server 20.

[0012] Sensor 10 can be a so-called odor sensor. However, sensor 10 is not limited to an odor sensor. Sensor 10 can be any type of sensor, regardless of the principle and configuration of measurement, as long as it is capable of measuring components generated from the object to be detected S and components generated from substances released from the object to be detected S. Furthermore, when a sensor of a different type than an odor sensor, such as a particle measuring instrument, is used as sensor 10, the components generated from the object to be detected S can include not only the components mentioned above, but also aerosols, fine particles, etc. Other examples of sensors different from odor sensors include gas sensors that measure the concentration of gas components, sensors that output measurement results according to combinations of multiple gas components, and sensors that detect changes in electrical resistance, impedance, voltage, or current due to the adsorption of components generated from a source. Sensor 10 may also be a sensor that measures optical properties based on absorption, reflection, or scattering by components generated from a source. In addition, sensor 10 only needs to be capable of detecting changes in physical or chemical quantities caused by components generated from a source.

[0013] Furthermore, the sensor 10 includes a fixed sensor 11 and a portable sensor 12. When explaining without specifically distinguishing between the fixed sensor 11 and the portable sensor 12, they will be referred to simply as sensor 10. The fixed sensor 11 performs measurements while being installed in a fixed position. In the illustrated example, the support system 1 is provided with two fixed sensors 11, but the number of fixed sensors 11 provided in the support system 1 can be any number. The portable sensor 12 is a portable sensor. In this disclosure, measurements are taken by the portable sensor 12 while a moving object M is carrying the portable sensor 12. Therefore, the portable sensor 12 performs measurements while moving. In other words, the measurement position of the portable sensor 12 changes over time as the moving object M moves. Examples of the moving object M include drones, vehicles, aircraft, ships, operating robots, and animals such as humans. The portable sensor 12 may be equipped with positioning means, for example. The portable sensor 12 periodically transmits location information indicating the current location acquired by the positioning means to the management server 20, along with information identifying the portable sensor 12, which is the source of this location information. Alternatively, the moving object M may be equipped with positioning means and periodically transmit location information indicating the current location acquired by the positioning means to the management server 20, along with information identifying the moving object M, which is the source of this location information. Examples of positioning means include GPS (Global Positioning system), wireless base stations, and Wi-Fi. In the illustrated example, the support system 1 is equipped with one portable sensor 12, but the number of portable sensors 12 provided in the support system 1 can be any number.

[0014] The management server 20 is a server device that manages the information generated in the support system 1. When the management server 20 receives result information from the sensor 10, it identifies the source of the component measured by the sensor 10 based on the received result information by comparing it with pre-stored information or with multiple result information. The source identified by the management server 20 may include the type of source and the individual source. In addition, the management server 20 may further identify the location of the source and, if the source is an animal, the range of the source's activity. The management server 20 transmits information indicating the identified source to the administrator terminal 30 and the user terminal 40. The source of the component measured by the measurement means such as the sensor 10 may be simply referred to as the source below. The source identified by type or individual by the management server 20 is considered as the detected object S (see Figure 1). Furthermore, the management server 20 counts the number of individuals identified as sources of the components measured by the sensor 10. The management server 20 then transmits information indicating the counting results to the administrator terminal 30 and the customer terminal 40.

[0015] The management server 20 is implemented, for example, by a computer. The management server 20 may consist of a single computer, or it may be implemented through distributed processing by multiple computers. Alternatively, the management server 20 may be implemented on virtual hardware provided by cloud computing.

[0016] In this way, the source of the component measured by sensor 10 is identified by the management server 20. Therefore, sensor 10 and management server 20 can also be considered as detection devices for detecting a target object. Furthermore, in a detection device, sensor 10, which measures the component, can also be considered as a detection means for detecting a target object. The target object can be the source of the component measured by sensor 10.

[0017] The administrator terminal 30 is a terminal device owned by the administrator of the support system 1. In this disclosure, the support system 1 is provided with an administrator terminal 30 for each administrator of the support system 1. The customer terminal 40 is a terminal device owned by a customer of the support system 1. In this disclosure, the support system 1 is provided with a customer terminal 40 for each customer of the support system 1. Furthermore, both the administrator and the user of Support System 1 are considered users of Support System 1. In the following explanation, when the administrator terminal 30 and the user terminal 40 are not specifically distinguished, they may be referred to as user terminals. Examples of user devices include smartphones. Other examples of user devices include computers such as tablet PCs, laptops, or desktop PCs.

[0018] Camera 50 photographs the subject. The field of view of camera 50, in other words, the area photographed by camera 50, is the area where the source of the component measured by sensor 10 may exist. Camera 50 may continuously shoot video. Camera 50 transmits the captured image to the management server 20, associating it with information indicating the time of capture and information identifying camera 50 as the source of the image. In this disclosure, camera 50 periodically transmits images to the management server 20. The period at which camera 50 transmits images to the management server 20 may be any time. In the illustrated example, one camera 50 is provided in the support system 1, but the number of cameras 50 provided in the support system 1 may be any number.

[0019] The anemometer 60 measures wind direction and wind speed. The anemometer 60 is installed in the same space as the sensor 10. The same space means the same outdoor space or the same indoor space. The anemometer 60 may also be installed near the sensor 10. For example, a location within a range of several meters to several hundred meters from the sensor 10 could be near the sensor 10. However, the location where the anemometer 60 is installed near the sensor 10 can be any location. The anemometer 60 may also be installed in an environment that is identified as being under the same airflow influence as the sensor 10 for each sensor 10. The anemometer 60 transmits information indicating the measurement result to the management server 20, associated with information indicating the time of measurement and information identifying the anemometer 60 that is the source of the information. In this disclosure, the anemometer 60 periodically transmits the latest measurement result to the management server 20. The period at which the wind direction and speed meter 60 transmits the measurement results to the management server 20 may be any time. In the illustrated example, the support system 1 is equipped with two wind direction and speed meters 60, but the number of wind direction and speed meters 60 equipped in the support system 1 may be any number. In addition, a wind direction and speed meter 60 may be provided for each sensor 10.

[0020] Network 70 is not particularly limited in type, as long as it is capable of sending and receiving data. Examples of Network 70 include the Internet, LAN (Local Area Network), WAN (Wide Area Network), and 4G (4G). th Generation Mobile Communication) and 5G (5 th Examples include mobile communication systems such as Generation Mobile Communication. Furthermore, the communication lines used for sending and receiving data in network 70 may be wired or wireless. Also, network 70 may be configured to connect each device in support system 1 via multiple communication lines.

[0021] Next, we will describe the hardware configuration of the management server 20, the administrator terminal 30, and the user terminal 40. Figure 2 shows an example of the hardware configuration of the management server 20, administrator terminal 30, and customer terminal 40. In the following description, the management server 20, administrator terminal 30, and customer terminal 40 may be collectively referred to simply as "computer." As shown in Figure 2, the computer includes a processor 101, ROM 102, RAM 103, auxiliary storage device 104, display unit 105, operation reception unit 106, speaker 107, microphone 108, and communication IF 109.

[0022] The processor 101 is a device that realizes various functions through the execution of a program. The processor 101 may include, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), and a DSP (Digital Signal Processor). The processor 101 may consist of a single processor or may consist of multiple processors located in physically separate locations. ROM102 is a memory area that stores control programs such as the BIOS (Basic Input Output System), various setting information, and so on. RAM103 is the workspace for processor 101. The auxiliary storage device 104 stores programs executed by the processor 101 and various types of data. Examples of auxiliary storage devices 104 include HDDs (Hard Disk Drives) and non-volatile storage devices such as semiconductor storage. Examples of programs include operating systems (OS) and application programs.

[0023] The display unit 105 displays information. Examples of the display unit 105 include liquid crystal displays and organic EL (Electro-Luminescence) displays. The operation reception unit 106 receives input from the computer. Examples of the operation reception unit 106 include a keyboard, mouse, capacitive touch sensor, switch, and remote controller. The combination of computer type and operation reception unit 106 type is not limited to any combination. For example, the display unit 105 and operation reception unit 106 may both be touch panels. Speaker 107 outputs sound. Microphone 108 is used for sound input. More specifically, microphone 108 converts the input sound into digital data. The communication interface 109 is used for communication with external devices. The communication interface 109 may also be used to perform a portion of the processing performed by the processor 101 in cooperation with an external computer.

[0024] The processor 101 and various devices (ROM 102, RAM 103, auxiliary storage device 104, display unit 105, operation reception unit 106, speaker 107, microphone 108, communication IF 109) are connected via buses and other signal lines. In this disclosure, the processor 101 reads programs stored in the ROM 102 and auxiliary storage device 104, thereby executing various processes performed by the computer. Note that a computer does not necessarily need to have all of the components shown in the diagram. Depending on its application and implementation, a computer may not have all of the components.

[0025] Figure 3 shows an example of the functional configuration of the management server 20. The management server 20 includes a transmission / reception unit 201, a storage unit 202, a timing unit 203, a graph generation unit 204, a comparison unit 205, a source identification unit 206, a related identification unit 207, a counting unit 208, a condition determination unit 209, an information generation unit 210, a target determination unit 211, and an information provision unit 212. Each of the functions of the management server 20 described above is realized through the cooperation of the management server 20's hardware and programs. Note that the management server 20 does not necessarily need to have all the functional units shown in Figure 3. Some of the functional units shown in Figure 3 of the management server 20 may be omitted or integrated into other functional units.

[0026] The transmitting / receiving unit 201 transmits and receives information to and from external devices such as the sensor 10, administrator terminal 30, user terminal 40, camera 50, and wind direction and speed meter 60. Information received by the transmitting / receiving unit 201 includes result information transmitted from the sensor 10, information indicating requests from user terminals, images captured by the camera 50, and information indicating measurement results from the wind direction and speed meter 60. The transmitting / receiving unit 201 also receives information entered into the management server 20 when the administrator of the support system 1 operates the management server 20. Information transmitted by the transmitting / receiving unit 201 includes information to be notified to user terminals. When the transmitting / receiving unit 201 receives an information request from a user terminal, it transmits the requested information to the recipient. The storage unit 202 stores information received by the transmitting / receiving unit 201, information generated by the management server 20, and the like. The timing unit 203 performs timing.

[0027] The graph generation unit 204 generates a graph showing the measurement results of the sensor 10 based on the result information acquired by the transmission / reception unit 201. More specifically, the graph generation unit 204 graphs the measured values ​​of the sensor 10 per unit time, or the measured values ​​for each measurement position of the sensor 10, which are identified from the result information. The graph generation unit 204 stores the generated graph in the storage unit 202, associating it with the identification information and date / time information associated with the result information used to generate the graph. The graph generation unit 204 may generate a graph from a single piece of result information, or it may generate a graph from multiple pieces of result information intermittently transmitted from the same sensor 10. Furthermore, the graph generation unit 204 may generate graphs using the same method for result information transmitted from the fixed sensor 11 and result information transmitted from the portable sensor 12, or it may generate graphs using different methods.

[0028] The comparison unit 205 compares the graphs generated by the graph generation unit 204. The comparison unit 205 may also compare graphs generated by the graph generation unit 204 with each other. Alternatively, the comparison unit 205 may compare graphs generated by the graph generation unit 204 with graphs generated without the graph generation unit 204. An example of a graph generated without the graph generation unit 204 is a graph generated by a computer device and stored in the storage unit 202 as the measured values ​​of the sensor 10 per unit time when components generated from a predetermined type of source are measured by the sensor 10.

[0029] When a new graph is generated by the graph generation unit 204, the comparison unit 205 compares the newly generated graph with the graph to be compared. As will be described in detail later, the graph newly generated by the graph generation unit 204 is the graph whose source of the measured value component shown in this graph is identified by the source identification unit 206 as a result of the comparison. For this reason, the graph newly generated by the graph generation unit 204 may be referred to as the identified target graph below. The source of the measured value component shown in the identified target graph may be referred to as the identified target source below. The graph to be compared with the identified target graph may be referred to as the comparison target graph below. The comparison target graph may be any graph stored in the storage unit 202, or it may be limited to graphs with the same attributes as the identified target graph. When the comparison is performed, the comparison unit 205 may extract the graph with the highest degree of agreement with the shape of the identified target graph from among the comparison target graphs. In addition, addition, normalized addition, correlation coefficient, or distance between feature vectors may be used to identify the degree of agreement. The comparison unit 205 then associates the extracted comparison target graph with comparison information, which is information indicating the results of the comparison, and transmits it to the source identification unit 206. Examples of comparison results shown in the comparison information include an index indicating the degree of similarity between the graph newly generated by the graph generation unit 204 and the comparison target graph.

[0030] Furthermore, the comparison graphs include graphs showing measured values ​​for sources where the species is identified, and graphs showing measured values ​​for sources where the individual is identified. The species that have been identified as the source of the component related to the measured values ​​shown in the comparison graph may be referred to as the comparison species below. Similarly, the individual that has been identified as the source of the component related to the measured values ​​shown in the comparison graph may be referred to as the comparison individual below. The comparison unit 205 extracts the graph that is most similar to the identified target graph for each of the comparison graphs related to sources where the species is identified and the comparison graph related to sources where the individual is identified, and transmits the extracted comparison graph to the source identification unit 206.

[0031] The source identification unit 206 identifies the type or individual source of the component measured by the sensor 10 based on the comparison results from the comparison unit 205. The source identification unit 206 stores the information indicating the identified content in the storage unit 202. The source identification unit 206 determines whether the comparison information associated with the comparison graph extracted by the comparison unit 205 as the most similar to the identified target graph among the comparison graphs for which the type of source has been identified satisfies the type identification conditions. The type identification conditions are conditions used by the source identification unit 206 to determine whether or not to identify the type of source. In this disclosure, the degree of similarity shown in the comparison information is defined as satisfying a predetermined standard as the type identification condition. For example, a predetermined standard may be that the degree of agreement between the identified target graph and the comparison graph is 95% or higher. If the comparison information satisfies the type identification conditions, the source identification unit 206 identifies the comparison type related to the comparison graph associated with this comparison information as the type of source of the identified target.

[0032] Furthermore, if no comparative information exists that satisfies the type identification conditions, the source identification unit 206 determines whether or not there is a comparative graph that satisfies the candidate identification conditions. The candidate identification conditions are conditions used by the source identification unit 206 to determine whether or not to identify a candidate for the type of source. In this disclosure, the degree of similarity between the shape of the comparative graph and the shape of the identified target graph is defined as a predetermined standard as a candidate for the type of source. For example, a predetermined standard may be that the degree of agreement between the identified target graph and the comparative graph is 75% or higher. The source identification unit 206 identifies the comparative type related to the comparative graph that satisfies the candidate identification conditions as a candidate for the type of source of the identified target. Furthermore, if there are multiple comparative graphs that satisfy the candidate identification conditions, the source identification unit 206 identifies each of the comparative types related to the comparative graph that satisfies the candidate identification conditions as a candidate for the type of source of the identified target.

[0033] Furthermore, the source identification unit 206 determines whether the comparison information associated with the comparison graph extracted by the comparison unit 205 as the most similar to the identified source graph among the comparison graphs for which individuals have been identified satisfies the individual identification conditions. The individual identification conditions are the conditions used by the source identification unit 206 to identify the individual of the source. In this disclosure, the degree of similarity shown in the comparison information is defined as satisfying a predetermined standard as the individual identification condition. For example, a predetermined standard may be that the degree of agreement between the identified source graph and the comparison graph is 99% or higher. If the comparison information satisfies the individual identification conditions, the source identification unit 206 identifies the comparison individual related to the comparison graph associated with this comparison information as the individual of the identified source. If the comparison information does not satisfy the individual identification conditions, the source identification unit 206 may identify the identified source as a new individual. The criteria predetermined for individual identification, species identification, and candidate identification may be set according to the environment in which the sensor 10 is measured, the characteristics of the sensor 10, and other circumstances that identify the source.

[0034] The related identification unit 207 identifies information related to the source identified by the source identification unit 206, either by type or individual. Examples of information identified by the related identification unit 207 include the location of the source, the attributes of the source, the size of the source, and, if the source is an animal, the details of its movement. Other examples of information identified by the related identification unit 207 include the type of source of the component related to the measurement value shown in the target graph, and the period from the time the component related to the measurement value shown in the target graph is generated until it is measured by the sensor 10. Furthermore, the related identification unit 207 identifies information used by the management server 20 to determine whether or not to notify the user. The related identification unit 207 stores the information indicating the identified information in the storage unit 202.

[0035] The counting unit 208 counts the number of individuals identified by the source identification unit 206. More specifically, the counting unit 208 counts the number of individuals for each attribute of the source identified by the related identification unit 207. The counting unit 208 stores information indicating the counting results in the storage unit 202. The condition determination unit 209 determines whether predetermined conditions are met in the management server 20. The conditions that the condition determination unit 209 determines are those used in various processes in the management server 20. The condition determination unit 209 transmits information indicating the result of the determination to the information generation unit 210 and the target determination unit 211.

[0036] The information generation unit 210 generates information to be notified to the user terminal based on the result of the determination by the condition determination unit 209. The information generation unit 210 generates information according to the content identified by the source identification unit 206 or the related identification unit 207. The information generation unit 210 also generates information according to the result of the counting by the counting unit 208. The information generation unit 210 also generates information according to the result of the determination by the condition determination unit 209. The target determination unit 211 determines the users to whom the information generated by the information generation unit 210 will be provided, based on the results of the determination by the condition determination unit 209. Based on the results of the determination by the condition determination unit 209, the target determination unit 211 determines the user terminal to which the information will be provided, in accordance with the user's attributes, settings on the user terminal, etc., thereby determining the administrators and consumers to whom the information will be provided. The information provision unit 212 provides the information generated by the information generation unit 210 to the user terminal that has been determined by the target determination unit 211 as the target for information provision. More specifically, the information provision unit 212 provides the information by outputting it via the transmission / reception unit 201.

[0037] In this disclosure, the processor 101 of the management server 20 reads and executes a program stored in the ROM 102 or auxiliary storage device 104. This enables the functions of the transmission / reception unit 201, timing unit 203, graph generation unit 204, comparison unit 205, source identification unit 206, related identification unit 207, counting unit 208, condition determination unit 209, information generation unit 210, target determination unit 211, and information provision unit 212. In addition, in this disclosure, the functions of the storage unit 202 are realized by the ROM 102, RAM 103, or auxiliary storage device 104 of the management server 20.

[0038] Figure 4 shows an example of a sensing means management table. The sensing means management table is a table used by the management server 20 to manage sensing means that detect changes in state. Examples of sensing means that are managed by the sensing means management table include the sensor 10, the camera 50, and the wind direction and speed meter 60. The sensing means management table is stored in the storage unit 202 of the management server 20. The sensing means management table shows the "No.", "Type", "Fixed", "Installation Location", and "Result" associated with each other. Note that the "..." shown in the sensing means management table indicates that the entry has been omitted.

[0039] The contents of the information shown in the sensing means management table will be explained in detail. The "No." indicates a number that identifies the sensing device. The "Type" column indicates the type of sensing device. "Sensor" in the "Type" column means that the sensing device is sensor 10. Similarly, "Camera" in the "Type" column means that the sensing device is camera 50. Furthermore, "Anemometer" in the "Type" column means that the sensing device is anemometer 60.

[0040] The "Fixed" column indicates whether the sensing means is installed in a fixed position or not. A "○" next to "Fixed" means that the sensing means is installed in a fixed position. A "×" next to "Fixed" means that the position of the sensing means is not limited to a fixed position. In other words, a sensing means that is marked with a "○" next to "Fixed" and "Sensor" next to "Type" is a fixed sensor 11. A sensing means that is marked with a "×" next to "Fixed" and "Sensor" next to "Type" is a portable sensor 12. As shown in the sensing means management table, there are cameras 50 that are installed in a fixed position and cameras 50 whose position is not fixed. However, any camera 50 may be installed in a fixed position. The "installation location" indicates the installation location of the sensing means. While details are omitted, the "installation location" may, for example, indicate the coordinates of the location where the sensing means is installed. Furthermore, the "installation location" of the portable sensor 12 may indicate the coordinates of the location identified from the latest location information transmitted from the portable sensor 12 or the mobile body M.

[0041] The "Results" section shows the results of the sensing by the sensing means. More specifically, if the sensing means is a sensor 10, the "Results" section shows the measurement results from the sensor 10; if the sensing means is a camera 50, the "Results" section shows the results of the images taken by the camera 50; and if the sensing means is an anemometer 60, the "Results" section shows the measurement results from the anemometer 60. In addition, the "Results" section shows the time of sensing in relation to the results of the sensing by the sensing means. In addition, the "Result" associated with the "Sensor" shown in "Type" may show result information, or it may show a graph generated by the graph generation unit 204.

[0042] For example, the administrator of support system 1 may input information into the "No.", "Type", "Fixed", and "Installation Location" fields of the sensing means management table by operating the management server 20. Furthermore, each time the transmitting / receiving unit 201 of the management server 20 receives information indicating the measurement results from the sensor 10 and the wind direction / speed meter 60, it stores the received information in the "Result" field of the target sensing means in the sensing means management table, associating it with the measurement time. Also, each time the graph generation unit 204 generates a graph, it may store the generated graph in the "Result" field of the target sensor 10 in the sensing means management table, associating it with the measurement time related to the result information used for generation. Additionally, each time the transmitting / receiving unit 201 of the management server 20 receives an image from the camera 50, it stores the received image in the "Result" field of the target sensing means in the sensing means management table, associating it with the time of capture. As a result, "Result" stores information indicating the results of sensing by the sensing means. Note that the configuration and items of the sensing means management table are examples only and are not limited to the illustrated example.

[0043] Figure 5 shows an example of a type management table. The type management table is a table for managing the types of source materials of components that can be measured by measuring means such as the sensor 10. The type management table is stored in the storage unit 202 of the management server 20. The category management table shows the following associated fields: "Category," "Graph," "Gender," "Age (years)," "Height (m)," "Weight (kg)," "Source," "Duration (seconds)," and "Distance (m)." Note that the "..." shown in the category management table indicates that the entry has been omitted.

[0044] This section will provide a detailed explanation of the information displayed in the category management table. The "Type" column indicates the type of source. Specifically, "Type" shows examples of animal types such as "bear," "wild boar," "deer," "fox," "raccoon dog," "crested ibis," and "human." It also shows examples of plant types such as "apple." Furthermore, "Type" shows examples of object types such as "landmine." The "graph" shows a graph of the measured values ​​of the components generated from the source, measured per unit time by a different measurement method. The measured values ​​shown in the graph may be measured by sensor 10, or by a different measurement method (not shown) than sensor 10.

[0045] The "sex" field indicates the sex of the source when the source is an animal. The "Age (years)" column indicates the age of the source of the outbreak if the source is an animal. The "Height (m)" column indicates the height of the source in meters, if the source is an animal. The "Weight (kg)" column indicates the weight of the source in kilograms, if the source is an animal. Furthermore, source attributes such as "gender," "age (years)," "height (m)," and "weight (kg)" are managed according to the type of source and do not need to be set for all sources. Furthermore, source attributes such as "gender," "age (years)," "height (m)," and "weight (kg)" may be identified by the management server 20 based on measurement results from the measurement means, or they may be information pre-set by the administrator.

[0046] The "Source" column indicates the type of source of the component that is the subject of the measurement shown in the "Graph". The "Period (seconds)" column indicates the time, in seconds, from when the component originates from the "source" into the same space as the measuring device until this component is measured by the measuring device. The "Distance (m)" indicates the distance from the "source" to the measuring device, expressed in meters.

[0047] In this disclosure, the administrator of support system 1 writes the type, gender, age, height, weight, and source of the source that is the target of measurement by the measurement means, associating them with the "type", "gender", "age (years)", "height (m)", "weight (kg)", and "source" fields in the type management table. The measurement means measures the components emitted from the source at a location a distance from the source indicated by "distance (m)". The graph obtained as a result of this measurement is stored as "graph" in the type management table. This graph may be generated by the graph generation unit 204 based on the measurement results by the measurement means, or it may be generated by a device other than the management server 20. The administrator also writes the time from when the components are emitted from the source until the measurement by the measurement means is performed into "duration (seconds)" in the type management table. As a result, the information of "type", "graph", "gender", "age (years)", "height (m)", "weight (kg)", "source", "duration (seconds)", and "distance (m)" is stored as being associated with each other in the type management table. Note that the structure and items of the category management table are examples only and are not limited to the example shown.

[0048] Figure 6 shows an example of a notification target management table. The notification target management table is a table used by the management server 20 to manage the relationship between the type of source and the target of notifications to users. The notification target management table is stored in the storage unit 202 of the management server 20. The notification target management table shows the "Type," "Recommended Type," "Required Type," and "Target Type" in relation to each other. Note that the "..." shown in the notification target management table means that the entry has been omitted.

[0049] This section provides a detailed explanation of the information displayed in the notification target management table. The "Type" column indicates the type of source. In the example shown, the "Type" column includes at least "Bear," "Wild Boar," "Deer," "Fox," "Raccoon Dog," "Crested Ibis," "Human," "Apple," and "Landmine." The "Recommended Type" column indicates whether the management server 20 recommends notifying the user if it detects a source within a predetermined area. A "○" in the "Recommended Type" column means that notification to the user is recommended for that type. A "×" in the "Recommended Type" column means that notification to the user is not recommended for that type. In the example shown, "○" is shown for the "Recommended Type" of "Bear," "Wild Boar," "Deer," "Fox," "Raccoon Dog," and "Landmine," while "×" is shown for the "Recommended Type" of "Ibis," "Human," and "Apple."

[0050] The "Required Type" column indicates whether the management server 20 determines that notification to the user is mandatory when it detects a source in a predetermined area. A "○" in the "Required Type" column means that notification to the user is mandatory for that type. A "×" in the "Required Type" column means that notification to the user is not mandatory for that type. Note that the areas in which the management server 20 determines whether a source is a "Required Type" are different from the areas in which it determines whether a source is a "Recommended Type". In the example shown, "○" is shown for "Bear," "Wild Boar," "Deer," "Fox," and "Landmine," while "×" is shown for "Raccoon Dog," "Ibis," "Human," and "Apple." It should also be noted that the number of applicable "Types" is limited compared to "Recommended Types."

[0051] The "Target Type" column indicates whether the management server 20 determines that a source detected within a predetermined area is a "type" that should be notified to the user. A "○" in the "Target Type" column means that the type is determined to be subject to notification to the user. A "×" in the "Target Type" column means that the type is not determined to be subject to notification to the user. Note that the area in which the management server 20 determines whether a source is a "Target Type" when it detects a source is different from the area in which it determines whether a source is a "Recommended Type" when it detects a source, and the area in which it determines whether a source is a "Required Type" when it detects a source. In the example shown, "○" is shown for the "Target Type" of "Bear," "Wild Boar," "Apple," and "Landmine," while "×" is shown for the "Target Type" of "Deer," "Fox," "Raccoon Dog," "Ibis," and "Human." It should also be noted that the number of applicable "Types" is limited compared to the "Required Type." Note that the "Recommended Type," "Required Type," and "Target Type" may be set independently of each other, or they may be set to partially overlap. For example, the administrator of support system 1 may input information into the "Type," "Recommended Type," "Required Type," and "Target Type" fields of the notification target management table by operating the management server 20. Please note that the structure and items of the notification target management table are examples only and are not limited to the example shown.

[0052] Figure 7 shows an example of an individual management table. The individual management table is a table for managing sources that have been identified as individuals by the source identification unit 206. The individual management table is stored in the storage unit 202. The individual management table displays the following information, associated with each other: "No.", "Species", "Sex", "Age (years)", "Height (m)", "Weight (kg)", "Number of Detections", and "History". Note that the "..." shown in the individual management table indicates that the entry has been omitted.

[0053] Let's explain the contents of the individual management table in detail. The "No." indicates a number that identifies the source as an individual by the source identification unit 206. The "Type" column indicates the type of source identified by the source identification unit 206. In the case where the source is identified as an animal, the "sex" field indicates the sex of the source identified in the relevant identification section 207. In the "Age (years)" column, if the source is identified as an animal, the age of the source identified in the relevant identification section 207 is shown. In the "Height (m)" column, if the source is identified as an animal, the height of the source identified in the relevant identification section 207 is shown in meters. In the case where the source is identified as an animal, the "Weight (kg)" column indicates the weight of the source identified in the relevant identification section 207 in kilograms. Furthermore, source attributes such as "gender," "age (years)," "height (m)," and "weight (kg)" are managed according to the type of source and are not set for all sources.

[0054] The "Detection Count" indicates the number of times the source identification unit 206 detected a source based on the result information. In other words, the "Detection Count" indicates the number of times the same individual was identified. The "History" section shows the history of the source identified as an individual by the source identification unit 206. For example, the "History" of a source whose "Type" is animal shows the history of the source's behavior, the history of the source's location, etc.

[0055] The source identification unit 206 writes "No." and "Type" according to the information it has identified about the source. The related identification unit 207 also writes information in "Gender," "Age (years)," "Height (m)," and "Weight (kg)" according to the information it has identified about the source. Furthermore, each time the source identification unit 206 identifies a source as the same individual, it updates the "Detection Count" associated with the identified individual. In addition, for example, the administrator of the support system 1 can input information into the "History" by operating the management server 20. Alternatively, the related identification unit 207 may write the identified information into the "History." Note that the structure and items of the individual management table are examples only and are not limited to the example shown.

[0056] Figure 8 shows the results management table. The results management table is a table used by the management server 20 to manage result information. The results management table is stored in the storage unit 202. The results management table displays the following associated fields: "No.", "Result Information", "Individual", "Type", "Candidate", "Graph", "Sensor", "Measurement Date and Time", "Location", "Source", "Duration (seconds)", and "Distance (m)". Note that the "..." shown in the results management table indicates that the entry has been omitted.

[0057] Let's explain the contents of the results management table in detail. The "No." column contains a number that identifies the result information. The "Result Information" section displays the result information. The "Individual" field displays a number that identifies the individual that is the source of the component being measured in the "Result Information." The number displayed in "Individual" has the same meaning as the number displayed in "No." in the individual management table (see Figure 7). If the source individual has not been identified, no number is displayed in "Individual." The "Type" field indicates the type identified by the source identification unit 206 for the source of the component being measured in the "Result Information." If the type of source is not identified, no information is entered in the "Type" field. In the "Candidates" field, when the type of source of the component being measured related to the "Result Information" has not been identified, the source identification unit 206 displays the candidate types identified. If no candidate types of source have been identified, no information is entered in the "Candidates" field.

[0058] The "Graph" section displays the graph generated by the graph generation unit 204 based on the "Result Information". The "Sensor" field displays a number that identifies the sensor 10 that performed the measurement, which is the subject of the "Result Information." This number is derived from the identification information associated with the "Result Information." The number displayed in "Sensor" has the same meaning as the number displayed in "No." in the sensing means management table (see Figure 4). The "Measurement Date and Time" field indicates the date and time of the measurement, as identified from the date and time information associated with the "Result Information." The "Location" field indicates the measurement location of the "Sensor". If the "Sensor" is a fixed sensor 11, the administrator may input the "Location" by operating the management server 20. If the "Sensor" is a portable sensor 12, the management server 20 may input the location identified from the location information transmitted from the portable sensor 12 along with the "Result Information" into the "Location" field. Furthermore, if the related identification unit 207 has identified the location of the "Type" or "Individual", it may input the identified location into the "Location" field.

[0059] The "Source" field indicates the type of component identified by the relevant identification unit 207 as the source of the component being measured in the "Result Information." If the source is not identified, no information is entered in the "Source" field. The "Period (seconds)" field indicates the time, in seconds, that has been identified by the related identification unit 207 as the period from when the component from the "source" is generated in the same space as the "sensor" until this component is measured by the "sensor". If no period is identified, no information is entered in the "Period (seconds)" field. The "Distance (m)" field shows the length in meters, as specified by the related identification unit 207, as the distance from the "source" to the "sensor". If the distance is not specified, no information is entered in the "Distance (m)" field.

[0060] When the transmitting / receiving unit 201 receives result information, date and time information, and identification information from the sensor 10, it writes "No.", "Result Information", "Sensor", and "Measurement Date and Time" to the result management table. The graph generation unit 204 writes the graph generated based on the result information to "Graph". The source identification unit 206 writes information to "Individual", "Type", and "Candidate" according to the identified content. The related identification unit 207 writes information to "Source", "Period (seconds)", and "Distance (m)" according to the identified content. Note that the structure and items of the results management table are examples only and are not limited to the example shown.

[0061] Figure 9 shows an example of a population management table. The population management table is a table for managing the number of individuals identified by the counting unit 208 for each individual identified by the source identification unit 206, and indicators related to individual management. The population management table is stored in the storage unit 202. A population management table is provided for each species identified by the source identification unit 206 for each source. Figure 9 shows a bear population management table. The population management table shows the "area," "attributes," "specific number," "number to be eradicated," "specific number / number to be eradicated," and "eradication criterion index" associated with each other. Note that the "..." shown in the population management table indicates that the entry has been omitted.

[0062] Let's explain the contents of the population management table in detail. The "Region" section shows areas divided according to their location. In the example shown, the "Region" section shows areas within Japan divided according to their respective locations. In the example shown, the "Region" section is further divided into "Prefectures," "Cities / Towns / Villages," and "Smallest Regions." The term "prefecture" refers to the prefectures of Japan, which are territories divided according to their location within the country. The term "municipalities" refers to municipalities that are divided into areas within a prefecture according to their location. The "Minimum Area" column displays a number that identifies the smallest unit of area divided according to the corresponding location. The number shown in the "Minimum Area" column has the same meaning as the number shown in the "Area" column of the sensing means management table (see Figure 4).

[0063] The "Attributes" section shows the attributes identified in the relevant identification unit 207 regarding the source. The "specified number" indicates the number of individuals identified by the source identification unit 206 for the source of the outbreak, as counted by the counting unit 208. The "Number of individuals exterminated" column shows the number of individuals that were exterminated. In the illustrated example, the "specific number" and "number to be eradicated" are shown for each "attribute" of the individual located in the smallest area.

[0064] The "Specific Number / Number Exterminated" column shows the value obtained by dividing the specific number by the number exterminated. The "Eradication Criteria Index" indicates the criteria for eradicating species that are subject to management in the population management table. In this disclosure, for example, it is stipulated that eradication is triggered when the "Number of Specified Species / Number of Species Eradicated" is equal to or greater than the "Eradication Criteria Index." Furthermore, the "Eradication Criteria Index" is given values ​​that correspond to the "area." In the illustrated example, the "specific number / number to be eradicated" and the "eradication standard index" are shown for each "minimum area."

[0065] For example, the administrator of support system 1 may input information into "area," "extermination criteria index," and "number of exterminated insects" by operating the management server 20. The counting unit 208 counts the "number of individuals" and the "number of individuals / number of individuals exterminated" for each "area" and "attribute" based on the individual management table (see Figure 7), and writes the counting results. In this case, the counting unit 208 may, for example, use the position of the sensor 10 when the individual's components were measured as the position of that individual, and count the number of individuals in the "area" corresponding to this position. Alternatively, the counting unit 208 may, for example, use the position of the mobile body M when the portable sensor 12 measured the individual's components as the position of that individual, and count the number of individuals in the "area" corresponding to this position. Furthermore, the counting unit 208 may, for example, use the position specified by the related identification unit 207 for that individual as the position of that individual, and count the number of individuals in the "area" corresponding to this position. Furthermore, if an individual whose components have been measured by multiple sensors 10 is located in different "regions" depending on the measurement, only the position related to the most recent measurement may be determined as the position of this individual.

[0066] Furthermore, the counting of "specific number," "exterminated number," and "specific number / exterminated number" by the counting unit 208 may be performed for each "prefecture," each "city / ward / town / village," or each "smallest area." In addition, the counting of "specific number," "exterminated number," and "specific number / exterminated number" by the counting unit 208 may be performed for each of the "areas" and "attributes." Furthermore, if an individual that has been identified and managed in the individual management table is exterminated, the administrator may update the "number exterminated" in the individual count management table by operating the management server 20. Note that the structure and items of the population management table are examples only and are not limited to the example shown.

[0067] Figure 10 shows an example of a user management table. The user management table is used by the management server 20 to manage users of the support system 1. The user management table is stored in the storage unit 202. The user management table shows the relationships between "User," "Attributes," "Management Area," "Residence," "Current Location," "Planned Location," "Mode," "Area," and "Registered Individual."

[0068] Let's explain the contents of the user management table in detail. The "User" field displays information that identifies the user of support system 1. The "Attributes" section shows the user's attributes. "General Public" in the "Attributes" section means the user is a user of Support System 1. "Administrator" in the "Attributes" section means the user is an administrator of Support System 1. The "Management Area" indicates the areas managed by the "User" when the "User" is the administrator of Support System 1.

[0069] The "Place of Residence" field shows the user's place of residence. The "Current Location" indicates the current location of the "User". In this disclosure, the user terminal periodically transmits location information acquired as its current location by a positioning means to the management server 20, along with information identifying the user terminal that is the source of this location information. Examples of positioning means include GPS (Global Positioning system), wireless base stations, and Wi-Fi. When the transmitting / receiving unit 201 of the management server 20 receives location information, it writes the location identified from the received location information to the "Current Location" associated with the "User," who is the owner of the user terminal that is the source of this location information. Even if the "Current Location" is updated with the latest information, the "Current Location" information before the update may be stored in the storage unit 202 as the "User's" past location.

[0070] The “scheduled location” indicates the place the “user” plans to go, along with the scheduled date and time of the visit. In this disclosure, for example, the user sets the place the user plans to go, along with the scheduled date and time, by operating the user terminal. The user terminal sends configuration information indicating the set content, along with information identifying the user terminal that sent this configuration information, to the management server 20. When the transmission / reception unit 201 of the management server 20 receives the configuration information, it writes the content identified from the received configuration information to the “scheduled location” associated with the “user” who owns the user terminal that sent this configuration information.

[0071] The "mode" indicates the mode set by the user. In this disclosure, when the management server 20 identifies the type of source from which the component has been measured by the sensor 10, it notifies the user terminal to which the mode to which the identified type belongs has been set of the detection of the source. In this disclosure, for example, the user terminal sends mode information indicating the set mode to the management server 20, along with information identifying the user terminal that sent this mode information. When the transmitting / receiving unit 201 of the management server 20 receives the mode information, it writes the mode identified from the received mode information to the "mode" associated with the "user" who owns the user terminal that sent this mode information. Furthermore, the "mode" is not limited to being set solely based on the source type; it may also be set based on the source type, area, time, user attributes, or a combination of these. Modes set for users will be described in detail later.

[0072] The "domain" indicates the domain to which the "installation location" of the sensing means shown in the sensing means management table (see Figure 4) belongs, and is determined in relation to the "user's" "place of residence". For example, the "domain" for "user A" is shown as "1:A, 2:B, 3:C...". This means that sensor 10 with "No." "1" in the sensing means management table belongs to the "domain" of "A" in relation to "user A", sensor 10 with "No." "2" in the sensing means management table belongs to the "domain" of "B" in relation to "user A", and sensor 10 with "No. "3" in the sensing means management table belongs to the "domain" of "C" in relation to "user A". Alternatively, for example, "B" in "domain" may be closer to the "user's" "place of residence" than "C" in "domain", and "A" in "domain" may be closer to the "user's" "place of residence" than "B" in "domain". Furthermore, the "area" may be defined in relation to the "user's" "current location" as the area to which the "installation location" of the sensing means shown in the sensing means management table belongs. Furthermore, the "area" may be determined by the management server 20, or it may be determined based on settings made by the administrator or user.

[0073] The “Registered Individual” shows information about a source that has been pre-registered as an individual associated with the “User.” More specifically, the “Registered Individual” shows a graph showing the measured values ​​per unit time when a measuring means such as the sensor 10 measures the components generated based on the pre-registered source. In this disclosure, for example, the user measures the components generated based on the registered source using a measuring means such as the sensor 10. The measuring means transmits result information showing the measurement results, along with information identifying the user who used the measuring means, to the management server 20. When the result information is received by the transmission / reception unit 201 of the management server 20, the graph generation unit 204 generates a graph based on the received result information and writes the generated graph to the “Registered Individual” associated with the “User” who is the source of the result information. However, the information shown in the “Registered Individual” may be result information instead of a graph.

[0074] In this disclosure, for example, a user may be registered as a user of the support system 1 by operating a user terminal. The user terminal transmits registration information indicating the registered content, along with information identifying the user terminal that sent the registration information, to the management server 20. When the transmission / reception unit 201 of the management server 20 receives the registration information, it writes the content identified from the received registration information to the "user," "attributes," "management area," and "place of residence" associated with the "user" who owns the user terminal that sent the registration information. The transmission / reception unit 201 also writes an "area" identified from the relationship between the "area" and "place of residence" associated with the "user." Note that the configuration and items of the user management table are examples only and are not limited to the example shown.

[0075] Next, we will explain the graphs generated by the graph generation unit 204. Figure 11 shows an example of a graph generated by the graph generation unit 204. The following describes a case where sensor 10 is a sensor whose resistance value changes depending on the measured component, such as the Bosch BME688. Note that the following description of sensor 10 is an example, and the same applies to cases where a physical quantity other than resistance is used, as long as the measured value of sensor 10 changes over time. For example, sensor 10 may have impedance, voltage, or current that changes depending on the measured component. Sensor 10 transmits information indicating the resistance value of sensor 10 for each unit of time to the management server 20 as result information. Furthermore, in the following, we will assume that sensor 10 has transmitted result information regarding the measurement of components generated from the feces of one bear to the management server 20.

[0076] When the result information transmitted from the sensor 10 is acquired by the transmitting / receiving unit 201, the graph generation unit 204 generates a linear graph as shown in Figure 11(A) based on the acquired result information. In the graph shown in Figure 11(A), the horizontal axis represents time, and the vertical axis represents the resistance value of the sensor 10. Time point t1 is the timing when the sensor 10 begins measuring components generated from bear feces, which are components generated from a source outdoors. In the illustrated example, the resistance value of the sensor 10 changes in a sigmoid curve shape from time point t1.

[0077] Next, let's assume that sensor 10 performs a measurement at the same location as the measurement result shown in Figure 11(A), but when no bear droppings are present, and transmits result information showing the measurement result to the management server 20. When the graph generation unit 204 receives the result information transmitted from sensor 10 to the transmission / reception unit 201, it generates the graph shown in Figure 11(B) based on the acquired result information. In the illustrated example, the resistance value of sensor 10 does not change significantly over time. On the other hand, the resistance value of sensor 10 remains greater than 0 over time. This is because, even if bear droppings are not present in the environment where components are measured by sensor 10, other components that are recognized by humans as odors are present, and these other components are measured by sensor 10. Examples of other components include components generated from soil and plants outdoors. Examples of other components include components generated from facilities indoors. In addition, although there is no significant change in the resistance value of sensor 10 over time in the illustrated example, the resistance value may change over time depending on the environment at the time of measurement of sensor 10.

[0078] Therefore, when the graph generation unit 204 designates the graph shown in Figure 11(A) as the target graph, it may subtract the resistance value shown in Figure 11(B) from the resistance value shown in Figure 11(A). As a result of this subtraction, as shown in Figure 11(C), the resistance value of the target graph changes from the value shown by the dashed line D to the value shown by the solid line L. In this case, in the example of Figure 11(A), other components among the components measured by the sensor 10 that are different from the components generated from bear feces are removed as noise appropriate to the environment, and this noise is prevented from affecting the identification of the source. Furthermore, the resistance value to be subtracted from the resistance value of the specific target graph may be the resistance value at a point in time when the component generated from the specific target source identified by the source identification unit 206 has not been measured by the sensor 10. Also, the resistance value to be subtracted may be the average value or median of the resistance values ​​when the component generated from the specific target source identified by the source identification unit 206 has not been measured by the sensor 10. Furthermore, the resistance value to be subtracted may be the resistance value shown in a specific "result information" or "graph" in the results management table (see Figure 8) for a "sensor" that measured a component generated from a specific target source, where no information has been entered in the "type" field. An example of a resistance value shown in a specific "result information" or "graph" is the "result information" or "graph" showing the lowest resistance value on any given day when sensor 10 measured a component generated from a specific target source. Furthermore, the process of removing noise from the resistance values ​​of a specific target graph is not limited to subtracting resistance values, but may also be achieved through normalization, ratio calculation, filtering, or a combination thereof.

[0079] Furthermore, the correction process for specific target graphs described above is not limited to processing based on predetermined rules, but may also be performed based on the results of machine learning. For example, the management server 20 acquires result information or graphs (see Figure 11(B)) as training data when components generated based on a specific source identified by the source identification unit 206 are not measured by the sensor 10. This training data includes information showing the time change of the sensor 10's measured values ​​due to environmental components. The management server 20 uses the training data to generate a learning model for estimating the influence of environmental components included in the sensor 10's measured values. This learning model may be, for example, a regression model, a neural network, a time series model, or a model combining these. The management server 20 then provides the measured values ​​shown in the specific target graph as input to a trained model, causing it to output an estimated value corresponding to the influence of environmentally derived components included in the measured values. Based on this estimated value, the management server 20 may correct the measured values ​​in the specific target graph and generate a corrected graph in which changes caused by components originating from the source are emphasized. This correction process is not limited to subtracting the measured values, but may also be performed by normalization, ratio calculation, filtering, or a combination thereof. The corrected graph may also be used by the source identification unit 206 to identify the type or individual source.

[0080] Furthermore, in this disclosure, for example, the length of the measurement period of the sensor 10 required for the source identification unit 206 to identify the type of source may be the period from time t1 to time t2 as shown in Figure 11(C). Also, for example, the length of the measurement period of the sensor 10 required for the source identification unit 206 to identify an individual source may be the period from time t1 to time t3, which is later than time t2. In addition, the source identification unit 206 may require the results of longer measurement periods of the sensor 10 when identifying an individual source than when identifying the type of source source. This is because identifying an individual source may require higher precision in determining the degree of similarity between the identified target graph and the comparison target graph by the comparison unit 205 than identifying the type of source source. Furthermore, the measurement time shown as a result for each piece of result information may be shorter than the period from time t1 to time t2, longer than the period from time t1 to time t2 and shorter than the period from time t1 to time t3, or longer than the period from time t1 to time t3.

[0081] Next, we will describe an example in which the management server 20 identifies the type of source. Figure 12 is a diagram illustrating an example of the concept by which the management server 20 identifies the type of source. Figure 12 shows the graph represented as the solid line L in Figure 11(C) as the specific target graph. The comparison unit 205 compares this specific target graph with each "graph" shown in the type management table (see Figure 5) as the comparison target graph. For example, the comparison unit 205 may compare the shape of the rise of the graph, the height of the peak value, the steady value, the overall shape, etc., between the specific target graph and the comparison target graph. The comparison unit 205 may also perform the comparison based on the feature quantities extracted from the specific target graph and the comparison target graph. Furthermore, in order to detect components with high accuracy, the measurement means such as BME688 is heated in stages, and measurements are taken at each heating temperature. In this case, a specific target graph and a comparison target graph are generated for each heating temperature. Therefore, the specific target graph and the comparison target graph may be provided as graphs showing the measured values ​​for each heating temperature of the measurement means. The comparison unit 205 may then compare the specific target graph and the comparison target graph for each heating temperature. Furthermore, the comparison unit 205 may integrate the comparison results for each heating temperature and calculate a single degree of agreement.

[0082] In the illustrated example, comparison graphs are shown for human, apple, and bear species. For example, the comparison graph for human species shows a graph generated based on result information showing the components contained in the breath of a 20-year-old male, measured by sensor 10 at a distance of 2m from this human. Another example shows a comparison graph for human species showing a graph generated based on result information showing the components generated from the sweat of a 20-year-old male, measured by sensor 10 at a distance of 2m from this human. Furthermore, the comparison graph for apple species shows a graph generated based on result information showing the components generated from an unripe apple, measured by sensor 10. Furthermore, the comparison graph for bears shows a graph generated based on result information indicating that components contained in the breath of a 3-year-old male bear were measured by sensor 10 located 2m away from the bear. Similarly, the comparison graph for bears shows a graph generated based on result information indicating that components contained in the feces of a 3-year-old male bear were measured by sensor 10 located 2m away from the bear. Thus, comparison graphs for each comparison target species may be provided for each attribute and measurement condition of the comparison target species.

[0083] In this example, for instance, the comparison unit 205 extracts a comparison graph generated based on result information showing the measurement results of components originating from the feces of a 3-year-old male bear at a sensor 10 located 2m away from the feces, selecting the one with the highest degree of agreement with the specified target graph. The comparison unit 205 then transmits the extracted comparison graph to the source identification unit 206, associating it with the comparison information. The source identification unit 206 then identifies the type of source of the specified target as a bear if the acquired comparison information satisfies the type identification conditions. In this case, the related identification unit 207 may also use the attributes of the comparison target type, the source of the components, and the measurement status identified from the comparison graph extracted by the comparison unit 205 as the attributes of the source of the specified target and the measurement status related to the specified target graph. In this example, the related identification unit 207 may identify the age and sex of the source of the specified target as a 3-year-old male. The related identification unit 207 may also identify the source of the component that is the subject of measurement and is shown as a result in the specified target graph as feces. Furthermore, the related identification unit 207 may identify the distance from the source to the sensor 10 as 2m in the measurement shown as a result in the identified target graph.

[0084] Furthermore, in this disclosure, the comparison between the specified target graph and the comparison target graph, and the identification of the type of source, performed by the comparison unit 205 and the source identification unit 206 may be implemented based on the results of machine learning. For example, the management server 20 may use the comparison graphs shown in the type management table (see Figure 5) as training data to generate a learning model that takes as input feature quantities representing the time change of measured values ​​obtained by a measurement means that measures components generated based on the source, for each type of source, and outputs the type of source. Any model capable of performing classification based on the time change of measured values ​​may be used as this learning model, such as a neural network, support vector machine, decision tree, or a model combining these. The comparison unit 205 extracts features to be used as input to the trained model from the specific target graph generated based on the result information showing the measurement results from the sensor 10, and inputs the extracted features into the trained model. The source identification unit 206 may then identify the type with the highest value as the type of source of the target, based on the probability, likelihood, or score for each type of source obtained as the output of the trained model. If the output of the trained model does not meet predetermined criteria, the source identification unit 206 may determine that the type of source is unspecified, or identify multiple types as candidates. In this case, the condition for type identification is that the output of the trained model meets predetermined criteria necessary for identifying the type of source. Thus, the comparison of a specific target graph with a comparison target graph, and the identification of the source type based on the comparison target graph with the highest degree of agreement, in this disclosure may be implemented based on the output of a model obtained by machine learning.

[0085] Next, we will describe an example in which the management server 20 identifies the source of the problem. Figure 13 is a diagram illustrating an example of the concept of the management server 20 identifying the source individual. Figure 13 shows the graph represented as the solid line L in Figure 11(C) as the specific target graph. The comparison unit 205 may compare this specific target graph with each "graph" shown in the results management table (see Figure 8) as the comparison target graph. Alternatively, if the type of source of the specific target has already been identified, the comparison unit 205 may compare each "graph" from the "graphs" shown in the results management table that is associated with the same "type" as the source of the specific target as the comparison target graph. The comparison method used by the comparison unit 205 may be the same as the comparison method described above for identifying the type of source.

[0086] In this example, for instance, the comparison unit 205 may extract the comparison target graph related to the bear whose "No." is "2" in the individual management table (see Figure 7) as having the highest degree of agreement with the specific target graph. The comparison unit 205 then associates the extracted comparison target graph with the comparison information and transmits it to the source identification unit 206.

[0087] If the acquired comparison information satisfies the individual identification conditions, the source identification unit 206 identifies the individual at the source of the identified target as, for example, a bear whose "No." is "2". In this case, the source identification unit 206 increments the "number of detections" associated with "No." "2" in the individual management table by one. In this case, the related identification unit 207 may also use the attributes of the comparison target type, the source of the components, and the measurement status of the graph of the identified target as the attributes of the source of the identified target and the measurement status related to the graph of the identified target, which are identified from the comparison target graph extracted by the comparison unit 205. Furthermore, if the acquired comparison information does not meet the individual identification conditions, the source identification unit 206 may identify the individual at the source of the identified threat as a new individual. In this case, the source identification unit 206 adds a new "No." to the individual management table and writes "1" to the "Number of Detections" associated with the added "No.".

[0088] Furthermore, in this disclosure, if there are multiple comparison graphs for the same individual with different distances from the source of the component to the sensor 10, the comparison unit 205 may compare each of the multiple comparison graphs generated for each of these distances with the specific target graph. On the other hand, for the same individual, there may be only one comparison graph where the distance from the source of the component to the sensor 10 is a single distance. In this case, the comparison unit 205 may assume the distance from the source to the sensor 10 in the measurement related to the specific target graph. The comparison unit 205 may then correct the resistance value in the comparison graph according to the assumed distance and compare the corrected comparison graph with the specific target graph. Such correction may be performed by considering, for example, the degree of diffusion of the component according to the distance, the degree of attenuation, or the change in the amount of component reaching the sensor 10.

[0089] Furthermore, in this disclosure, the comparison between the specified target graph and the comparison target graph, and the identification of the source individual, performed by the comparison unit 205 and the source identification unit 206 may be implemented based on the results of machine learning. For example, the management server 20 may use comparison graphs related to sources where individuals have already been identified, stored in the result management table (see Figure 8) and individual management table (see Figure 7), as training data to generate a learning model that takes features representing the time change of measured values ​​by the measurement means as input and outputs identification information to identify individuals. Any model capable of performing classification based on the time change of measured values ​​may be used as this learning model, such as a neural network, support vector machine, decision tree, or a model combining these. Furthermore, the input to the learning model may not only be the time change of measured values, but also features corresponding to the distance from the source of the component to the measurement means, the period from when the component is generated from the source until it is measured by the measurement means, the source of the component, etc. The comparison unit 205 extracts features from the target graph to be used as input to the trained model and inputs the extracted features into the trained model. The source identification unit 206 may then identify the individual with the highest value as the source of the target, based on the probability, likelihood, or score of belonging to an existing individual obtained as the output of the trained model. If the output of the trained model does not meet predetermined criteria, the source identification unit 206 may identify the source of the target as a new individual. If the output of the trained model does not meet predetermined criteria, the source identification unit 206 may determine that the source of the target is unidentified. In this case, the condition for individual identification is that the output of the trained model meets predetermined criteria necessary for identifying the source individual.

[0090] Next, we will explain the modes that are set on the user terminal. In this disclosure, a mode is a setting unit that logically groups a set of conditions for determining whether or not to notify the user based on the detection results of the source. Specifically, the mode is used by the management server 20 to decide whether or not to notify the user, or to switch the notification method, depending on the content of the source identified based on the measurement results of the sensor 10, or the user's status as described later. The management server 20 may perform different notification controls for each user, even if the same source is detected, by referring to the conditions associated with the mode set for the user.

[0091] Figure 14(A) shows an example of the mode setting screen 500. The mode setting screen 500 is a screen for setting the mode for which, for example, a source detected by the management server 20 will be subject to notification. In this disclosure, the user terminal may display the mode setting screen 500 in response to user input. The mode setting screen 500 shows a selection prompt image 501 and a mode acceptance image 502. Selection prompt image 501 is an image that prompts the user to select a mode. In the illustrated example, selection prompt image 501 shows the text "Please select the mode you wish to be notified about."

[0092] The mode reception image 502 is an image that accepts the selection of a mode for which the management server 20 should be notified, based on which source is detected. In the illustrated example, the mode reception images 502 for "Home Mode," "Absent Mode," "Animal Mode," "Plant Mode," and "Object Mode" are shown. The modes shown as mode reception images 502 in Figure 14(A) are just examples, and other modes may be provided.

[0093] The mode selection image 502 for "Home Mode" accepts the selection of Home Mode. Home Mode is a mode in which, when the management server 20 detects the presence of a specific source in a house where residents are present, the presence of this source will be notified. The mode reception image 502 for "Absence Mode" accepts the selection of Absence Mode. Absence Mode is a mode in which, when the management server 20 detects the presence of a specific source in a house where the residents are absent, the presence of this source will be notified. The mode selection image 502 for "Animal Mode" accepts the selection of Animal Mode. Animal Mode is a mode in which, when the management server 20 detects the presence of a specific animal as the source of an issue, the presence of that specific animal will be subject to notification. The "Plant Mode" mode acceptance image 502 accepts the selection of Plant Mode. Plant Mode is a mode in which, when the management server 20 detects the presence of a specific plant as the source, this specific plant is made the target of notification. The "Object Mode" mode acceptance image 502 accepts the selection of the Object Mode. The Object Mode is a mode in which, when the management server 20 detects the presence of a specific object as a source, the existence of this specific object is made subject to notification.

[0094] Here, for example, suppose the user selects the "Animal Mode" mode selection image 502 by operating the user terminal. In this case, the user terminal may display the mode setting screen 500 shown in Figure 14(B). The mode setting screen 500 shown in Figure 14(B) displays the mode selection images 502 related to the modes categorized within the "Animal Mode" selected by the user. In the illustrated example, the mode selection images 502 for "Rare Animal Mode," "Insect Mode," "Pest Bird Mode," and "Pest Animal Mode" are shown. The modes shown as mode selection images 502 in Figure 14(B) are just examples, and other modes may be provided.

[0095] The mode selection image 502 for "Rare Animal Mode" accepts the selection of Rare Animal Mode. Rare Animal Mode is a mode in which, if the management server 20 detects the existence of a source designated as a rare animal, the existence of this source may be included in the notification. The mode reception image 502 for "Pest Mode" accepts the selection of Pest Mode. Pest Mode is a mode in which, if the management server 20 detects the presence of a source designated as a pest, the existence of this source may be included in the notification. The mode reception image 502 for "Pest Bird Mode" accepts the selection of Pest Bird Mode. Pest Bird Mode is a mode in which, if the management server 20 detects the presence of a source designated as a pest bird, the existence of this source may be included in the notification. The mode reception image 502 for "Pest Mode" accepts the selection of Pest Mode. Pest Mode is a mode in which, if the management server 20 detects the presence of a source designated as a pest, the existence of this source may be included in the notification.

[0096] Here, for example, suppose a user selects the "Rare Animal Mode" mode reception image 502 by operating the user terminal. In this case, the user terminal sends mode information indicating the selected mode, along with information identifying the user terminal that sent this mode information, to the management server 20. When the transmission / reception unit 201 of the management server 20 receives the mode information, it writes "Rare Animal," which is the mode identified from the received mode information, to the "Mode" associated with the "User," who is the owner of the user terminal that sent this mode information.

[0097] Figures 15 and 16 are flowcharts showing the flow of the fixed notification process. The fixed notification process is the process by which the management server 20 notifies the user of information regarding the source from which a component was measured by the fixed sensor 11. In this disclosure, for example, when result information transmitted from the fixed sensor 11 is received by the transmission / reception unit 201 of the management server 20, the fixed notification process is started. In this disclosure, the fixed notification process is performed for each fixed sensor 11. The fixed sensor 11 that is the target of the fixed notification process that is currently being executed, in other words, the fixed sensor 11 that transmitted the result information that triggered the start of the fixed notification process, may be referred to as the target fixed sensor 11 below. In a broader sense, the target fixed sensor 11 can also be considered as the target sensor 10. The graph generation unit 204 of the management server 20 generates a specific target graph based on the result information received by the transmitting / receiving unit 201 (step (hereinafter sometimes referred to as "S") 101). As described above, in continuous measurement, the sensor 10 transmits result information related to each new measurement to the management server 20 each time a new measurement is taken. Therefore, the graph generation unit 204 may generate the specific target graph not only using the latest result information received by the transmitting / receiving unit 201, but also including past result information that is continuous with this latest result information.

[0098] The graph generation unit 204 removes noise from the target graph using the method shown in Figure 11(C) (S102). The comparison unit 205 determines whether the source of the component measured by the target fixed sensor 11 has been identified by the source identification unit 206 (S103). The comparison unit 205 refers to the result management table (see Figure 8). The comparison unit 205 may then make the determination in step 103 based on whether a numerical value is shown for the "individual" associated with the "result information" that triggered the start of the previous fixed notification process among the "result information" related to the target fixed sensor 11. The previous fixed notification process refers to the fixed notification process that was immediately executed for the target fixed sensor 11. The result information referenced in the previous fixed notification process may be shown in the "result" of the sensing means management table (see Figure 4) and the "result information" of the result management table (see Figure 8).

[0099] If the individual has already been identified (Yes in S103), the comparison unit 205 determines the graph generated by the graph generation unit 204 based on the result information that triggered the start of the previous fixed notification process as the comparison target graph, and generates comparison information showing the result of the comparison between the determined comparison target graph and the identified target graph. The source identification unit 206 then determines whether the generated comparison information satisfies the individual identification conditions (S104). If the comparison information does not satisfy the individual identification conditions (No in S104), the source identification unit 206 determines that the component generated from the individual identified in the previously executed fixed notification process for the target fixed sensor 11 is not measured by the target fixed sensor 11. In this case, the source identification unit 206 may determine that the individual identified in the previously executed fixed notification process for the target fixed sensor 11 is absent in the measurement area of ​​the target fixed sensor 11 (S105). In other words, the source identification unit 206 may determine that the component generated from the previously identified individual is not measured by the target fixed sensor 11 in the measurement area of ​​the target fixed sensor 11.

[0100] If the source of the component measured by the target fixed sensor 11 has not been identified (No in S103), the comparison unit 205 determines whether the source of the component measured by the target fixed sensor 11 has been identified by the source identification unit 206 (S106). The comparison unit 205 refers to the result management table (see Figure 8). The comparison unit 205 may then make the determination in step 106, for example, by checking whether the source type is indicated in the "type" associated with the "result information" related to the target fixed sensor 11 that triggered the start of the previous fixed notification process. If the type of source of the component measured by the target fixed sensor 11 has not been identified (No in S106), the process proceeds to the next step. The comparison unit 205 compares the "graphs" for each type shown in the type management table (see Figure 5) with the identified target graph as comparison graphs (S107). The comparison unit 205 then extracts the graph with the highest degree of agreement with the identified target graph from among the comparison graphs, associates the extracted comparison graph with comparison information which is information indicating the comparison result, and transmits it to the source identification unit 206.

[0101] The source identification unit 206 determines whether the received comparison information satisfies the type identification conditions (S108). If the comparison information satisfies the type identification conditions (Yes in S108), the source identification unit 206 identifies the type of source of the identified target (S109). The source identification unit 206 may, for example, identify the type of comparison target related to the comparison target graph associated with the comparison information that satisfies the type identification conditions as the type of source of the identified target. Furthermore, as mentioned above, steps 107 and 108 may be performed based on the results of machine learning.

[0102] The related identification unit 207 identifies the type of source of the component that is the target of measurement for the specified target graph (S110). The related identification unit 207 may, for example, identify the type of source of the component that is the target of measurement for the comparison target graph extracted by the comparison unit 205 as a result of the comparison in step 107 as the type of source of the component that is the target of measurement for the specified target graph. In this case, the type of source identified is the "source" associated with the "graph" that corresponds to the comparison target graph extracted by the comparison in step 107, among the "graphs" shown in the type management table (see Figure 5).

[0103] Furthermore, the related identification unit 207 may perform the identification of the type of source of the component in step 110 based on the results of machine learning. The related identification unit 207 inputs, for example, the identified target graph, the estimated type of the identified target graph, and information indicating the measurement status related to the identified target graph into the trained model. Examples of measurement status include the distance from the source of the component to the measurement means such as the sensor 10, the measurement environment, the heating temperature stage at the sensor 10, and the wind direction and wind speed at the location where the measurement was performed. The trained model may also be a classifier corresponding to the type of source, or an estimator that outputs the likelihood for each type of source. The related identification unit 207 may obtain the type of source, the confidence level for each type of source, or a candidate for the type of source as output of the trained model, and identify the type of source based on this output. Furthermore, the related identification unit 207 may identify the type of origin solely from the output of the trained model without using the comparison target graph stored in the type management table, or it may use the output of the trained model to reinforce the identification result obtained by comparison.

[0104] The related identification unit 207 identifies the attributes of the source of the specified target (S111). The related identification unit 207 may, for example, identify the attributes of the source of the component that is the subject of measurement related to the comparison target graph extracted by the comparison unit 205 as a result of the comparison in step 107 as the attributes of the source of the specified target. In this case, the attributes to be identified are "gender" and "age (years)" associated with the "graph" that corresponds to the comparison target graph extracted by the comparison in step 107 from among the "graphs" shown in the type management table (see Figure 5).

[0105] Furthermore, the related identification unit 207 may perform the identification of the source attributes in step 111 based on the results of machine learning. The related identification unit 207 inputs, for example, the identified target graph or its features, and information indicating the type identified in step 109, into the trained model. The trained model may be a classifier or regressor for each attribute. The trained model may also output classification results such as male or female for gender, or an estimated value or a range category such as age for age. The related identification unit 207 may obtain attribute values, confidence levels of attribute values, or attribute candidates as output of the trained model, and identify attributes based on said output.

[0106] The related identification unit 207 determines whether the source of the identified target has been identified by the source identification unit 206 as an animal (S112). If the source of the specified object is identified as an animal (Yes in S112), the related identification unit 207 identifies the size of the source of the specified object (S113). Examples of the size of the source include the height of the source and the weight of the source. The related identification unit 207 may, for example, identify the size of the source of the component that is the subject of measurement related to the comparison target graph extracted by the comparison unit 205 as a result of the comparison in step 107 as the size of the source of the specified object. In this case, the sizes identified are the "height (m)" and "weight (kg)" associated with the "graph" corresponding to the comparison target graph extracted by the comparison in step 107 from the "graphs" shown in the type management table (see Figure 5).

[0107] Furthermore, the related identification unit 207 may perform the identification of the size of the source in step 113 based on the results of machine learning. The related identification unit 207 inputs, for example, the specified target graph or its features, the distance from the source of the component to the measurement means such as the sensor 10, the measurement environment, and the type and / or attributes of the source to the trained model. The trained model may be a regression model or a classification model that outputs stepped divisions of size. The related identification unit 207 may obtain estimated height and / or weight, estimation range, division, confidence level, etc., as output of the trained model, and identify the size based on said output.

[0108] If the source of the specified target is identified as a species different from an animal (No in S112), or after step 113, the process proceeds to the next step. The related identification unit 207 identifies the time when the component that is the subject of measurement related to the specified target graph originated from the source (S114). For example, the related identification unit 207 extracts the "period (seconds)" associated with the "graph" that corresponds to the comparison target graph extracted by the comparison in step 107 from among the "graphs" shown in the species management table (see Figure 5). The related identification unit 207 may then identify the extracted period as the period from when the component that is the subject of measurement related to the specified target graph originated from the source. Furthermore, the related identification unit 207 may identify the time when the component that is the subject of measurement related to the specified target graph originated from the source, by the specified period backward from the measurement time related to the specified target graph.

[0109] Furthermore, the related identification unit 207 may perform the identification of the timing of component occurrence in step 114 based on the results of machine learning. The related identification unit 207 inputs, for example, the time change of the resistance value shown in the identified target graph, the transition from the rise of the resistance value to a steady state, the decay shape of the resistance value peak, the distance from the source to the measurement means such as the sensor 10, wind direction and wind speed, etc., into the trained model. The trained model may be a regressor that estimates the time elapsed since the component was generated from the source, or an estimator that outputs an elapsed time distribution. Examples of elapsed time distributions include probability distributions and likelihood distributions. The related identification unit 207 may then obtain, as output of the trained model, an estimated value or estimated range of the period from when the component was generated from the source until it was measured by the measurement means, and at least one of the confidence level of the estimate, and identify the time of occurrence by working backward from the measurement date and time through the estimated period.

[0110] The related identification unit 207 identifies the range of movement of the source of the identified target up to the present (S115). For example, the memory unit 202 may store information indicating the characteristics of the source's behavior for each type of source. Examples of information indicating the characteristics of the source's behavior include the average movement speed of the source. Then, the related identification unit 207 may, for example, identify the range of movement of the source of the identified target from the time identified in step 114 as the time when the component that is the target of measurement related to the identified target graph occurred up to the present, according to the information stored in the memory unit 202.

[0111] Furthermore, the related identification unit 207 may perform the identification of the range of the source's activity in step 115 based on the results of machine learning. The related identification unit 207 inputs, for example, the estimated time when the component was generated from the source, the location where the component was measured by a measuring means such as the sensor 10, the detection history at that location, wind direction and speed, geographic information, etc., into the trained model. The trained model may be a model that estimates the area that can be reached by the movement of the source, the speed of movement, or the probability distribution of existence over time. Examples of models include time series models, state-space models, and probabilistic estimators. The related identification unit 207 may then obtain information indicating an area representing the range of activity and at least one of the probability of existence or score within a specific area as output from the trained model, and identify the range of activity up to the present based on this output.

[0112] Furthermore, if the type of source of the component being measured by the target fixed sensor 11 has already been identified (Yes in S106), or if the process proceeds to the next step after step 115, the comparison unit 205 determines whether the time during which the resistance value of the target fixed sensor 11 is deemed to have changed significantly relative to the noise, within the measurement time shown in the target graph, satisfies the required time condition (S116). The required time condition is a condition used by the source identification unit 206 to determine whether it is possible to identify the individual source of the target using the target graph. In this disclosure, for example, the required time condition may be defined as the time during which the resistance value of the target fixed sensor 11 is deemed to have changed significantly relative to the noise, within the measurement time shown in the target graph, being equal to or greater than a predetermined time. Note that "significantly changed" includes the resistance value of the target fixed sensor 11 being equal to or greater than a predetermined threshold. The predetermined time is defined as the measurement period of the sensor 10 necessary for identifying the individual source. The predetermined time is, for example, the time from time point t1 to time point t3 as shown in Figure 11(C).

[0113] If the required time condition is met (Yes in S116), the process proceeds to the next step. The comparison unit 205 compares each of the graphs shown in the results management table (see Figure 8) that are associated with the same type as the type identified for the source of the specific target as a comparison graph (S117). This compares the comparison graph and the specific target graph for each individual of the same type as the source of the specific target. The comparison unit 205 then extracts the graph with the highest degree of agreement with the specific target graph from among the comparison graphs, associates the extracted comparison graph with comparison information which is information indicating the results of the comparison, and transmits it to the source identification unit 206. The source identification unit 206 identifies the individual that is the source of the target (S118). For example, if the comparison information related to the comparison target graph extracted by the comparison in step 117 satisfies the individual identification conditions, the source identification unit 206 identifies the comparison target individual related to the comparison target graph associated with this comparison information as the individual that is the source of the target. Alternatively, if the comparison information related to the comparison target graph extracted by the comparison in step 117 does not satisfy the individual identification conditions, the source identification unit 206 may identify the source of the target as a new individual that has not been identified before. Furthermore, as mentioned above, steps 117 and 118 may be performed based on the results of machine learning.

[0114] The related identification unit 207 identifies the details of the individual identified in step 118 regarding the measurement related to the specified target graph (S119). The related identification unit 207 refers to the "source," "period (seconds)," and "distance (m)" associated with the "graph" extracted by the comparison in step 117 from the results management table (see Figure 8). The related identification unit 207 may then, for example, identify the type of source of the component that is the target of measurement related to the specified target graph, and the time when the component that is the target of measurement related to the specified target graph originated from the source, depending on the information it has referenced. Furthermore, if the information of the identified individual is already shown in the individual management table (see Figure 7), the related identification unit 207 may identify the "sex," "age (years)," "height (m)," and "weight" already shown in the individual management table as the attributes and size of the source of the specified target. The related identification unit 207 may also identify the range of the current movement of the source of the specified target, depending on the information it has identified.

[0115] Furthermore, the related identification unit 207 may perform the identification of individual details in step 119 based on the results of machine learning. The related identification unit 207 inputs information such as the target graph, the individual identification result, the history shown in the result management table for the individual, the location of the measurement means such as the sensor 10 on which the measurement related to the target graph was performed, and the wind direction and wind speed in the measured environment into the trained model. The trained model may be a multi-task learning model that simultaneously outputs estimation targets such as the source of the component, the timing of the component's generation, and the attributes of the source, or separate trained models may be used for each estimation target. The related identification unit 207 may then obtain the value of the estimation target, the estimation range, the confidence level, or a candidate set as the output of the trained model, and identify the content related to the individual based on this output.

[0116] Furthermore, if the comparison information satisfies the individual identification condition in step 104 (Yes in S104), or after step 119, the process proceeds to the next step. The related identification unit 207 determines whether or not there is result information that satisfies the proximity condition (S120). The proximity condition is a condition used by the related identification unit 207 to determine whether or not other components were measured by the sensor 10 in the vicinity of the target fixed sensor 11. In this disclosure, for example, the proximity condition may be defined as the result information generated by a sensor 10 located within a predetermined distance range from the target fixed sensor 11 showing a resistance value in which a significant change with respect to noise was observed. Alternatively, for example, the proximity condition may be defined as the result information generated by a sensor 10 adjacent to the target fixed sensor 11 showing a resistance value in which a significant change with respect to noise was observed.

[0117] If result information that satisfies the proximity conditions exists (Yes in S120), the source identification unit 206 determines whether the component that is the subject of measurement related to the specified target graph and the component that is the subject of measurement related to the result information that satisfies the proximity conditions are the same individual (S121). The same individual condition is a condition used by the source identification unit 206 to determine whether the component that is the subject of measurement related to the specified target graph and the component that is the subject of measurement related to the result information that satisfies the proximity conditions are the same individual. In this disclosure, for example, the same individual condition may be that the difference between the measurement time related to the specified target graph and the measurement time related to the result information that satisfies the proximity conditions is within a predetermined period. The predetermined period may be any amount of time, for example, 1 minute. Also, for example, the same individual condition may be that the camera 50 captured that the component that is the subject of measurement related to the specified target graph and the component that is the subject of measurement related to the result information that satisfies the proximity conditions originated from the same individual. Furthermore, for example, the relationship between the resistance value shown in the specific target graph and the resistance value shown in the result information that satisfies the surrounding conditions may be predetermined, even if it is under the same individual conditions. Examples of predetermined relationships include relationships identified from the resistance values ​​shown as measurement results by sensor 10 for components generated from different sources of the same individual. If the condition of being the same individual is met (Yes in S121), the source identification unit 206 identifies that the source of the identified target and the source of the component that is the target of measurement related to the result information satisfying the proximity condition are the same individual (S122).

[0118] The related identification unit 207 may perform the determination of the proximity condition in step 120 based on the results of machine learning. For example, the related identification unit 207 may use a trained model that takes information showing the results of measurements of the target graph of the target fixed sensor 11 and the nearby sensors 10 as input and outputs the probability that the measurements of each component are due to the same event. Information showing the measurement results can include result information, graphs generated based on the result information, and features extracted from the graph. The related identification unit 207 may then determine that the proximity condition is met if the output of the trained model is above a predetermined threshold. The output of the trained model can include probabilities, scores, etc. Furthermore, the source identification unit 206 may perform the determination of the same individual condition in step 121 based on the results of machine learning. For example, the source identification unit 206 may use a trained model that takes the identified target graph and the graph relating to the result information that satisfies the proximity condition or the features of the said graph as input to determine whether the two originate from the same individual. Examples of trained models include similarity estimators, matchers, and binary classifiers. The trained model may also output a matching result such as the probability of them being the same individual, a score for being the same individual, or truth or falsity. The source identification unit 206 may then determine whether the same individual condition is met based on the output of the trained model.

[0119] If the proximity condition is not met (No in S120), if the same individual condition is not met (No in S121), or after step 122, the process proceeds to the next step. The related identification unit 207 determines whether the source of the specified target satisfies the multiple detection conditions (S123). The multiple detection conditions are conditions used by the related identification unit 207 to determine whether the source of the specified target has been detected at multiple locations in a short period of time. In this disclosure, for example, the multiple detection conditions may be defined as the fact that a component generated from a source identified as the same individual as the source of the specified target was measured at a sensor 10 at a different location from the measurement location related to the specified target graph within a predetermined period from the measurement time related to the specified target graph. The predetermined period may be any time, but for example, it is 6 hours. The related identification unit 207 performs the processing in step 123 by referring to the result management table. Furthermore, if in step 122 the source of the specified target and the source of the component that is the subject of measurement related to the result information satisfying the surrounding conditions are identified as the same individual, then a positive result is obtained in step 123 (Yes in S123).

[0120] If the source of the specified target satisfies multiple detection conditions (Yes in S123), the related identification unit 207 may specify the movement pattern of the source of the specified target (S124). Examples of movement patterns include the direction of movement and the range of movement. For example, the related identification unit 207 may specify a range including the position of the fixed sensor 11 of the target and the position of the sensor 10 where multiple detection conditions are satisfied as the range of movement of the source of the specified target. Alternatively, the related identification unit 207 may specify a direction from the position where components were measured at an earlier time to the position where components were measured at a later time, among the position of the fixed sensor 11 of the target and the position of the sensor 10 where multiple detection conditions are satisfied, as the direction of movement of the source of the specified target.

[0121] Furthermore, the related identification unit 207 may perform the determination of the multiple detection conditions in step 123 based on the results of machine learning. For example, the related identification unit 207 may use a trained model that takes the history shown in the results management table as input and outputs the probability that components measured at multiple locations in a short period of time are due to the movement of the same individual. The output of the trained model may include probabilities, scores, etc. The related identification unit 207 may then determine that the multiple detection conditions are met if the output of the trained model is above a predetermined threshold. Furthermore, the related identification unit 207 may perform the identification of the movement pattern in step 124 based on the results of machine learning. For example, the related identification unit 207 may use a trained model that takes as input information such as the measurement time, measurement location, and wind direction and speed in the measurement environment for multiple locations where components generated from the same individual are measured, and outputs a movement vector, reachable area, or probability distribution of future position. The related identification unit 207 may then identify the direction of movement and / or movement range based on the output of the trained model.

[0122] If, after step 105, the multiple detection conditions are not met (No in S123), or after step 124, the process proceeds to the next step. The management server 20 updates the contents of the individual management table (see Figure 7) and the result management table (see Figure 8) according to the results of each process in the ongoing fixed notification process. In addition, the counting unit 208 of the management server 20 counts the individuals, including the identified individuals, when individuals are identified in the ongoing fixed notification process, and updates the contents of the individual count management table (see Figure 9) according to the counting results (S125). Note that if no individuals are identified in the ongoing fixed notification process, the counting unit 208 does not need to count individuals or update the individual count management table. The management server 20 performs result output processing (S126). As will be described in detail later, the result output processing is the process by which the management server 20 outputs information regarding the measurement results from the sensor 10.

[0123] Figures 17 and 18 are flowcharts illustrating the flow of the result output processing (see S126 in Figure 16). The condition determination unit 209 of the management server 20 determines whether the type of source of the specified target has already been identified by the source identification unit 206 (S201). The processing in step 201 may be performed using the same method as in step 106 of the fixed notification processing (see Figure 15). If the type of source of the specified target has not been identified (No in S201), the target determination unit 211 determines that all users of the support system 1 are not to be notified of the measurement results from the target sensor 10 (S202). In this case, the information regarding the measurement results from the target sensor 10 does not need to be output to the user terminals of all users of the support system 1.

[0124] Furthermore, if the type of source of the specified target has been identified (Yes in S201), the condition determination unit 209 determines whether the source of the specified target is a mandatory individual (S203). A mandatory individual is an individual of a source that has been designated as a target for which it is essential to notify the user of the measurement results by the target sensor 10. In this disclosure, for example, a mandatory individual may be designated if the source of the specified target is a bear that has previously attacked a person. Alternatively, for example, a mandatory individual may be designated if the source of the specified target is a person who may have a significant impact on public safety. The condition determination unit 209 focuses on the "No." in the individual management table (see Figure 7) that shows the same number as the "Individual" related to the source of the specified target in the result management table (see Figure 8). The condition determination unit 209 may then perform the processing in step 203 based on the information shown in the "History" associated with the "No." that it focused on. Alternatively, identification information such as a flag may be shown for each individual in the individual management table, and whether or not it is a mandatory individual may be determined by this identification information. Identification information may be entered by an administrator through operations on the management server 20, or it may be entered into the management server 20 on an individual basis. If the individual at the source of the specified target has not been identified by the source identification unit 206, a negative result is obtained in step 203 (No in S203).

[0125] Furthermore, the management server 20 may determine whether the source of a specific target is an essential individual based on the results of machine learning. The management server 20 may use the history of previously detected source individuals as training data to generate a trained model that estimates whether or not an individual should be one that requires notification to the user. Examples of history include the frequency of past detections, the number of times notifications have been issued in the past, whether or not a dangerous event has occurred in the past, and the history of actions taken by the administrator. The trained model may also take features related to a specific source individual as input and output the probability that the individual is a mandatory individual, or a determination result indicating whether or not it is a mandatory individual. The condition determination unit 209 may then determine that the specific source individual is a mandatory individual if the output of the trained model is above a predetermined threshold, and obtain a positive result in step 203.

[0126] If the source of the specified target is an essential individual (Yes in S203), the target determination unit 211 determines that all users of the support system 1 will be notified of the measurement results from the target sensor 10 (S204). In this case, information regarding the measurement results from the target sensor 10 may also be output to the user terminals of all users of the support system 1. If the source of the specified target is not an essential individual (No in S203), the condition determination unit 209 determines one user of the support system 1 who has not been determined to be the target of determination in the currently running result output processing as the target of determination (S205). The user determined to be the target of determination in step 205 may be referred to as the target user below.

[0127] The condition determination unit 209 determines whether the source of the specified target satisfies the individual relationship conditions (S206). The individual relationship conditions are conditions defined regarding the relationship between the source of the specified target and the user being determined. The individual relationship conditions are used by the condition determination unit 209 to determine whether or not to notify the user being determined of the measurement results by the sensor 10 of the target. In this disclosure, for example, the individual relationship condition may be defined as the fact that the source of the specified target is a different individual from the "registered individual" associated with the "user" corresponding to the user being determined in the user management table (see Figure 10). Alternatively, for example, the individual relationship condition may be defined as the fact that the source of the specified target is a "registered individual" associated with the "user" corresponding to the user being determined in the user management table (see Figure 10). If the individual of the source of the specified target is not identified by the source identification unit 206, a negative result is obtained in step 206 (No in S206).

[0128] Furthermore, the individual relationship conditions may be determined from the relationship between the source of the specific target, the user being judged, and the mode set on the user terminal of the user being judged. For example, if the user being judged is set to home mode (see Figure 14(A)), the individual relationship condition may be defined as the source of the specific target being a "registered individual" associated with the "user" corresponding to the user being judged in the user management table. In this case, the "user" will be aware that the source of the specific target is a "registered individual" in home mode through notification of information to the "user" as described later. Also, for example, if the user being judged is set to absent mode (see Figure 14(A)), the individual relationship condition may be defined as the source of the specific target being a different individual from the "registered individual" associated with the "user" corresponding to the user being judged in the user management table. In this case, the "user" will be aware that the source of the specific target is a different individual from the "registered individual" in absent mode through notification of information to the "user" as described later.

[0129] Furthermore, the condition determination unit 209 may determine, based on the results of machine learning, whether the relationship between the source of the specific target and the user being determined satisfies the individual relationship conditions. The management server 20 may use past notification history, user-specific behavior history, information on "registered individuals" registered by users, user mode settings, and a history of user responses to previously notified sources as training data. The trained model may receive information on the individual source of a specific target, information on the user to be judged, and the mode set for the user to be judged as input, and output whether or not the user should be notified of the source, or a score indicating the degree of suitability for notification. The condition determination unit 209 may then determine whether or not the individual relationship condition is met based on the output of the trained model.

[0130] If the source of the specified target satisfies the individual relationship conditions (Yes in S206), the target determination unit 211 determines that the user to be determined will be the target of notification based on the measurement results from the target sensor 10 (S207). Furthermore, if the source of the specified target does not satisfy the individual relationship conditions (No in S206), the condition determination unit 209 determines whether the target sensor 10 satisfies the type area conditions (S208). The type area conditions are defined for the area to which the position of the target sensor 10, when it measures the component generated from the source of the specified target, belongs. The type area conditions are used by the condition determination unit 209 to determine whether it has a high priority to notify the user being judged of the measurement results by the target sensor 10. In this disclosure, for example, the type area condition may be defined as the area to which the position of the target sensor 10, when it measures the component generated from the source of the specified target, belongs being "A" or "B" as shown in the "Area" of the user management table (see Figure 10). The condition determination unit 209 performs the processing in step 208 based on the "Area" shown in the user management table as the relationship between the target sensor 10 and the user being judged.

[0131] If the target sensor 10 satisfies the type area conditions (Yes in S208), the condition determination unit 209 determines whether the location where the target sensor 10 measures the component generated based on the specific target source is within the notification recommendation area (S209). The notification recommendation area is a predetermined area where, if the sensor 10 detects a source, it is recommended to notify the user of this source. In this disclosure, for example, "A" shown in the "Area" of the user management table (see Figure 10) may be the notification recommendation area. The condition determination unit 209 performs the processing in step 209 based on the "Area" shown in the user management table as the relationship between the target sensor 10 and the user to be determined.

[0132] The condition determination unit 209 may also determine, based on the results of machine learning, whether the relationship between the position measured by the target sensor 10 and the user being determined satisfies the type domain conditions. The management server 20 may use as training data information the past measurement locations of components generated based on the source, past notification results regarding the source, the user's "place of residence" and "current location" as shown in the user management table (see Figure 10), and the degree of danger or importance for each type of source. The trained model may also receive the location information of the target sensor 10, the type of source, and the location information of the user to be judged as input, and generate an output indicating the priority of notifying the user of the measurement results from the target sensor 10 or whether notification is possible. The condition determination unit 209 may then make the determination in step 208 based on the output of the trained model. Alternatively, the condition determination unit 209 may perform the determination in step 209 based on the results of machine learning using a similar method.

[0133] If the location where the target sensor 10 measures the component generated based on the specific target source is within the notification recommendation area (Yes in S209), the process proceeds to the next step. The condition determination unit 209 determines whether the specific target source is of the recommended type (S210). The condition determination unit 209 focuses on the "type" in the notification target management table (see Figure 6) that indicates the "type" identified for the specific target source in the result management table. Then, the condition determination unit 209 performs the process in step 210 depending on whether "○" is indicated in the "recommended type" associated with the "type" it focused on.

[0134] If the source of the specified target is of the recommended type (Yes in S210), the condition determination unit 209 determines whether the user being determined is an administrator of the support system 1 (S211). The condition determination unit 209 performs the process in step 211 based on the "attributes" associated with the "user" corresponding to the user being determined in the user management table (see Figure 10). If the user being judged is an administrator (Yes in S211), the condition determination unit 209 determines whether the source of the specified target is a type of target for action (S212). The type of target for action is a type of source predetermined as a type that is subject to action by the administrator. In this disclosure, for example, a "Type" that is marked with "○" in the "Target Type" column of the notification target management table (see Figure 6) is considered a type of target for action. However, the type of target for action may be determined independently of the "Target Type".

[0135] If the source of the specified target is of the type that requires treatment, the target determination unit 211 determines that the source of the specified target is subject to treatment by the administrator (S213). If the user being judged is not an administrator (No in S211), if the source of the specific target is not of the type to be treated (No in S212), or if the process proceeds to the next step after step 213, the target determination unit 211 determines that the user being judged will be the target of notification based on the measurement results from the target sensor 10 (S207).

[0136] Furthermore, if the source of the specified target is not of the recommended type (No in S210), the condition determination unit 209 determines whether the mode of the user being determined corresponds to a mode that is subject to notification (S214). The condition determination unit 209 focuses on the "mode" associated with the "user" corresponding to the user being determined in the user management table (see Figure 10). Then, the condition determination unit 209 determines whether the mode of the user being determined is subject to notification based on whether the "mode" it focuses on corresponds to the type of source of the specified target. For example, suppose the type of source of the specified target is the "Japanese crested ibis" as an example of a rare animal. In this case, if the "rare animal mode" is set for the "user" corresponding to the user being determined, it is determined that the mode of the user being determined is a mode subject to notification (Yes in S214). Also, if a mode other than the "rare animal mode" is set for the "user" corresponding to the user being determined, it is determined that the mode of the user being determined is a mode that is not subject to notification (No in S214).

[0137] Furthermore, the condition determination unit 209 may determine, based on the results of machine learning, whether the mode set for the user being determined corresponds to the type of source of the specific target. The management server 20 may use information such as the user's mode setting history, past notification results, and the user's operation history after notification as training data to generate a trained model that estimates which type of source should be targeted for notification in a particular mode. The trained model may also receive information such as the type of source, the mode of the user to be judged, and past notification trends as input and generate an output indicating whether or not it should be targeted for notification in that mode. The condition determination unit 209 may then make the determination in step 214 based on the output of the trained model.

[0138] If the mode of the user being judged matches a mode that is subject to notification (Yes in S214), the target determination unit 211 determines that the user being judged will be subject to notification based on the measurement results from the target sensor 10 (S207). If the mode of the user being judged does not correspond to a mode that is subject to notification (No in S214), the target determination unit 211 determines that the user being judged will not be subject to notification based on the measurement results from the target sensor 10 (S215).

[0139] Furthermore, if the location where the target sensor 10 measures the component generated based on the specific target source is not within the notification recommendation area (No in S209), the process proceeds to the next step. The condition determination unit 209 determines whether the specific target source is a mandatory type or not (S216). The condition determination unit 209 focuses on the "type" in the notification target management table (see Figure 6) that indicates the identified "type" for the specific target source. Then, the condition determination unit 209 performs the process in step 216 depending on whether or not "○" is indicated in the "mandatory type" associated with the "type" it focused on.

[0140] If the source of the specified target is of the required type (Yes in S216), the target determination unit 211 determines that the user to be determined will be the target of notification based on the measurement results from the target sensor 10 (S207). If the source of the specified target is not of the required type (No in S216), the target determination unit 211 determines that the user to be determined will be subject to non-notification based on the measurement results from the target sensor 10 (S215).

[0141] Furthermore, if the target sensor 10 does not satisfy the type area conditions (No in S208), the condition determination unit 209 determines whether the source of the specified target is of the target type (S217). The condition determination unit 209 focuses on the "type" in the notification target management table (see Figure 6) that indicates the "type" identified for the source of the specified target in the result management table. Then, the condition determination unit 209 performs the process in step 217 depending on whether or not "○" is indicated for the "target type" associated with the "type" that it focused on. If the source of the specified target is of the target type (Yes in S217), the condition determination unit 209 determines whether the source of the specified target satisfies the positional relationship conditions (S218). The positional relationship conditions are predetermined conditions regarding the positional relationship between the source of the specified target and the user being determined. As will be described in detail later, the positional relationship conditions are used by the condition determination unit 209 to determine whether or not to notify the user being determined of the measurement results by the sensor 10 of the target for the "target type" shown in the type management table.

[0142] Furthermore, the condition determination unit 209 may determine, based on the results of machine learning, whether the positional relationship between the source of the specific target and the user being determined satisfies the positional relationship conditions. The management server 20 may use as training data information such as the relationship between the location where the component generated based on the source was measured in the past and the user's location, the distance range in which notifications were effective in the past, and the range of influence for each type of source. The trained model may also receive the location where the source of a specific target was detected, the current location or planned location of the user to be judged, and the type of source as input, and generate an output indicating whether or not the location relationship is such that a notification should be issued, or the effectiveness of the notification. The condition determination unit 209 may then make the determination in step 218 based on the output of the trained model.

[0143] If the source of the specified target satisfies the positional relationship conditions (Yes in S218), the target determination unit 211 determines that the user to be determined will be the target of notification based on the measurement results from the target sensor 10 (S207). If the source of the specified target is not of the target type (No in S217), or if the source of the specified target does not satisfy the positional relationship conditions (No in S218), the target determination unit 211 determines that the user to be determined will be subject to non-notification based on the measurement results from the target sensor 10 (S215).

[0144] After step 207 or step 215, proceed to the next step. The condition determination unit 209 determines whether or not all users of the support system 1 have been determined to be users to be determined (S219). If there are users who have not been determined to be the target users (No in S219), the process from step 205 is repeated. As a result, the process from step 205 onwards is performed for each user of support system 1. Furthermore, if all users are determined to be users subject to determination (Yes in S219), the process proceeds to the next step. The information generation unit 210 generates information to be notified for each user, according to the content of the processing in the fixed notification process and the content of the determination by the information determination unit 209 in the result output process. The information provision unit 212 then notifies the information by having the target determination unit 211 output the information generated by the information generation unit 210 to the user terminals of the users determined to be subject to notification (S220). The information notified at this time is the information generated by the information generation unit 210 according to the users determined to be subject to notification. Furthermore, no information is output to the user terminals of users determined to be not subject to notification in step 202 or step 215.

[0145] Figure 19 is a flowchart showing the flow of the deletion process. The deletion process is the process by which the management server 20 deletes the information of individuals identified by the source identification unit 206 from the individual management table (see Figure 7). In this disclosure, for example, the deletion process may be started when a predetermined number of individuals or more are identified based on the results of measurements by multiple sensors 10 located within a predetermined range, and when such measurements by the multiple sensors 10 are performed within a predetermined period. The predetermined range may be any range, but for example, it may be a range with a diameter of 10m. The predetermined number may be any number, but for example, it may be 3. The predetermined period may be any amount of time, but for example, it may be 5 minutes.

[0146] The comparison unit 205 of the management server 20 focuses on each of the graphs generated by steps 101 and 102 of the fixed notification process (see Figure 15) with respect to the result information used to identify the individual that triggered the deletion process. The comparison unit 205 then determines whether the graphs it focuses on satisfy the combination conditions (S301). The combination conditions are conditions used by the comparison unit 205 to determine whether the graph generated by the graph generation unit 204 for the individual identified by the source identification unit 206 is a graph generated from the results of each component generated from multiple individuals being measured by a single sensor 10 at the same timing. In this disclosure, the combination conditions are defined as the degree of similarity between the combination of resistance values ​​per unit time shown in the two graphs that the comparison unit 205 focuses on and the resistance values ​​per unit time shown in the other graph that it focuses on, satisfying a predetermined standard. For example, predetermined criteria include a 99% or higher agreement rate between the combination of resistance values ​​per unit time shown in two graphs of interest and the resistance values ​​per unit time shown in another graph of interest.

[0147] I will now explain in detail the method for determining the combination conditions. Figure 20 is a diagram illustrating the concept of the method by which the comparison unit 205 determines the combination conditions. In the following example, it is assumed that three individuals were identified by the source identification unit 206 as the trigger for the deletion process. Figure 20(A) shows the graphs generated by the graph generation unit 204 for the three identified individuals, individual A, individual B, and individual C.

[0148] The graph generation unit 204 generates a graph that combines the resistance values ​​per unit time shown in the graphs of two of the three figures. The comparison unit 205 then compares the graph formed by combining the two figures with the graph of the remaining single figure. Furthermore, the graph generation unit 204 combines the individuals identified as triggers for deletion processing so as to cover all possible combination patterns. Any method may be used for combination, but one example is the method of adding the resistance values ​​of the two graphs to be combined. Alternatively, for example, a method of calculating the average resistance value per unit time for the two graphs to be combined, a method of extracting the maximum or minimum value, a method of weighting each graph and then combining them, or a method of superimposing one graph on the other based on the other graph may be used. In addition, the graph generation unit 204 may generate the combined graph by, for example, extracting feature quantities of the shape of each graph to be combined and combining or integrating the extracted feature quantities. Furthermore, the comparison unit 205 compares the combined graph with each of the graphs that were not included in the combination among the individuals identified as triggers for deletion processing.

[0149] In this example, the comparison unit 205 assumes that the graph of individual C satisfies the combination condition in relation to the graphs of individual A and individual B combined, as shown in Figure 20(B). In this case, the comparison unit 205 identifies the component to be measured shown in the graph of individual C as a combination of the component to be measured shown in the graph of individual A and the component to be measured shown in the graph of individual B.

[0150] Returning to the explanation of Figure 19, if the combination condition is met (Yes in S301), the comparison unit 205 deletes the information of the individuals that are the target of the graph satisfying the combination condition from the individual management table (see Figure 7) (S302). The comparison unit 205 also updates the contents of the result management table (see Figure 8) for the result information that is the target of the graph satisfying the combination condition. Furthermore, the counting unit 208 counts the number of individuals again based on the deleted individual information and updates the contents of the individual count management table (see Figure 9) according to the counting result. In the example shown in Figure 20, the comparison unit 205 deletes the information for individual C from the individual management table. The comparison unit 205 also overwrites the content shown for individual C in the results management table from "individual C" to "individual A + individual B". Furthermore, the counting unit 208 updates the "specific number" and "specific number / extermination number" associated with the "area" and "attribute" to which individual C belongs in the individual count management table. Specifically, the counting unit 208 subtracts one from the "specific number" associated with the "area" and "attribute" to which individual C belongs, and updates the "specific number / extermination number" according to the "specific number" after the subtraction.

[0151] The triggers for the deletion process are not limited to the examples described above. For example, the deletion process may be started each time a new individual is identified by the source identification unit 206. In this case, the graph generation unit 204 may combine graphs to cover all possible combinations for each individual identified by the source identification unit 206. The comparison unit 205 may also compare the combined graphs with each individual identified by the source identification unit 206. In this case, even if multiple sources exist simultaneously in close proximity, the identification results of the source individuals are continuously corrected, improving the accuracy of individual identification by the management server 20.

[0152] Furthermore, the comparison unit 205 may execute the process in step 301 of the deletion process based on the results of machine learning. The management server 20 may input graphs generated based on measurement results from a single measuring means, such as the sensor 10, as training data into the learning model. The graphs input into the learning model include graphs generated based on measurement results from components generated from a single source, and graphs generated based on measurement results when each of the components generated from multiple sources is simultaneously measured by a single measuring means, such as the sensor 10. The management server 20 may generate a trained model by inputting these graphs as training data into the learning model. The trained model may also determine whether the input graph is the result of components generated from multiple sources being simultaneously measured by a single sensor 10. The trained model may then output whether the combination condition is satisfied, or its probability or degree of agreement, as a result of the determination. Furthermore, the comparison unit 205 may determine whether the combination condition in step 301 is satisfied based on the output of the trained model.

[0153] Next, we will describe an example of information that will be notified to the user as a result of the fixed notification process. In the following, we assume that in the fixed notification process (see Figures 15 and 16), the type of source of the specified target is identified as a bear (S109), and the required time condition is not met (No in S116). Furthermore, in the result output process (see Figures 17 and 18), we assume that the type area condition is met (Yes in S208), and that the position where the target sensor 10 measures the component generated based on the source of the specified target is within the notification recommendation area in relation to the user being judged (Yes in S209). In addition, we assume that the type of source of the specified target is a recommended type (Yes in S210). In this case, the information provision unit 212 of the management server 20 may, via the transmission / reception unit 201, display the notification screen 300 shown in Figure 21(A) on the user terminal of the user who is the target of the notification.

[0154] The notification screen 300 is a screen for notifying the user of the measurement results from the sensor 10. The notification screen 300 shown in Figure 21(A) is the notification screen 300 displayed on the user terminal 40 of the support system 1. In the following, the user who is the target of the notification screen 300, in other words, the user who owns the user terminal on which the notification screen 300 is displayed, may be referred to as the target user. The notification screen 300 displays a date and time image 301, an overview image 302, a notice notification section 304, a result image 310, and a location image 320.

[0155] The date and time image 301 displays the current time. In the example shown, the date and time image 301 displays the text "March 1, 2026, 6:30 AM". The information generation unit 210 of the management server 20 generates the date and time image 301 based on the timing result from the timing unit 203. Summary image 302 shows an overview of the measurement results from sensor 10. In the illustrated example, summary image 302 shows the text "A bear has been found in your residential area," including the location of the source or the sensor 10 that detected the source, and the type of source. The information generation unit 210 generates summary image 302 according to the information transmitted from the target sensor 10 and the results of the source identification unit 206 and related identification unit 207 in the fixed notification processing. The caution notification section 304 displays points to note depending on the type or individual source of the specific target. In the illustrated example, the caution notification section 304 displays the text, "Take care to avoid encountering bears, based on the bear's past range of movement."

[0156] The result image 310 is an image that shows information regarding the measurement results of the sensor 10. The result image 310 shows the source image 312, the time of occurrence image 313, the attribute image 314, the size image 315, and the cumulative image 316. The source image 312 shows the type of source identified by the related identification unit 207 in the fixed notification process (see Figure 15) (S110, S119). In the illustrated example, the source image 312 shows the text "Detected odor source: Feces". The occurrence time image 313 shows the occurrence time (S114, S119) of the component identified by the related identification unit 207 in the fixed notification process. In the illustrated example, the occurrence time image 313 shows the text "Occurrence time of detected odor: March 1, 2026, 6:25 AM".

[0157] The attribute image 314 shows the source's gender and age as the source's attributes (S111, S119) identified by the related identification unit 207 in the fixed notification process. In the illustrated example, the attribute image 314 shows the text "Attributes of the detected entity: Male, 5 years old". The size image 315 shows the height and weight of the source as the size of the source identified by the related identification unit 207 in the fixed notification process (S113, S119). In the illustrated example, the size image 315 shows the text, "Estimated size of detected object: 1.8m, 220kg". The cumulative image 316 shows information regarding the number of individuals counted by the counting unit 208 for the type of source of the specific target. In the illustrated example, the cumulative image 316 shows the text "Cumulative number of specific individuals of the same species in this area: 8" which is the number of bears belonging to the "area" corresponding to the location of the target sensor 10 in the population management table (see Figure 9). This "area" may be a "prefecture," a "city / ward / town / village," or a "minimum area" in the population management table. In other words, this "area" may be any unit of "area" shown in the population management table.

[0158] Furthermore, the information shown in the source image 312, attribute image 314, and size image 315 in the result image 310 is the "source," "sex," "age (years)," "height (m)," and "weight (kg)" information associated with the "bear" whose "age (years)" is "5" in the species management table (see Figure 5). In addition, the identified target graph is assumed to satisfy the species identification condition (see S108 in Figure 15) in relation to the "graph" associated with the "bear" whose "age (years)" is "5" in the species management table (see Figure 5).

[0159] Location image 320 is an image showing the location of the source of a specific target or the location of the user being notified. Location image 320 shows the user's current location explanation section 321, the sensor location explanation section 322, the source's current location explanation section 323, and the similar past explanation section 324. Location image 320 also shows a map image 340, the user's current location display section 341, the sensor location display section 342, the source's current location display section 343, and the similar past display section 344.

[0160] The user location description section 321 describes the current location of the user being notified. In the illustrated example, the user location description section 321 shows a mark and the text "User's current location". The sensor position description unit 322 describes the position of the target sensor 10. In the illustrated example, the sensor position description unit 322 shows a mark and the text "Position of the detected sensor". The source location explanation unit 323 explains the current location of the source of the specified target. In the illustrated example, the source location explanation unit 323 shows a mark and the text "Current location of the detected object (expected range)". The similar species past description section 324 describes the past range of activity of the source of the specific target and the source of the same species. In the illustrated example, the similar species past description section 324 shows a mark and the text "Past range of activity of the same species (March 2025, 6am)". The similar species past description section 324 may also show the species identified for the source of the specific target, for example, "Past range of activity of bears of the same species as the detected object (March 2025, 6am)". Furthermore, each image displayed in the location image 320, such as the user's current location explanation section 321, the sensor location explanation section 322, the source location explanation section 323, and the similar past explanation section 324, displays a different mark.

[0161] Map image 340 shows a map. In the illustrated example, map image 340 shows a map that includes the location of the target sensor 10 and the current location of the user to be notified. The information generation unit 210 generates map image 340 based on the "installation location" of the target sensor 10 in the sensing means management table (see Figure 4) and the "current location" of the user to be notified in the user management table (see Figure 10).

[0162] The user current location display unit 341 shows the current location of the user being notified. In the illustrated example, the user current location display unit 341 is the same mark shown in the user current location explanation unit 321, and is displayed in the area of ​​the map image 340 that corresponds to the user's current location. The information generation unit 210 determines the display position of the user current location display unit 341 on the map image 340 based on the "current location" of the user being notified in the user management table.

[0163] The sensor position display unit 342 shows the position where the target sensor 10 measured the component generated from the specific target source. In the illustrated example, the sensor position display unit 342, as shown in the sensor position explanation unit 322, is shown in the area of ​​the map image 340 that corresponds to the position where the target sensor 10 measured the component generated from the specific target source. If the target sensor 10 is a fixed sensor 11, the information generation unit 210 determines the display position of the sensor position display unit 342 on the map image 340 based on the "installation position" of the target sensor 10 in the sensing means management table (see Figure 4) in the result management table (see Figure 8).

[0164] The current location of the source of the specified target is shown in the current location of the source of the specified target, as identified by the related identification unit 207. In the illustrated example, the current location of the source

[0165] The similar-type past display unit 344 shows the past activity range of the source of the specified target and sources of the same type. In the illustrated example, the same-type past display unit 344 shows the same marks as those shown in the similar-type past explanation unit 324, within the area shown in the map image 340 that corresponds to the past activity range of the source of the specified target and sources of the same type. The information generation unit 210 generates the similar-type past display unit 344 based on the information of each "location" in the map image 340 that corresponds to the area shown in the map image 340, among the "locations" associated with the "type" that is the target of notification on the notification screen 300, in the result management table (see Figure 8). Alternatively, the information generation unit 210 may generate the similar-type past display unit 344 only for "locations" associated with the "measurement date and time" that shows the same month and / or the same time period as shown in the occurrence time image 313 in the result management table. In this case, the characteristics of the source's activity according to the season or time are reflected in the similar-type past display unit 344. Examples of times belonging to the same time zone include times corresponding to the same hour hand.

[0166] Next, we will explain another example of notification screen 300. In the following, we assume that in the fixed notification process (see Figures 15 and 16), the type of source of the specified target is identified as a bear (S109), and the required time condition is not met (No in S116). Furthermore, in the result output process (see Figures 17 and 18), we assume that the type area condition is met (Yes in S208), and that the position where the target sensor 10 measures the component generated based on the source of the specified target is in the notification recommendation area in relation to the user being judged (Yes in S209). In addition, we assume that the type of source of the specified target is a recommended type (Yes in S210), the user being judged is an administrator (Yes in S211), and the source of the specified target is a type that requires action (Yes in S212). In this case, the administrator terminal 30 of the administrator, who is the user being notified, may display the notification screen 300 shown in Figure 21(B).

[0167] The notification screen 300 shown in Figure 21(B) displays a date and time image 301, an overview image 302, a treatment request image 305, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 21(B) will be described in a way that differs from the notification screen 300 shown in Figure 21(A), while the same configuration as the notification screen 300 shown in Figure 21(A) will not be described.

[0168] The date and time image 301, summary image 302, result image 310, and location image 320 show the same information as the notification screen 300 shown in Figure 21(A). Image 305, a request for action, is an image used to request that the administrator take action regarding the source of a specific pest. In the illustrated example, image 305 shows the text, "This is a target for extermination. Please take action." The information displayed in the treatment request image 305 is not limited to the examples described above. The treatment request image 305 may also display information related to capture, such as, "This animal is a target for capture. Please take action."

[0169] Next, we will explain another example of notification screen 300. In the following, we assume that in the fixed notification process (see Figures 15 and 16), the type of source of the specified target is identified as a bear (S109), and the required time condition is not met (No in S116). Furthermore, in the result output process (see Figures 17 and 18), the type area condition is met (Yes in S208), and the position where the target sensor 10 measures the component generated based on the source of the specified target is not in the notification recommendation area in relation to the user being judged (No in S209). In addition, the type of source of the specified target is a required type (Yes in S216). In this case, the notification screen 300 shown in Figure 22(A) may be displayed on the user terminal of the notified user.

[0170] The notification screen 300 shown in Figure 22(A) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 22(A) will be described in a way that differs from the notification screen 300 shown in Figure 21(A), while the same configuration as the notification screen 300 shown in Figure 21(A) will not be described.

[0171] In the example shown, the overview image 302 displays the text, "Bears have been spotted in the suburbs of your city or town." Furthermore, location image 320 shows the user's current location explanation section 321, the sensor location explanation section 322, the source location explanation section 323, and the similar past explanation section 324. Also, location image 320 shows the map image 340, the user's current location display section 341, the sensor location display section 342, the source location display section 343, and the similar past display section 344. The map image 340, the user's current location display section 341, the sensor location display section 342, the source location display section 343, and the similar past display section 344 display different content from the example shown in Figure 21(A). Thus, different information may be displayed on the notification screen 300 depending on the region defined by the relationship between the location of the target sensor 10 and the user to be judged, such as the "region" in the user management table (see Figure 10). The information generation unit 210 may, for example, generate the content of the summary image 302, such as "suburbs," based on the distance or administrative division corresponding to the relationship between the "place of residence" of the notified user in the user management table and the "location" of the source of the specific target in the result management table (see Figure 8).

[0172] Next, we will explain another example of notification screen 300. In the following, we assume that in the fixed notification process (see Figures 15 and 16), the type of the source of the specified target is identified as the Japanese crested ibis (S109), and the required time condition is not met (No in S116). Furthermore, in the result output process (see Figures 17 and 18), the type area condition is met (Yes in S208), and the position where the target sensor 10 measures the component generated based on the source of the specified target is not in the notification recommendation area in relation to the user being judged (No in S209). In addition, we assume that the type of the source of the specified target is not a required type (No in S216), and the mode of the user being judged is "rare animal mode" (see Figure 14(B)), which means it falls under the mode that is subject to notification (Yes in S214). In this case, the notification screen 300 shown in Figure 22(B) may be displayed on the user terminal of the user being notified.

[0173] The notification screen 300 shown in Figure 22(B) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 22(B) has a different configuration from the notification screen 300 shown in Figure 21(A), and the configuration that is the same as the notification screen 300 shown in Figure 21(A) will not be explained.

[0174] In the illustrated example, the overview image 302 displays the text, "A crested ibis has been found approximately 2 km away from your current location." The information generation unit 210 generates the information to be displayed in the overview image 302 based on the relationship between the "current location" of the notified user in the user management table (see Figure 10) and the "location" of the source of the specific target in the result management table (see Figure 8). In addition, in the illustrated example, the notice section 304 displays the text, "Please do your best to find the crested ibis, taking into account its past range of movement!" Thus, the overview image 302 and the caution notification section 304 may display content corresponding to the type of source of the specified target.

[0175] Furthermore, the result image 310 displays the source image 312, the occurrence time image 313, the attribute image 314, the size image 315, and the cumulative image 316. In the illustrated example, the source image 312 displays the text, "Detected odor source: Feces." In the illustrated example, the image 313 showing the time of occurrence displays the text, "Time of occurrence of detected odor: March 2, 2026, 11:10 AM." In the illustrated example, attribute image 314 shows the text "Attributes of the detected subject: Male, 10 years old". In the illustrated example, size image 315 shows the text, "Estimated size of detected object: 0.8m, 1.7kg". In the illustrated example, cumulative image 316 shows the text "Cumulative number of specific individuals of this species in this area: 20," which is the number of crested ibises belonging to the "area" corresponding to the location of the target sensor 10 in the population management table (see Figure 9).

[0176] Furthermore, the information shown in the source image 312, attribute image 314, and size image 315 in the result image 310 is the "source," "sex," "age (years)," "height (m)," and "weight (kg)" information associated with the "crested ibis" whose "age (years)" is "10" in the species management table (see Figure 5). In addition, the identified target graph is assumed to satisfy the species identification condition (see S108 in Figure 15) in relation to the "graph" associated with the "crested ibis" whose "age (years)" is "10" in the species management table (see Figure 5).

[0177] Furthermore, in location image 320, the user's current location display unit 341, the sensor location display unit 342, the source's current location display unit 343, and the same type's past display unit 344 show different content than when the type of source of the specific target was a bear (see Figures 21(A) and 22(A)).

[0178] Next, we will explain another example of notification screen 300. In the following, it is assumed that in the fixed notification processing (see Figures 15 and 16), the type of the source of the specified target is identified as a bear (S109), and the required time condition is not met (No in S116). Also, in the result output processing (see Figures 17 and 18), the type area condition is not met (No in S208), and the source of the specified target is of the target type (Yes in S217). Furthermore, in this example, it is assumed that a positional relationship condition (see S218 in Figure 18) is defined regarding the relationship between the current reference position of the source of the specified target and the current location of the user being judged. The current reference position is the position when the target sensor 10 measures the component generated based on the source of the specified target, or the area identified as the current location of the source of the specified target (see S115 in Figure 15 and S119 in Figure 16). In this example, the positional relationship condition is that the current reference position of the source of the specified target and the current location of the user being judged are less than or equal to a predetermined distance. Furthermore, the predetermined distance can be any distance, but for example, it is 1 km. In this example, the positional relationship condition is assumed to be met (Yes in S218). In this case, the notification screen 300 shown in Figure 23(A) may be displayed on the user terminal of the notified user.

[0179] The notification screen 300 shown in Figure 23(A) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 23(A) will be described in a way that differs from the notification screen 300 shown in Figure 21(A), while the same configuration as the notification screen 300 shown in Figure 21(A) will not be described.

[0180] In the illustrated example, the overview image 302 shows the text, "A bear has been spotted near your current location." The information generation unit 210 generates the overview image 302 with content corresponding to the location relationship conditions being met during the result output processing.

[0181] The result image 310 shows the source image 312, the occurrence time image 313, the attribute image 314, the size image 315, and the cumulative image 316. In the illustrated example, the source image 312 displays the text, "Detected odor source: Feces." In the illustrated example, the image 313 showing the time of occurrence displays the text, "Time of occurrence of detected odor: March 1, 2026, 6:25 AM." In the illustrated example, attribute image 314 shows the text "Attributes of the detected subject: Male, 5 years old". In the illustrated example, size image 315 shows the text, "Estimated size of detected object: 1.8m, 220kg". In the illustrated example, cumulative image 316 shows the text, "Cumulative number of this species in this area: 8 individuals."

[0182] The location image 320 shows the user's current location explanation section 321, the sensor location explanation section 322, the source location explanation section 323, the similar past explanation section 324, the map image 340, the user's current location display section 341, the sensor location display section 342, the source location display section 343, and the similar past display section 344. Furthermore, in location image 320, the map image 340, user current location display unit 341, sensor location display unit 342, source current location display unit 343, and similar past display unit 344 display different content from the examples shown in Figures 21(A) and 22(A).

[0183] Next, we will explain another example of notification screen 300. In the following, we assume that in the fixed notification process (see Figures 15 and 16), the type of source of the specified target is identified as a bear (S109), and the required time condition is not met (No in S116). Furthermore, in the result output process (see Figures 17 and 18), the type area condition is not met (No in S208), and the source of the specified target is of the target type (Yes in S217). In addition, in this example, we assume that a positional relationship condition (see S218 in Figure 18) is defined regarding the relationship between the current reference position of the source of the specified target and the area that the user subject to judgment plans to go to. More specifically, the positional relationship condition is that the current reference position of the source of the specified target and the area that the user subject to judgment plans to go to are less than or equal to a predetermined distance. The predetermined distance can be any distance, but for example, it is 1 km. The condition determination unit 209 determines whether the positional relationship condition is met based on the "planned location" of the user subject to judgment in the user management table (see Figure 10). In this case, the "scheduled location" that the condition determination unit 209 determines may be a "scheduled location" for a date and time earlier or later than the time when the measurement related to the graph of the specified object was performed. In this example, the positional relationship condition is assumed to be met (Yes in S218). In this case, the notification screen 300 shown in Figure 23(B) may be displayed on the user terminal of the notified user.

[0184] The notification screen 300 shown in Figure 23(B) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 23(B) will be described in a way that differs from the notification screen 300 shown in Figure 23(A), while the same configuration as the notification screen 300 shown in Figure 23(A) will not be described.

[0185] In the notification screen 300 shown in Figure 23(B), the date and time image 301, the attention notification section 304, and the result image 310 display the same content as shown in Figure 23(A). Also, in the illustrated example, the summary image 302 shows the text "A bear has been found near the place you are going to." The information generation unit 210 generates the summary image 302 with content corresponding to the satisfaction of the positional relationship condition in the result output process.

[0186] Also, in the position image 320 shown in FIG. 23(B), a user current location explanation unit 321, a user planned location explanation unit 329, a sensor position explanation unit 322, a source location explanation unit 323, and a same-kind past explanation unit 324 are shown. Also, in the position image 320, a map image 340, a user current location display unit 341, a user planned location display unit 349, a sensor position display unit 342, a source location display unit 343, and a same-kind past display unit 344 are shown.

[0187] The user planned location explanation unit 329 explains the area to which the place the user to be notified plans to go belongs. In the illustrated example, the user planned location explanation unit 329 shows a mark and the text "Place where the user plans to go (place name: ○○)" indicating the name of the place the user to be notified plans to go. The information generation unit 210 generates the information to be displayed on the user planned location explanation unit 329 based on the "planned location" of the user to be notified for whom the positional relationship condition in the user management table (see FIG. 10) is satisfied. The user planned location display unit 349 shows the area that the user to be notified plans to go. In the illustrated example, as the user planned location display unit 349, the same mark as that shown in the user planned location explanation unit 329 is shown in the area corresponding to the place the user to be notified plans to go among the areas shown in the map image 340. The information generation unit 210 determines the display position on the map image 340 of the user planned location display unit 349 based on the "planned location" of the user to be notified for whom the positional relationship condition in the user management table is satisfied.

[0188] In the illustrated example, the distance from the sensor position display unit 342 to the user's planned destination display unit 349 is shorter than the distance from the sensor position display unit 342 to the user's current location display unit 341. Also, the distance from the source location display unit 343 to the user's planned destination display unit 349 is shorter than the distance from the source location display unit 343 to the user's current location display unit 341. In this case, the user grasps that the location where the user plans to go is closer to the detected object S, which is the source of the specific target, than the user's current location.

[0189] Next, another example of the notification screen 300 will be described. Hereinafter, in the fixed notification process (see FIGS. 15 and 16), it is assumed that the type of the source of the specific target is specified as a bear (S109), and the required time condition is not satisfied (No in S116). Also, in the result output process (see FIGS. 17 and 18), the type area condition is not satisfied (No in S208), and it is assumed that the source of the specific target is the target type (Yes in S217). Further, in this example, it is assumed that a positional relationship condition (see S218 in FIG. 18) is defined regarding the relationship between the current reference position of the source of the specific target and the past position of the user to be determined. More specifically, it is assumed that the positional relationship condition is that the current reference position of the source of the specific target and the past position of the user to be determined are within a predetermined distance. Also, the predetermined distance may be any distance, but for example, it is 1 km. Also, the past position subject to the determination of the positional relationship condition may be in the past within a predetermined period from the current time. The predetermined period may be any period, but for example, it is 1 year. The condition determination unit 209 determines whether the positional relationship condition is satisfied based on the information shown in the "current position" of the user to be determined in the user management table (see FIG. 10), and the information stored in the storage unit 202 as the past position when this "current position" is updated to the latest information. And in this example, it is assumed that the positional relationship condition is satisfied (Yes in S218). In this case, the notification screen 300 shown in FIG. 24(C) may be displayed on the user terminal of the user to be notified.

[0190] The notification screen 300 shown in Figure 24(C) displays a date and time image 301, an overview image 302, a notice notification section 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 24(C) has a different configuration from the notification screen 300 shown in Figure 23(A), and the configuration that is the same as the notification screen 300 shown in Figure 23(A) will not be explained.

[0191] In the notification screen 300 shown in Figure 24(C), the date and time image 301, the attention notification section 304, and the result image 310 display the same content as shown in Figure 23(A). In the illustrated example, the overview image 302 displays the text, "A bear has been found near a place you have visited in the past." The information generation unit 210 generates the overview image 302 with content corresponding to whether the positional relationship conditions are met during the result output processing.

[0192] Furthermore, the location image 320 shown in Figure 24(C) includes a user current location explanation unit 321, a user past location explanation unit 330, a sensor location explanation unit 322, a source current location explanation unit 323, and a similar past location explanation unit 324. Additionally, the location image 320 includes a map image 340, a user current location display unit 341, a user past location display unit 350, a sensor location display unit 342, a source current location display unit 343, and a similar past location display unit 344.

[0193] The User Past Location Description Unit 330 describes the area to which the notified user's past location belongs. In the illustrated example, the User Past Location Description Unit 330 displays a mark and the text "Places the user has visited in the past (Place name: ○○)" indicating the name of a place the notified user has visited in the past. The Information Generation Unit 210 generates the information to be displayed in the User Past Location Description Unit 330 based on the information shown in the "Current Location" of the notified user in the user management table (see Figure 10), which is stored in the storage unit 202 as a past location when this "Current Location" is updated with the latest information. In addition, the Information Generation Unit 210 may generate the User Past Location Description Unit 330 by obtaining the place name or facility name corresponding to the information indicating the past location based on map information or geocoding information. The User Past Location Display Unit 350 shows an area corresponding to the past location of the notified user. In the illustrated example, the User Past Location Display Unit 350 uses the same mark as shown in the User Past Location Explanation Unit 330, and is displayed in the area of ​​the map image 340 that corresponds to the past location of the notified user. The Information Generation Unit 210 determines the display position of the User Past Location Display Unit 350 on the map image 340 based on the information that was shown in the "Current Location" of the notified user whose location relationship conditions are met in the user management table, and which is stored in the storage unit 202 as a past location when this "Current Location" is updated with the latest information.

[0194] In the illustrated example, the distance from the sensor location display unit 342 to the user's current location display unit 341 is shorter than the distance from the sensor location display unit 342 to the user's past location display unit 350. Also, the distance from the source location display unit 343 to the user's past location display unit 350 is shorter than the distance from the source location display unit 343 to the user's current location display unit 341. In this case, the user will understand that their past location is closer to the detected object S, which is the source of the specific target, than their current location. Users may revisit places they have stayed in the past. Therefore, the support system 1 defines location relationship conditions for the user's past locations, and if these location relationship conditions are met, it may notify the user of the notification screen 300.

[0195] Next, we will explain another example of notification screen 300. In the following, it is assumed that in the fixed notification processing (see Figures 15 and 16), the type of source of the specified target is identified as a bear (S109), and the required time condition is not met (No in S116). Furthermore, in the result output processing (see Figures 17 and 18), the type area condition is not met (No in S208), and the source of the specified target is of the target type (Yes in S217). In addition, in this example, it is assumed that a positional relationship condition (see S218 in Figure 18) is defined regarding the relationship between the past range of activity of sources of the same type as the source of the specified target and the current location of the user being judged. More specifically, the positional relationship condition is that the past range of activity of sources of the same type as the source of the specified target and the current location of the user being judged are less than or equal to a predetermined distance. The predetermined distance may be any distance, for example, 1 km. In this case, the past range of activity of sources of the same type as the source of the specified target may be identified by the same method used to determine the display position of the same type past display unit 344. Furthermore, the past range of activity of similar sources that are subject to the determination of the location relationship condition may be the past range of activity within a predetermined period from the present time. The predetermined period may be any period, but for example, it may be one year. In this example, the location relationship condition is assumed to be met (Yes in S218). In this case, the notification screen 300 shown in Figure 24(D) may be displayed on the user terminal of the notified user.

[0196] The notification screen 300 shown in Figure 24(D) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 24(D) has a different configuration from the notification screen 300 shown in Figure 23(A), and the same configuration as the notification screen 300 shown in Figure 23(A) will not be explained.

[0197] In the notification screen 300 shown in Figure 24(D), the date and time image 301, the attention notification section 304, and the result image 310 display the same content as shown in Figure 23(A). In the illustrated example, the overview image 302 displays the text, "A bear has been spotted. In the past, bears have appeared near your current location." The information generation unit 210 generates the overview image 302 with content corresponding to whether the positional relationship conditions are met during the result output processing.

[0198] Furthermore, the location image 320 shown in Figure 24(D) includes a user current location explanation unit 321, a sensor location explanation unit 322, a source current location explanation unit 323, a similar past explanation unit 324, a map image 340, a user current location display unit 341, a sensor location display unit 342, a source current location display unit 343, and a similar past display unit 344. In the illustrated example, the distance from the sensor position display unit 342 to the user's current location display unit 341 is shorter than the distance from the user's current location display unit 341 to the sensor position display unit 342. Also, the distance from the user's current location display unit 344 to the user's current location display unit 341 is shorter than the distance from the source current location display unit 343 to the user's current location display unit 341. In this case, the user will understand that the past locations of sources of the same type as the source of the specific target are closer to the user's current location than the location where the source of the specific target was detected or the current location of the source of the specific target.

[0199] Next, we will explain another example of notification screen 300. In the following, we assume that in the fixed notification process (see Figures 15 and 16), the type of source of the specified target is identified as a bear (S109), and the required time condition is not met (No in S116). Furthermore, in the result output process (see Figures 17 and 18), the type area condition is not met (No in S208), and the source of the specified target is of the target type (Yes in S217). In addition, in this example, we assume that a positional relationship condition (see S218 in Figure 18) is defined regarding the relationship between the future range of movement of the source of the specified target and the current location of the user being judged. More specifically, the positional relationship condition is that the future range of movement of the source of the specified target and the current location of the user being judged are less than or equal to a predetermined distance. The predetermined distance can be any distance, but for example, it is 1 km. In this case, the related identification unit 207 may determine the range of action for a predetermined period as the future of the source of the identified target, based on the content identified in step 115 or step 119 of the fixed notification processing. Alternatively, the related identification unit 207 may determine the range of action for a predetermined period as the future of the source of the identified target, based on the past range of action of sources of the same type as the source of the identified target. Furthermore, the related identification unit 207 may determine the range of action for a predetermined period as the future of the source of the identified target, based on the content identified in the fixed notification processing and the past range of action of sources of the same type as the source of the identified target. The predetermined period can be any period, but for example, it may be 1 hour. In this example, the positional relationship condition is assumed to be met (Yes in S218). In this case, the notification screen 300 shown in Figure 25(E) may be displayed on the customer terminal 40 of the customer who is the user subject to determination.

[0200] The notification screen 300 shown in Figure 25(E) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 25(E) will be described in a way that differs from the notification screen 300 shown in Figure 23(A), while the same configuration as the notification screen 300 shown in Figure 23(A) will not be explained.

[0201] In the notification screen 300 shown in Figure 25(E), the date and time image 301, the attention notification section 304, and the result image 310 display the same content as shown in Figure 23(A). In the illustrated example, the overview image 302 displays the text, "A bear has been spotted. There is a possibility that a bear may appear near your current location in the future." The information generation unit 210 generates the overview image 302 based on the content that is met in the result output processing, according to the positional relationship conditions.

[0202] Furthermore, the location image 320 shown in Figure 25(E) includes a user current location explanation unit 321, a sensor location explanation unit 322, a source current location explanation unit 323, a similar past explanation unit 324, and a source future location explanation unit 326. Additionally, the location image 320 includes a map image 340, a user current location display unit 341, a sensor location display unit 342, a source current location display unit 343, a similar past display unit 344, and a source future location display unit 346.

[0203] The future source location explanation unit 326 explains the results identified by the related identification unit 207 as the future range of activity of the source of the specified object. In the illustrated example, the future source location explanation unit 326 displays a mark and the text "Future range of activity of the detected object (expected range)" which indicates the future range of activity of the source of the specified object. The future location display unit 346 shows the future range of activity of the specified source. In the illustrated example, the future location display unit 346 is the same mark shown in the future location explanation unit 326, and is shown in the area of ​​the map image 340 that corresponds to the future range of activity of the specified source. The information generation unit 210 determines the display position of the future location display unit 346 on the map image 340 based on the results of the identification by the related identification unit 207.

[0204] In the illustrated example, the distance from the source future location display unit 346 to the user's current location display unit 341 is shorter than the distance from the sensor position display unit 342 to the user's current location display unit 341. Also, the distance from the source future location display unit 346 to the user's current location display unit 341 is shorter than the distance from the source current location display unit 343 to the user's current location display unit 341. In this case, the user grasps that the area corresponding to the future movement range of the source of the specific target is closer to the user's current location than the position where the source of the specific target is detected or the current location of the source of the specific target.

[0205] Note that the related specific unit 207 may specify the future movement range of the source of the specific target based on the results of machine learning. The management server 20 may input, for example, information on the measurement results of components measured in the past, the measurement date and time, the measurement position, the attributes, and the current reference position of the source, for the source of the specific target and sources of the same type as the source of the specific target, as learning data into the learning model. This learning model may learn the tendency of the source to move over time, the moving direction, the moving distance, or the way the action range spreads, based on past measurement results. The management server 20 may generate a learned model by inputting the learning data into the learning model. Also, the management server 20 may input information such as the current reference position, the measurement time, the attributes, and the measurement situation of the source of the specific target specified in the fixed notification process into the learned model. Then, based on the input information, the learned model may estimate the area where the source of the specific target is likely to exist in the future and output information indicating the area. This output may be, for example, information indicating an area on the map, a set of multiple positions, or a probabilistically weighted range, as the future movement range of the source of the specific target. Also, the related specific unit 207 may specify the future movement range of the source of the specific target based on the output of the learned model. Furthermore, the result of the specification by the related specific unit 207 may be used for the determination of the positional relationship condition and the generation of the information displayed on the notification screen 300.

[0206] Next, another example of the notification screen 300 will be described. In the following, during the fixed notification process (see Figures 15 and 16), the source of the specified target is identified as a bear by the source identification unit 206 (S109), and identified as a new individual that has not been previously identified (S118). Furthermore, during the result output process (see Figures 17 and 18), the type area condition is met (Yes in S208), and the position where the target sensor 10 measures the component generated based on the specified target source is in the notification recommendation area in relation to the user being judged (Yes in S209). In addition, the source of the specified target is of the recommended type (Yes in S210). In this case, the notification screen 300 shown in Figure 26(A) may be displayed on the user terminal of the notified user.

[0207] The notification screen 300 shown in Figure 26(A) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320. Note that the notification screen 300 shown in Figure 26(A) will be described in a way that differs from the notification screen 300 shown in Figure 21(A), while the same configuration as the notification screen 300 shown in Figure 21(A) will not be described.

[0208] The date and time image 301 and the summary image 302 show the same content as shown in Figure 21(A). In addition, in the illustrated example, the cautionary notice section 304 displays the text, "Please take care to avoid encountering bears, taking into account their range of activity."

[0209] Furthermore, the result image 310 shows the individual name image 311, the origin image 312, the occurrence period image 313, the attribute image 314, the size image 315, and the cumulative image 316. The individual name image 311 shows the name of the individual that is the source of the specific target. The information generation unit 210 generates the individual name image 311 based on the "No." of the source of the specific target in the individual management table (see Figure 7).

[0210] In the illustrated example, the source image 312 displays the text, "Detected odor source: Feces." In the illustrated example, the image 313 showing the time of occurrence displays the text, "Time of occurrence of detected odor: March 1, 2026, 6:25 AM." In the illustrated example, attribute image 314 shows the text "Attributes of the detected subject: Male, 5 years old". In the illustrated example, size image 315 shows the text, "Estimated size of detected object: 1.8m, 220kg". In the illustrated example, cumulative image 316 shows the text "Cumulative number of specific bears of the same species in this area: 8" in the population management table (see Figure 9), which represents the number of bears belonging to the "area" corresponding to the location of the target sensor 10.

[0211] The information shown in the individual name image 311, attribute image 314, and size image 315 in result image 310 is the "No.", "Sex", "Age (years)", "Height (m)", and "Weight (kg)" information associated with the individual whose "No." is "1" in the individual management table (see Figure 7). In addition, the information shown in the source image 312 in result image 310 is the information identified from the "source" associated with the "bear" whose "Individual" is "1" in the result management table (see Figure 8). However, the contents shown in the source image 312, attribute image 314, and size image 315 in the result image 310 may be the information of "source," "sex," "age (years)," "height (m)," and "weight (kg)" associated with a "bear" whose "age (years)" is "5" in the species management table (see Figure 5). In addition, the specified target graph may be one in which the species identification condition (see S108 in Figure 15) is satisfied in relation to the "graph" associated with a "bear" whose "age (years)" is "5" in the species management table (see Figure 5).

[0212] Location image 320 shows the user's current location explanation section 321, the sensor location explanation section 322, the source's current location explanation section 323, the same type's past explanation section 324, and the source's future location explanation section 326. Location image 320 also shows the map image 340, the user's current location display section 341, the sensor location display section 342, the source's current location display section 343, the same type's past display section 344, and the source's future location display section 346. The map image 340, user current location display unit 341, sensor location display unit 342, source current location display unit 343, similar past location display unit 344, and source future location display unit 346 display different content from the example shown in Figure 25(E).

[0213] Next, in the fixed notification process (see Figures 15 and 16), the source of the specified target is identified as a bear by the source identification unit 206 (S109), and it is assumed that it has been identified again as an individual that had been identified in the past (S118). In other words, it is assumed that a bear that had been previously detected as an individual by the sensor 10 and the management server 20 has been detected again as the same individual. Furthermore, in the result output process (see Figures 17 and 18), the type area condition is met (Yes in S208), and the position where the target sensor 10 measures the component generated based on the source of the specified target is in the notification recommendation area in relation to the user being judged (Yes in S209). In addition, the source of the specified target is of the recommended type (Yes in S210). In this case, the notification screen 300 shown in Figure 26(B) may be displayed on the user terminal of the user being notified.

[0214] Note that the notification screen 300 shown in Figure 26(B) will be described in a way that differs from the notification screen 300 shown in Figure 26(A), while the same configuration as the notification screen 300 shown in Figure 26(A) will not be described. The notification screen 300 shown in Figure 26(B) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320.

[0215] The date and time image 301, the overview image 302, and the notice section 304 show the same content as shown in Figure 26(A). Furthermore, in the result image 310, the individual name image 311, the origin image 312, the occurrence period image 313, the attribute image 314, the size image 315, and the cumulative image 316 show the same content as shown in Figure 26(A). Furthermore, in location image 320, the user's current location explanation section 321, sensor location explanation section 322, source current location explanation section 323, similar past explanation section 324, source future location explanation section 326, map image 340, user's current location display section 341, sensor location display section 342, source current location display section 343, similar past display section 344, and source future location display section 346 show the same content as shown in Figure 26(A).

[0216] Furthermore, location image 320 shows the source past movement explanation unit 327 and the source past movement display unit 347. The source past movement explanation unit 327 explains the past movement history of the source of the specified object. In the illustrated example, the source past movement explanation unit 327 shows a mark and the text "Past movement history of the detected object". The Source Past Movement Display Unit 347 shows the past movement history of the specified source. In the illustrated example, the Source Past Movement Display Unit 347 uses the same marks as those shown in the Source Past Movement Explanation Unit 327, displayed in the area of ​​the map image 340 corresponding to the past movement history of the specified source. In addition, arrows indicating the direction of movement of the specified source are shown between adjacent marks in the Source Past Movement Display Unit 347. The Information Generation Unit 210 determines the display position of the Source Past Movement Display Unit 347 on the map image 340 based on the movement pattern specified by the Related Identification Unit 207 in a past fixed notification process for the specified source (see S124 in Figure 16). Note that the past fixed notification process refers to the fixed notification process performed for the target source before the fixed notification process that triggered the display of the notification screen 300 shown in Figure 26(B) was executed.

[0217] In this way, the map image 340 displays the sensor location display unit 342 or the current location display unit 343 and the past movement display unit 347 of the source, allowing the user to understand the relationship between the current location and past movement history of the source of a specific target.

[0218] Next, we will explain another example of notification screen 300. In the following, during the fixed notification process (see Figures 15 and 16), the source of the specified target is identified as a bear by the source identification unit 206 (S109), and it is assumed that the bear has been identified again as an individual that had been identified in the past (S118). Furthermore, multiple detection conditions are met (Yes in S123), and the movement pattern of the source of the specified target is identified (S124). In addition, during the result output process (see Figures 17 and 18), the type area condition is met (Yes in S208), and the position where the target sensor 10 measures the component generated based on the source of the specified target is in the notification recommendation area in relation to the user being judged (Yes in S209). Furthermore, the source of the specified target is of the recommended type (Yes in S210). In this case, the notification screen 300 shown in Figure 27(C) may be displayed on the user terminal of the user being notified.

[0219] Note that the notification screen 300 shown in Figure 27(C) will be described in a way that differs from the notification screen 300 shown in Figure 26(A), while the same configuration as the notification screen 300 shown in Figure 26(A) will not be described. The notification screen 300 shown in Figure 27(C) displays a date and time image 301, an overview image 302, a notice notification section 304, a result image 310, and a location image 320.

[0220] The date and time image 301, the overview image 302, and the notice section 304 show the same content as shown in Figure 26(A). Furthermore, in the result image 310, the individual name image 311, the origin image 312, the occurrence period image 313, the attribute image 314, the size image 315, and the cumulative image 316 show the same content as shown in Figure 26(A). Furthermore, in location image 320, the user current location explanation section 321, sensor location explanation section 322, source current location explanation section 323, similar past explanation section 324, source future location explanation section 326, source past movement explanation section 327, map image 340, user current location display section 341, sensor location display section 342, source current location display section 343, similar past display section 344, source future location display section 346, and source past movement display section 347 all show the same content as shown in Figure 26(B).

[0221] Furthermore, location image 320 shows the source movement explanation unit 325 and the source movement display unit 345. The source movement explanation unit 325 explains the current movement history of the source of the specified target. The current movement history refers to the movement history identified in the fixed notification process that triggered the display of the notification screen 300 shown in Figure 27(C) (see S124 in Figure 16). In the illustrated example, the source movement explanation unit 325 displays a mark and the text "Current movement history of the detected object". The source movement display unit 345 shows the current movement history of the specified source. In the illustrated example, the same mark shown in the source movement explanation unit 325 is displayed as the source movement display unit 345 in the area of ​​the map image 340 that corresponds to the current movement history of the specified source. Additionally, an arrow indicating the direction of movement of the specified source is shown between the source movement display unit 345 and the sensor position display unit 342 or the source current location display unit 343. The information generation unit 210 determines the display position of the source movement display unit 345 on the map image 340 based on the movement pattern specified by the related specification unit 207 in the fixed notification process (see S124 in Figure 16).

[0222] In this way, by displaying the source movement display unit 345 and the sensor location display unit 342 or the source current location display unit 343 on the map image 340, it becomes easier for the user to estimate the future actions of the source of a specific target. In particular, in the example shown in Figure 27(C), the map image 340 shows the source movement display unit 345, the sensor location display unit 342 or the source current location display unit 343, and the source past movement display unit 347. In this case, the relationship between the past movement history of the source of a specific target and the current movement history of the source of a specific target makes it easier for the user to estimate the future actions of the source of a specific target.

[0223] Next, we will explain another example of notification screen 300. In the following, during the fixed notification process (see Figures 15 and 16), the source of the specified target is identified as a bear by the source identification unit 206 (S109), and it is assumed that the bear has been identified again as an individual that had been identified in the past (S118). Furthermore, multiple detection conditions are met (Yes in S123), and the movement pattern of the source of the specified target is identified (S124). In addition, during the result output process (see Figures 17 and 18), the type area condition is met (Yes in S208), and the position where the target sensor 10 measures the component generated based on the source of the specified target is in the notification recommendation area in relation to the user being judged (Yes in S209). Furthermore, the source of the specified target is of the recommended type (Yes in S210).

[0224] Furthermore, in the following, it is assumed that the support system 1 detected a bear of the same species as the source of the specified target at the same time as it previously detected the source of the specified target. The same time period could be, for example, a predetermined period from the time of measurement of the component generated from the source of the specified target by the sensor 10. The predetermined period could be any length of time, but for example, it could be 30 seconds. The vicinity of the source of the specified target could be, for example, within a predetermined distance from the location identified for the source of the specified target, or from the location of the sensor 10 that measured the component generated from the source of the specified target. The predetermined distance could be any length of time, but for example, it could be 5m. In this case, the related identification unit 207 identifies that the detected multiple bears were acting together. On the other hand, if the support system 1 did not detect a bear of the same species as the source of the specified target at the same time as it detected the source of the specified target this time, it may notify the support system 1 of the possibility of the presence of a different bear from the source of the specified target, based on past behavioral history, even if the source of the specified target was detected alone. For example, the management server 20 may display the notification screen 300 shown in Figure 27(D) on the user terminal of the user to be notified.

[0225] Note that the notification screen 300 shown in Figure 27(D) will be described in a way that differs from the notification screen 300 shown in Figure 26(A), while the same configuration as the notification screen 300 shown in Figure 26(A) will not be explained. The notification screen 300 shown in Figure 27(D) displays a date and time image 301, an overview image 302, a past multiple notification section 303, a note notification section 304, a result image 310, and a location image 320. Furthermore, individuals that have previously acted together with the source of the specified target, or individuals identified in the related identification section 207 that are different from the source of the specified target, may be referred to as "other individuals" below.

[0226] The date and time image 301, the overview image 302, and the notice section 304 show the same content as shown in Figure 26(A). The past multiple notification unit 303 notifies that when the source of a specific target was detected in the past, it was acting together with other sources of the same type. In the illustrated example, the past multiple notification unit 303 displays the text, "Currently only one bear has been found, but the bear found this time was acting together with other bears last time." The information generation unit 210 generates the past multiple notification unit 303 based on the results of the identification by the related identification unit 207.

[0227] Furthermore, in the result image 310, the individual name image 311, the origin image 312, the occurrence period image 313, the attribute image 314, the size image 315, and the cumulative image 316 show the same content as shown in Figure 26(A). Furthermore, in location image 320, the user current location explanation section 321, sensor location explanation section 322, source current location explanation section 323, similar past explanation section 324, source movement explanation section 325, source future location explanation section 326, source past movement explanation section 327, map image 340, user current location display section 341, sensor location display section 342, source current location display section 343, similar past display section 344, source movement display section 345, source future location display section 346, and source past movement display section 347 show the same content as shown in Figure 27(C).

[0228] Furthermore, the position image 320 shows the other individual movement explanation unit 328 and the other individual movement display unit 348. The other individual movement explanation unit 328 explains the past movement history of other individuals. In the illustrated example, the other individual movement explanation unit 328 shows a mark and the text "Past movement history of other individuals that were acting together". The Other Individual Movement Display Unit 348 shows the movement history of other individuals when they have acted together with the source of the specified target in the past. In the illustrated example, the Other Individual Movement Display Unit 348 uses the same marks as those shown in the Other Individual Movement Explanation Unit 328, and is displayed in the area of ​​the map image 340 that corresponds to the movement history of other individuals when they have acted together with the source of the specified target in the past. In addition, arrows indicating the direction of movement of other individuals are shown between adjacent marks in the Other Individual Movement Display Unit 348. The Information Generation Unit 210 determines the display position of the Other Individual Movement Display Unit 348 on the map image 340 based on the movement pattern identified by the Related Identification Unit 207 in a fixed notification process performed on the other individual in the past (see S124 in Figure 16).

[0229] In this way, when multiple past notifications 303 are displayed on the notification screen 300, even if the source of a specific target is detected alone, the user will understand that there is a possibility that other individuals may be present along with the source of the specific target. Furthermore, when the other individual movement display unit 348 is displayed, it becomes easier for the user to estimate not only the source of the specific target, but also the future actions of other individuals if they are present.

[0230] Next, we will explain another example of notification screen 300. In the following, we assume that in the fixed notification process (see Figures 15 and 16), the source of the specified target is identified as a bear by the source identification unit 206 (S109), and that it has been identified again as an individual that had been identified in the past (S118). Furthermore, we assume that the multiple detection conditions are met (Yes in S123), and that the movement pattern of the source of the specified target is identified (S124). In addition, in the result output process (see Figures 17 and 18), the type area condition is not met (No in S208), and that the source of the specified target is of the target type (Yes in S217). Moreover, in this example, we assume that a positional relationship condition (see S218 in Figure 18) is defined regarding the relationship between the current reference position of the source of the specified target and the area from the current location to the place that the user subject to judgment plans to go. More specifically, the positional relationship condition is that the distance between the current reference position of the source of the specified target and the area corresponding to the range from the current location to the place that the user subject to judgment plans to go is less than or equal to a predetermined distance. Furthermore, the predetermined distance can be any distance, but for example, it may be 1 km. The condition determination unit 209 may determine whether the location relationship condition is met based on the "current location" and "planned location" of the user to be determined in the user management table (see Figure 10). In this case, the "planned location" that the condition determination unit 209 determines may be a "planned location" for a date and time earlier or later than the time when the measurement related to the graph of the specific target was performed. In this example, the location relationship condition is assumed to be met (Yes in S218). In this case, the notification screen 300 shown in Figure 28(E) may be displayed on the user terminal of the notified user.

[0231] Note that the notification screen 300 shown in Figure 28(E) will be described in a way that differs from the notification screen 300 shown in Figure 26(A), while the same configuration as the notification screen 300 shown in Figure 26(A) will not be described. The notification screen 300 shown in Figure 28(E) displays a date and time image 301, an overview image 302, a notice notification unit 304, a result image 310, and a location image 320.

[0232] In the example shown, the overview image 302 displays the text, "Bears have been spotted near your current location and your intended destination." In the illustrated example, the cautionary notice section 304 displays the text, "Please take care to avoid encountering bears, taking into account their range of activity."

[0233] Furthermore, in the result image 310, the individual name image 311, the origin image 312, the occurrence period image 313, the attribute image 314, the size image 315, and the cumulative image 316 show the same content as shown in Figure 26(A). Furthermore, in location image 320, the user current location explanation section 321, sensor location explanation section 322, source current location explanation section 323, similar past explanation section 324, source movement explanation section 325, source future location explanation section 326, source past movement explanation section 327, map image 340, user current location display section 341, sensor location display section 342, source current location display section 343, similar past display section 344, source movement display section 345, source future location display section 346, and source past movement display section 347 show the same content as shown in Figure 27(C). Furthermore, location image 320 shows the user's planned location explanation section 329 and the user's planned location display section 349.

[0234] Furthermore, the location image 320 shows the route reception unit 352. The route reception unit 352 receives a display of a route from the current location of the user being determined to the destination, taking into account the relationship with the source of the specified target. For example, the route reception unit 352 receives a display of a route in which the source of the specified target has not been detected by the sensor 10, or a route in which the source of the specified target has never been identified as existing, either currently or in the past. In the illustrated example, the route reception unit 352 displays the text "Route with no appearance history".

[0235] Here, for example, suppose the user operates the user terminal and selects the route reception unit 352. In this case, the management server 20 displays the route display unit 353, the expanded reception unit 354, and the start reception unit 355 on the notification screen 300, as shown in Figure 28(F).

[0236] The route display unit 353 displays a route from the current location of the user being determined to the planned destination, taking into account the relationship with the source of the specified target. In this disclosure, for example, the route display unit 353 displays a route from the current location of the user being notified to the planned destination where the source of the specified target has not been detected by the sensor 10, or a route where the source of the specified target has never been identified as existing, either currently or in the past. In this disclosure, for example, map information of Japan may be stored in the storage unit 202. The information generation unit 210 generates the route display unit 353 based on the information used to generate the location image 320 and the map information. The magnification reception unit 354 accepts requests for magnified display of the map image 340. When the magnification reception unit 354 is selected, the information provision unit 212 magnifies the map image 340. In this case, the information provision unit 212 also magnifies each image that was displayed on the map image 340, while maintaining their relative positions. The start reception unit 355 accepts the request to start directions along the route displayed on the route display unit 353. When the start reception unit 355 is selected, the information provision unit 212 displays an image on the notification screen 300 showing directions along the route displayed on the route display unit 353. The information generation unit 210 generates an image showing directions along the route displayed on the route display unit 353 based on the information used to generate the location image 320 and the map information.

[0237] Note that in the example shown in Figure 28(F), the result image 310 (see Figure 28(E)) is not displayed on the notification screen 300, but this is not limited to this example. Even if the route reception unit 352 is selected, the result image 310 may be displayed on the notification screen 300.

[0238] Next, we will explain another example of notification screen 300. In the following, it is assumed that in the fixed notification process (see Figures 15 and 16), the source of the specified target has been identified as a human individual by the source identification unit 206 (S109, S118). Furthermore, it is assumed that multiple detection conditions have been met (Yes in S123), and the movement pattern of the source of the specified target has been identified (S124). In this example, it is also assumed that the source of the specified target is a different individual from the "registered individual" related to the user being judged in the user management table (see Figure 10), as defined in the individual relationship conditions for the result output process (see Figures 17 and 18). Additionally, it may be defined as an individual relationship condition that the user being judged is set to absent mode (see Figure 14(A)). In this example, it is assumed that the individual relationship conditions have been met in relation to the user being notified (Yes in S206). In this case, the notification screen 300 shown in Figure 29 may be displayed on the user terminal of the user being notified. In this example, it is assumed that multiple fixed sensors 11 are installed at multiple locations within the home of the user who is to be notified.

[0239] The notification screen 300 shown in Figure 29 displays a date and time image 301, an overview image 302, a notice notification section 304, a result image 310, and a location image 320. In the illustrated example, the overview image 302 shows the text, "An unregistered person has been found in your home." In the illustrated example, the caution notification unit 304 displays the text, "Please be careful as this person may be suspicious." The information generation unit 210 generates an overview image 302 and a notice notification unit 304 so that the content corresponds to when the individual relationship conditions are met.

[0240] The result image 310 displays the individual name image 311, the origin image 312, the time of occurrence image 313, the attribute image 314, and the size image 315. In the illustrated example, the individual name image 311 shows the text "Detected organism name: No. 10003". In the illustrated example, the source image 312 displays the text "Source of detected odor: exhaled breath." In the illustrated example, the occurrence date image 313 shows the text, "Occurrence date of detected odor: March 1, 2026, 15:14". In the illustrated example, attribute image 314 shows the text "Attributes of the detected subject: Male, 45 years old". In the illustrated example, size image 315 displays the text, "Estimated size of detected object: 1.7m, 65kg".

[0241] Furthermore, the contents shown in the source image 312, attribute image 314, and size image 315 in the result image 310 may be the information of "source," "gender," "age (years)," "height (m)," and "weight (kg)" associated with a "human" whose "age (years)" is "45" in the type management table (see Figure 5). In addition, the specific target graph may be one in which the type identification condition (see S108 in Figure 15) is satisfied in relation to the "graph" associated with a "human" whose "age (years)" is "45" in the type management table.

[0242] The location image 320 displays the user's current location explanation section 321, the sensor location explanation section 322, the source's current location explanation section 323, the source's movement explanation section 325, the map image 340, the user's current location display section 341, the sensor location display section 342, the source's current location display section 343, and the source's movement display section 345. Furthermore, location image 320 shows the house explanation unit 333, the house display unit 356, and the warning reception unit 357.

[0243] The housing description section 333 describes the location of the user's residence. In the illustrated example, the housing description section 333 shows a mark and the text "User's Residence". The residential display unit 356 shows the location of the home of the notified user. In the illustrated example, the residential display unit 356, as shown in the residential description unit 333, is shown in the area of ​​the map image 340 that corresponds to the location of the notified user's home. In this disclosure, for example, a user inputs the location information of their home into the consumer terminal 40 by operating a user terminal. The user terminal then transmits the input location information to the management server 20. The information generation unit 210 determines the display position of the residential display unit 356 on the map image 340 based on the location information received by the management server 20. The warning reception unit 357 receives the output of a warning sound. In this disclosure, for example, the sensor 10 may be provided with a speaker (not shown). When the warning reception unit 357 is selected, the management server 20 may output a warning sound from the speaker of the sensor 10 that measured the component generated based on the source of the specified target. Alternatively, the warning sound may be output from the speakers of all sensors 10 in the home of the notified user. Furthermore, in the support system 1, the speaker may be provided separately from the sensor 10.

[0244] In addition, in the notification screen 300 shown in Figure 29, the map image 340 may be a map that includes the site of the notified user's residence. Furthermore, the management server 20 may display the installation locations of each fixed sensor 11 within the notified user's residence within the residence display unit 356, corresponding to rooms or sections.

[0245] Next, we will explain another example of notification screen 300. In the following, during the fixed notification processing (see Figures 15 and 16), the source of the specified target is identified as a bear by the source identification unit 206 (S109), and it is assumed that the individual has been identified again as one that had been identified in the past (S118). Furthermore, multiple detection conditions are met (Yes in S123), and the movement pattern of the source of the specified target is identified (S124). In addition, during the result output processing (see Figures 17 and 18), it is assumed that the source of the specified target is identified as a required individual (Yes in S203). In this case, the notification screen 300 shown in Figure 30(A) may be displayed on the user terminals of all users. Note that the notification screen 300 shown in Figure 30(A) will be described in a way that differs from the notification screen 300 shown in Figure 27(C), while the same configuration as the notification screen 300 shown in Figure 27(C) will not be described.

[0246] The notification screen 300 shown in Figure 30(A) displays a date and time image 301, an overview image 302, a history notification unit 305, a note notification unit 304, a result image 310, and a location image 320. In the illustrated example, the overview image 302 shows the text "A bear has been found in the urban area of ​​○ city, ○ prefecture," which includes information about the region to which the location where the target sensor 10 measured components generated based on the source of a specific target belongs. The history notification unit 305 notifies the history of the source of the specific target. In the illustrated example, the history notification unit 305 displays the text, "This bear has attacked a person before." The information generation unit 210 generates the history notification unit 305 based on the "history" of the source of the specific target in the individual management table (see Figure 7). In the illustrated example, the cautionary notice section 304 displays the text, "Please take care to avoid encountering bears, taking into account their range of activity."

[0247] The result image 310 displays the individual name image 311, the origin image 312, the time of occurrence image 313, the attribute image 314, the size image 315, and the cumulative image 316. In the illustrated example, the individual name image 311 shows the text "Detected organism name: No. 4". In the illustrated example, the source image 312 displays the text, "Detected odor source: Feces." In the illustrated example, the image 313 showing the time of occurrence displays the text, "Time of occurrence of detected odor: March 2, 2026, 6:40 AM." In the illustrated example, attribute image 314 shows the text "Attributes of the detected subject: Male, 6 years old". In the illustrated example, the size image 315 displays the text, "Estimated size of detected object: 2.0m, 250kg". In the illustrated example, cumulative image 316 shows the text, "Cumulative number of this species in this area: 3 individuals."

[0248] The information shown in the individual name image 311, attribute image 314, and size image 315 in result image 310 is the "No.", "Sex", "Age (years)", "Height (m)", and "Weight (kg)" information associated with the individual whose "No." is "4" in the individual management table (see Figure 7). In addition, the information shown in the source image 312 in result image 310 is the information identified from the "source" associated with the "bear" whose "Individual" is "4" in the result management table (see Figure 8). However, the contents shown in the source image 312, attribute image 314, and size image 315 in the result image 310 may be the information of "source," "sex," "age (years)," "height (m)," and "weight (kg)" associated with a "bear" whose "age (years)" is "6" in the species management table (see Figure 5). In addition, the specified target graph may be one in which the species identification condition (see S108 in Figure 15) is satisfied in relation to the "graph" associated with a "bear" whose "age (years)" is "6" in the species management table.

[0249] The location image 320 displays the user's current location explanation section 321, the sensor location explanation section 322, the source's current location explanation section 323, the same type's past explanation section 324, the source's movement explanation section 325, the source's future location explanation section 326, the source's past movement explanation section 327, the map image 340, the user's current location display section 341, the sensor location display section 342, the source's current location display section 343, the same type's past display section 344, the source's movement display section 345, the source's future location display section 346, and the source's past movement display section 347. Furthermore, location image 320 shows the history explanation section 334 and the history display section 358.

[0250] The history description unit 334 describes the history of the source of the specific target. In the illustrated example, the history description unit 334 shows the history of the actions of the source of the specific target and the text "History of the detected entity: Attacks a person (Year Month Day Hour)" which includes the date and time of the action. The information generation unit 210 generates the history description unit 334 based on the "history" of the source of the specific target in the individual management table (see Figure 7). The history display unit 358 displays the location related to the history of the source of the specific target. In the illustrated example, the same mark shown in the history explanation unit 334 is displayed as the history display unit 358 in the area of ​​the map image 340 that corresponds to the location of the action recorded as part of the history of the source of the specific target. The information generation unit 210 determines the display position of the history display unit 358 on the map image 340 based on the "history" of the source of the specific target in the individual management table (see Figure 7).

[0251] Next, we will explain another example of notification screen 300. In the following, during the fixed notification process (see Figures 15 and 16), the source of the specified target is identified as a human by the source identification unit 206 (S109), and is identified again as an individual that had been identified in the past (S118). Furthermore, multiple detection conditions are met (Yes in S123), and the movement pattern of the source of the specified target is identified (S124). In addition, during the result output process (see Figures 17 and 18), the source of the specified target is identified as an essential individual (Yes in S203). In this example, it is assumed that the support system 1 detected other individuals of the same species in the vicinity at the same time as when it previously detected the source of the specified target, but did not detect other individuals in the vicinity at the same time when it detected the source of the specified target this time. In this case, the notification screen 300 shown in Figure 30(B) may be displayed on the user terminals of all users. Note that the notification screen 300 shown in Figure 30(B) will be described in a way that differs from the notification screen 300 shown in Figure 26(A), while the same configuration as the notification screen 300 shown in Figure 26(A) will not be explained.

[0252] The notification screen 300 shown in Figure 30(B) displays a date and time image 301, an overview image 302, a history notification unit 305, a past multiple notification unit 303, a notice notification unit 304, a result image 310, and a location image 320. In the illustrated example, the overview image 302 shows the text "A person of interest has been found in a residential area of ​​○ city, ○ prefecture," which includes information about the region to which the location where the target sensor 10 measured components generated based on the source of the specific target belongs. In the illustrated example, the history notification unit 305 displays the text, "This person under attention is a person whose past dangerous behavior has been recorded." The information generation unit 210 generates the history notification unit 305 based on the "history" of the source of the specific target in the individual management table (see Figure 7). In the illustrated example, the past multiple notification section 303 displays the text: "Currently, only one person has been found, but the person found this time was acting together with other persons under concern last time." In the illustrated example, the caution notice section 304 displays the text, "Please take precautions to avoid becoming a victim, taking into account the range of the person being cautioned."

[0253] The result image 310 displays the individual name image 311, the origin image 312, the time of occurrence image 313, the attribute image 314, and the size image 315. In the illustrated example, the individual name image 311 displays the text "Detected organism name: No. 10001". In the illustrated example, the source image 312 displays the text "Source of detected odor: exhaled breath." In the illustrated example, the image 313 showing the time of occurrence displays the text, "Time of occurrence of detected odor: March 2, 2026, 16:29". In the illustrated example, attribute image 314 shows the text "Attributes of the detected subject: Male, 35 years old". In the illustrated example, size image 315 displays the text, "Estimated size of detected object: 1.7m, 65kg".

[0254] The information shown in the individual name image 311, attribute image 314, and size image 315 in result image 310 is the "No.", "Sex", "Age (years)", "Height (m)", and "Weight (kg)" information associated with the individual whose "No." is "10001" in the individual management table (see Figure 7). In addition, the information shown in the source image 312 in result image 310 is the information identified from the "source" associated with the "human" whose "individual" is "10001" in the result management table (see Figure 8). However, the contents shown in the source image 312, attribute image 314, and size image 315 in the result image 310 may be the information of "source," "gender," "age (years)," "height (m)," and "weight (kg)" associated with a "human" whose "age (years)" is "35" in the type management table (see Figure 5). In addition, the specific target graph may be one in which the type identification condition (see S108 in Figure 15) is satisfied in relation to the "graph" associated with a "human" whose "age (years)" is "35" in the type management table.

[0255] The location image 320 displays the user's current location explanation section 321, the sensor location explanation section 322, the source's current location explanation section 323, the source's movement explanation section 325, the source's future location explanation section 326, the source's past movement explanation section 327, the movement of other individuals explanation section 328, the history explanation section 334, the map image 340, the user's current location display section 341, the sensor location display section 342, the source's current location display section 343, the source's movement display section 345, the source's future location display section 346, the source's past movement display section 347, the movement of other individuals display section 348, and the history display section 358. In the illustrated example, the history description section 334 displays the text, "History of the detected object: Dangerous behavior (Year / Month / Day / Time)".

[0256] Next, we will explain another example of notification screen 300. In the following, during the fixed notification process (see Figures 15 and 16), the source of the specified target is identified as a fox by the source identification unit 206 (S109), and is identified again as an individual that had been identified in the past (S118). Furthermore, multiple detection conditions are met (Yes in S123), and the movement pattern of the source of the specified target is identified (S124). In addition, during the result output process (see Figures 17 and 18), this source of the specified target is identified as an essential individual (Yes in S203). Here, the source of the specific target is, for example, the sensor 10 in question, which is the sensor 10 in which "C" is indicated in the "Area" of the user management table (see Figure 10) in relation to any of the users being judged, and the type area condition is not met in relation to any of the users being judged (No in S208). Also, the fox, which is the source of the specific target, is a recommended type (see Figure 6) and a required type, but not a target type (No in S217). On the other hand, as mentioned above, the source of the specific target is a required individual. In this case, the notification screen 300 shown in Figure 31(C) may be displayed on the user terminals of all users. Note that the notification screen 300 shown in Figure 31(C) will be described in a way that differs from the notification screen 300 shown in Figure 26(A), while the same configuration as the notification screen 300 shown in Figure 26(A) will not be described.

[0257] The notification screen 300 shown in Figure 30(C) displays a date and time image 301, an overview image 302, a history notification unit 305, a note notification unit 304, a result image 310, and a location image 320. In the illustrated example, the overview image 302 shows the text "A fox has been found in the suburbs of ○ city, ○ prefecture," which includes information about the region to which the location where the target sensor 10 measured the component generated based on the specific target source belongs. In the illustrated example, the history notification unit 305 displays the text, "This fox has previously harmed a person." In the illustrated example, the cautionary notice section 304 displays the text, "Please take care to avoid encountering foxes, taking into account their range of movement."

[0258] The result image 310 displays the individual name image 311, the origin image 312, the time of occurrence image 313, the attribute image 314, the size image 315, and the cumulative image 316. In the illustrated example, the individual name image 311 displays the text "Detected organism name: No. 1001". In the illustrated example, the source image 312 displays the text, "Source of detected odor: Urine." In the illustrated example, the image 313 showing the time of occurrence displays the text, "Time of occurrence of detected odor: March 2, 2026, 16:33". In the illustrated example, attribute image 314 shows the text "Attributes of the detected object: Male, 3 years old". In the illustrated example, size image 315 shows the text, "Estimated size of detected object: 0.55m, 5.2kg". In the illustrated example, cumulative image 316 displays the text, "Cumulative number of this species in this area: 2 individuals."

[0259] The information shown in the individual name image 311, attribute image 314, and size image 315 in result image 310 is the "No.", "Sex", "Age (years)", "Height (m)", and "Weight (kg)" information associated with the individual whose "No." is "1001" in the individual management table (see Figure 7). In addition, the information shown in the origin image 312 in result image 310 is the information identified from the "origin" associated with the "fox" whose "individual" is "1001" in the result management table (see Figure 8). However, the contents shown in the source image 312, attribute image 314, and size image 315 in the result image 310 may be the information of "source," "gender," "age (years)," "height (m)," and "weight (kg)" associated with a "fox" whose "age (years)" is "3" in the type management table (see Figure 5). In addition, the specific target graph may be one in which the type identification condition (see S108 in Figure 15) is satisfied in relation to the "graph" associated with a "fox" whose "age (years)" is "3" in the type management table.

[0260] The location image 320 displays the user's current location explanation section 321, the sensor location explanation section 322, the source's current location explanation section 323, the same type's past explanation section 324, the source's movement explanation section 325, the source's future location explanation section 326, the source's past movement explanation section 327, the history explanation section 334, the map image 340, the user's current location display section 341, the sensor location display section 342, the source's current location display section 343, the same type's past display section 344, the source's movement display section 345, the source's future location display section 346, the source's past movement display section 347, and the history display section 358. In the illustrated example, the history description section 334 displays the text: "History of the detected object: Caused harm to a person (Year / Month / Day / Time)".

[0261] In the notification screen 300 shown in Figures 30(A), 30(B), and 31(C), the map image 340 displays a map appropriate to the user being notified. Furthermore, the management server 20 may change the display range of the map image 340 displayed on the user terminal for each user, depending on the user's current location. Also, in the notification screen 300 shown in Figures 30(A), 30(B), and 31(C), the user's current location display unit 341, sensor location display unit 342, source current location display unit 343, similar past display unit 344, source movement display unit 345, source future location display unit 346, source past movement display unit 347, and history display unit 358 are displayed in positions appropriate to the user being notified. Additionally, in the notification screen 300 shown in Figure 30(B), the other individual movement display unit 348 is displayed in a position appropriate to the user being notified.

[0262] Next, we will describe the process by which the management server 20 notifies the user of information regarding the source from which the components were measured by the portable sensor 12. Figures 32 to 34 are flowcharts showing the flow of the mobile notification process. The mobile notification process is the process by which the management server 20 notifies the user of information regarding the source from which the component was measured by the mobile sensor 12. In this disclosure, for example, when result information transmitted from the mobile sensor 12 is received by the transmission / reception unit 201 of the management server 20, the mobile notification process is started. In this disclosure, the mobile notification process is executed for each mobile sensor 12. The mobile sensor 12 that is the target of the mobile notification process that is currently being executed, in other words, the mobile sensor 12 that transmitted the result information that triggered the start of the mobile notification process, may be referred to as the target mobile sensor 12 below. In a broader sense, the target mobile sensor 12 can also be considered as the target sensor 10. In other words, the target sensor 10 is the fixed sensor 11 that transmitted the result information that triggered the start of the fixed notification process (see Figures 15 and 16), or the mobile sensor 12 that transmitted the result information that triggered the start of the mobile notification process.

[0263] Steps 401 to 424 of the mobile notification processing are the same as steps 101 to 124 of the fixed notification processing, except that the sensor 10 that measures the components generated based on the source of the specific target, and the source of the result information, are both the mobile sensor 12. In addition, during mobile notification processing, there are cases where the source of the target has already been identified by the source identification unit 206 (Yes in S403) and the conditions for individual identification are met (Yes in S404). Even in this case, the related identification unit 207 identifies the content related to the individual identified by the source identification unit 206 for the measurement related to the identified target graph (S419). This is because the mobile sensor 12 is carried on the mobile body M and performs measurements while moving, so the result information related to the measurement at the latest measurement position of the mobile sensor 12 contributes to improving the accuracy of the identification of content related to the individual by the related identification unit 207.

[0264] If the multiple detection conditions are not met (No in S423), or after step 424, the process proceeds to the next step. The related identification unit 207 identifies the location of the source of the component that was generated based on the source of the specified target and measured by the target mobile sensor 12, based on the measurement results from the target mobile sensor 12 (S425). Furthermore, if the target mobile sensor 12 has measured the component generated based on the source of the specified target at multiple locations as it moves, the related identification unit 207 identifies the location of the source based on the measurement results from each of these multiple locations.

[0265] Furthermore, if the type identification condition is not met (No in S408), the comparison unit 205 determines whether the specified target graph satisfies the significant change condition (S426). The significant change condition is a condition used by the comparison unit 205 to determine whether the measurement value by the target mobile sensor 12 has changed significantly. In this disclosure, for example, the significant change condition may be defined as the resistance value of the target mobile sensor 12 in the specified target graph changing by a predetermined value or more over a predetermined period of time compared to the resistance value measured under a so-called noise environment where there is no source of the specific target identified by the source identification unit 206. The predetermined period may be any time, for example, 2 seconds. The predetermined value may also be any value.

[0266] If the specified target graph satisfies the significant change condition (Yes in S426), the source identification unit 206 determines whether the specified target graph satisfies the candidate identification condition (S427). The candidate identification condition is a condition used by the source identification unit 206 to determine whether or not to identify a candidate for the type of source of the specified target. In this disclosure, for example, the degree of similarity between the specified target graph and the comparison target graph may be defined as satisfying a predetermined standard. For example, a predetermined standard may be that the degree of agreement between the specified target graph and the comparison target graph is 80% or higher.

[0267] If the specified target graph does not meet the candidate identification conditions (No in S427), the source identification unit 206 identifies a significant change in the measured value from the target portable sensor 12 (S428). If the specified target graph satisfies the candidate identification conditions (Yes in S427), the source identification unit 206 identifies a significant change in the measured values ​​from the target portable sensor 12. The source identification unit 206 also extracts all comparison target graphs that satisfy the candidate identification conditions in relation to the specified target graph. The source identification unit 206 then identifies each of the extracted comparison target graphs as a candidate for the type of source of the specified target (S429).

[0268] Furthermore, the source identification unit 206 may identify candidate types of the source of the identified object based on the results of machine learning. The management server 20 may input result information related to the mobile sensor 12 as training data into the learning model. The training data may include, for the mobile sensor 12, a time series of resistance values ​​in the measurement, measurement time, measurement period, environmental information such as temperature, humidity, and atmospheric pressure, and training information of the type of source associated with the measurement. Based on the training data, the management server 20 may generate a trained model that estimates candidate types of sources when a specific target graph is input. The trained model may include, for example, a time series classification model, a convolutional neural network, a recurrent neural network, a transformer, or a model including a gradient boosting decision tree. The trained model may output the likelihood, probability, or score for each of the multiple types in the input data that the source of the specific target is of that type. The source identification unit 206 may then identify types whose likelihood, etc., is above a predetermined threshold as candidate types of sources for the specific target, based on the output of the trained model. Furthermore, the source identification unit 206 may identify types as candidates in order from the highest likelihood, up to a predetermined rank. The source identification unit 206 may also store the likelihood output by the trained model as the confidence level of the candidates in the result management table. Furthermore, the source identification unit 206 may identify candidate types of the source of the target based on the results of machine learning, using the same method as described above for identifying the type of source of the target.

[0269] If the significant change condition is not met (No in S426), the process proceeds to the next step after step 428 or after step 429. The condition determination unit 209 determines whether the target portable sensor 12 satisfies the measurement environment conditions (S430). The measurement environment conditions are conditions used by the condition determination unit 209 to determine whether the location where the target portable sensor 12 measures is suitable for identifying the source. In this disclosure, for example, the measurement environment condition may be that the time during which the resistance value of the target portable sensor 12 is less than or equal to a predetermined value is less than or equal to a predetermined period. The predetermined value may be any value. The predetermined period may be any time, but for example, it may be 5 seconds.

[0270] If the measurement environment conditions are not met (No in S430), the condition determination unit 209 determines whether the target portable sensor 12 satisfies the high-precision conditions (S431). The high-precision conditions are defined in relation to the location where the target portable sensor 12 measures, in relation to the position where the target portable sensor 12 has already measured. The high-precision conditions are used by the condition determination unit 209 to determine whether there is a location that improves the accuracy of the measurement by the target portable sensor 12 of the components generated from a specific source. In this disclosure, for example, the high-precision condition may be that there is a measurement location where a resistance value higher than the resistance value in the most recent measurement of the target portable sensor 12 is obtained. If the high-precision condition is met (Yes in S431), the related identification unit 207 identifies a region where the measurement accuracy is higher than that of the most recent measurement position of the target mobile sensor 12, based on the relationship between the measurement position of the target mobile sensor 12 and the measurement result (S432).

[0271] Here, we will explain the method by which the related identification unit 207 identifies regions where the measurement accuracy is improved. Figure 35 shows an example of a method by which the related identification unit 207 identifies regions where measurement accuracy is improved. As shown in Figure 35(A), the target mobile sensor 12 is assumed to have taken measurements at position P1 in the same space S as the source of the specific target. Position P1 is the central position in the left-right direction within space S as shown in the figure.

[0272] Next, as shown in Figure 35(B), the target mobile sensor 12 moves from position P1 in the direction of arrow A1 in the figure, and a measurement is taken at position P2. Then, as a result of this measurement, the resistance value of the target mobile sensor 12 is higher at position P1 than at position P2. In this case, the condition determination unit 209 determines that the target mobile sensor 12 satisfies the high-precision condition.

[0273] Furthermore, the related identification unit 207 identifies regions where measurement accuracy is improved. As shown in Figure 35(C), when space S is divided into left space S1, which is the region to the left of the center of space S in the figure, and right space S2, which is the region to the right of the center of space S in the figure, the related identification unit 207 identifies the region of space S1 as a region where measurement accuracy is improved. More specifically, the related identification unit 207 identifies the region moved from position P1 in the direction of arrow A2 in the figure as a region where measurement accuracy is higher compared to measurement at position P2. Furthermore, in the mobile notification processing, the related identification unit 207 identifies the location of the source of the component that was generated based on the source of the identified target and measured by the target mobile sensor 12, based on the relationship between the measurement result by the target mobile sensor 12 and the position of the target mobile sensor 12 or the position of the mobile body M at the time the measurement was performed (S425). In the example shown in Figure 35(C), the related identification unit 207 identifies the location of the source as an area belonging to the range of the left space S1, based on the relationship between position P1 and the measurement result at position P1, and the relationship between position P2 and the measurement result at position P2.

[0274] Furthermore, the related specific unit 207 may execute the processing in step 432 based on the results of machine learning. The management server 20 may generate a learning model that estimates the region in which measurement accuracy is improved based on the relationship between the measurement location of the portable sensor 12 and the measurement result. The learning data input to the learning model may include location information of multiple locations where the portable sensor 12 performed measurements, a time series of resistance values ​​at each location, the measurement time, environmental information at the time of measurement, and correct information on the location of the source based on the measurement. Examples of correct information include the location of the source in an experimental environment where the location of the source is known, and the location of the source estimated by other measurement means. The management server 20 may generate a trained model based on the training data, which estimates the location of the source or the probability distribution of the source location from the input set of measurement locations and measurement results. Examples of trained models include regression models and neural networks that integrate and process location information and time series data. The trained model may also output the location of the source as two-dimensional or three-dimensional coordinates. The trained model may also output the estimation uncertainty or confidence level along with the estimation result of the source location. The related identification unit 207 may input multiple measurement locations, including the most recent measurement location of the target mobile sensor 12, and the measurement results at each measurement location, into the trained model. The trained model may then output information indicating coordinates or regions that can be associated with a region on the map image 340 as an estimation result of the source location. The related identification unit 207 may identify an extended region based on the estimated location of the source output by the trained model as a region where measurement accuracy can be improved. Alternatively, the related identification unit 207 may extract a portion with a high probability from the probability distribution output by the trained model and identify the extracted portion as a region where measurement accuracy can be improved.

[0275] Returning to the explanation of the mobile notification process, after step 405, after step 425, if the measurement environment conditions are met (Yes in S430), if the high-precision conditions are not met (No in S431), or after step 432, the process proceeds to the next step. The management server 20 updates the contents of the individual management table (see Figure 7) and the result management table (see Figure 8) according to the results of each process in the mobile notification process being executed. In addition, the counting unit 208 of the management server 20 counts the individual, including the identified individual, if an individual is identified in the mobile notification process being executed, and updates the contents of the individual count management table (see Figure 9) according to the counting result (S433). Note that the counting unit 208 does not need to count the individual or update the individual count management table if no individual is identified in the mobile notification process being executed.

[0276] The management server 20 performs administrator output processing (S434). As will be explained in detail later, administrator output processing is the process by which the management server 20 outputs information regarding the results of the mobile notification processing to the administrator terminal 30. The management server 20 performs result output processing (see Figures 17 and 18) (S435).

[0277] Furthermore, if sensor 10 is a portable sensor 12, the transmitting / receiving unit 201 of the management server 20 acquires multiple result information related to measurements taken at multiple locations where the target portable sensor 12 is located. Here, the portable sensor 12 performs measurements while moving with the mobile body M. Therefore, even when the portable sensor 12 measures components generated from the same source, variations in measurement results may occur depending on the measurement location. Therefore, the graph generation unit 204 of the management server 20 may integrate the result information related to measurements taken by a single portable sensor 12 at multiple locations to generate a single specific target graph. The graph generation unit 204 may, for example, generate a graph that links the result information for each measurement location in chronological order, or a graph that integrates the result information for each measurement location by averaging or weighting. In addition, the graph generation unit 204 of the management server 20 may generate a specific target graph that has undergone normalization processing to correct the measurement results according to the distance traveled by the portable sensor 12, the measurement location, the measurement time interval, etc. In this case, the location-dependent variability inherent in the measurement results at multiple locations by the portable sensor 12 is reduced, making it easier to compare and identify the type or individual source based on the measurement results.

[0278] Furthermore, the comparison unit 205 may select the comparison target graph used for comparison with a specific target graph, taking into account that it is a mobile measurement by the portable sensor 12. For example, the graph generation unit 204 may generate a comparison graph based on measurements using the fixed sensor 11 and a comparison graph based on measurements at multiple locations using the portable sensor 12. Each generated comparison graph may be stored separately in a type management table (see Figure 5) or the like. The comparison unit 205 may then select and compare the comparison graph for the fixed sensor 11 if the target sensor 10 is the fixed sensor 11, or select and compare the comparison graph for the portable sensor 12 if the target sensor 10 is the portable sensor 12. In this case, it becomes possible to make a comparison that takes into account the effects caused by the differences between the 10 types of sensors being targeted.

[0279] Furthermore, even if the comparison unit 205 uses the same comparison graph regardless of whether the target sensor 10 is a fixed sensor 11 or a portable sensor 12, the measurement results from the portable sensor 12 may use comparison conditions corresponding to multiple measurement positions. For example, the comparison unit 205 may calculate the degree of agreement with the comparison target graph for each of the specific target graphs generated from multiple result information related to measurements taken by the portable sensor 12 at multiple different locations. The source identification unit 206 may then identify the type or individual source of the specific target if the type identification conditions or individual identification conditions are met for a predetermined number or proportion of the multiple specific target graphs. Furthermore, the management server 20 may identify the type or individual based not on comparing the measurement results for each measurement location individually, but on whether the change in measurement results accompanying the movement of the measurement location matches a predetermined fluctuation pattern for the source being compared. In this case, it becomes possible to make comparisons based on the assumption that the measurement results from the mobile sensor 12 will vary depending on the location.

[0280] Furthermore, the determination criteria used by the management server 20 to identify the type or individual source based on the measurement results from the portable sensor 12 may differ from those used when identifying the source based on the measurement results from the fixed sensor 11. Examples of determination criteria include type identification conditions and individual identification conditions. For example, if the target sensor 10 is a fixed sensor 11, the management server 20 may identify the type or individual source based on whether or not the determination conditions are met for a single measurement result. On the other hand, if the target sensor 10 is a portable sensor 12, the management server 20 may identify the type or individual source if the determination conditions are met for a certain percentage or more of the measurement results from multiple locations. Furthermore, the management server 20 may identify the type or individual source based on whether or not the temporal progression or trends of multiple measurement results match the trends of the source being compared. In this case, the type or individual source is identified based on the fluctuations in measurement results associated with mobile measurements by the portable sensor 12.

[0281] Figure 36 is a flowchart illustrating the flow of administrator output processing. The condition determination unit 209 of the management server 20 determines whether the result of the mobile notification processing satisfies the administrator notification conditions (S501). The administrator notification conditions are conditions used by the condition determination unit 209 to determine whether or not to notify the administrator of information regarding the result of the mobile notification processing. The administrator notification conditions are set up to notify the administrator only when the administrator needs to know the result of the mobile notification processing. In this disclosure, for example, the administrator notification conditions may be defined as the satisfaction of at least one of the following: significant change condition (see S426 in Figure 34), candidate identification condition (see S427 in Figure 34), high accuracy condition (see S431 in Figure 34), and result change condition. The result change condition is a condition used by the condition determination unit 209 to determine whether or not the measurement result of the target mobile sensor 12 has changed from the previous measurement result. The previous measurement result is the result of the measurement that triggered the previous mobile notification processing of the target mobile sensor 12. In this disclosure, for example, the result change condition may be defined as the resistance value of the target mobile sensor 12 changing by a predetermined value or more over a predetermined period of time compared to the resistance value in the previous measurement. The predetermined period may be any period, but for example, it may be 10 seconds. The predetermined value may also be any value.

[0282] If the administrator notification conditions are not met (No in S501), the administrator output process terminates. In this case, information regarding the results of the mobile notification process is not output to the administrator terminal 30 during the administrator output process. If the administrator notification conditions are met (Yes in S501), the condition determination unit 209 determines whether the specific target graph has met the significant change conditions in the mobile notification process that is currently being executed (S502). If the significant change condition is met (Yes in S502), the condition determination unit 209 determines whether the specific target graph in the currently executing mobile notification process satisfies the candidate identification condition (S503).

[0283] If the candidate identification conditions are met (Yes in S503), the target determination unit 211 determines that the information indicating the candidate identified as the type of source of the specified target in the mobile notification processing will be the target of notification to the administrator (S504). If the candidate identification conditions are not met (No in S503), or after step 504, proceed to the next step. The target determination unit 211 determines that information indicating a significant change in the resistance value of the target portable sensor 12 will be notified to the administrator (S505).

[0284] If the significant change condition is not met (No in S502), or after step 505, proceed to the next step. The condition determination unit 209 determines whether the target mobile sensor 12 has met the high-precision condition in the mobile notification processing (S506). If the high-precision condition is met (Yes in S506), the target determination unit 211 determines that the information indicating the area identified in step 432 of the mobile notification processing will be the target of notification to the administrator (S507).

[0285] If the high-precision condition is not met (No in S506), or after step 507, proceed to the next step. The condition determination unit 209 determines whether the measurement result of the target portable sensor 12 satisfies the result change condition (S508). If the result change condition is met (Yes in S508), the condition determination unit 209 determines whether the measurement result from the wind direction and speed meter 60 satisfies the wind change condition (S509). The wind change condition is a condition used by the condition determination unit 209 to determine whether the factor that satisfies the result change condition is due to a change in wind conditions. In this disclosure, the wind change condition may be that a predetermined change has occurred in the measurement result of the wind direction and speed meter 60 located closest to the location where the measurement of the target mobile sensor 12 that triggered the start of the mobile notification process was performed. Examples of predetermined changes include a change in wind direction of 60 degrees or more, or a change in wind speed of a predetermined value or more. The predetermined value may be any value, but for example, it may be 3 m / s. The timing of the measurement of the wind direction and speed meter 60 that is subject to the determination of whether or not the wind change condition is met is a predetermined period from the time the measurement of the target mobile sensor 12 that triggered the start of the mobile notification process was performed. The predetermined period can be any length of time, but for example, it may be 30 seconds. The condition determination unit 209 performs the processing in step 509 based on the "installation location," "result," etc., of the sensing means management table (see Figure 4). The anemometer 60 located closest to the location where the measurement of the target mobile sensor 12 that triggered the start of the mobile notification process was taken may be referred to below as the nearby anemometer 60.

[0286] If the wind change condition is not met (No in S509), the target determination unit 211 determines that information indicating that the measurement result of the target portable sensor 12 has changed from the previous measurement result will be the subject of notification to the administrator (S510). If the wind change condition is met (Yes in S509), the target determination unit 211 determines that the information indicating the wind change will be the subject of notification to the administrator (S511).

[0287] The information generation unit 210 generates information that has been determined to be the target of notification to the administrator in the administrator output processing, and this information is then output to the administrator terminal 30 by the information generation unit 210, thereby notifying the administrator (S512). In addition, the administrator terminal 30 to which information is notified during the administrator output processing may be any administrator terminal 30 in the support system 1, or it may be limited to the administrator terminal 30 of a predetermined administrator. Furthermore, if the administrator is carrying the target portable sensor 12 as a mobile device M, the information may be notified during the administrator output processing only to the administrator terminal 30 of that administrator.

[0288] Furthermore, if the type identification condition is met in the mobile notification processing (see Figures 32 to 34) (Yes in S408), the administrator output processing may be set so that neither the significant change condition nor the candidate identification condition is met (No in S502, No in S503). Also, if the individual that is the source of the specific target is identified in the mobile notification processing (S418), the significant change condition, the candidate identification condition, and the high accuracy condition may be set so that none of them are met (No in S502, No in S503, No in S506).

[0289] Next, we will describe an example of information that is notified to the administrator as a result of administrator output processing. In the following, we assume that the type identification condition is not met in the mobile notification processing (No in S408 of Figure 32). Also, in the administrator output processing (see Figure 36), we assume that the significant change condition is met (Yes in S502), but the candidate identification condition, high accuracy condition, and result change condition are not met (No in S503, No in S506, No in S508). In this case, the information provision unit 212 of the management server 20 may display the administrator notification screen 370 shown in Figure 37(A) on the administrator terminal 30.

[0290] The administrator notification screen 370 is a screen for notifying the administrator of information regarding the results of the mobile notification processing. The administrator notification screen 370 displays the mobile result image 371, the promotion image 372, and the mobile location image 380. The mobile result image 371 shows information corresponding to the conditions met in the administrator output processing, as it represents the measurement results from the target mobile sensor 12, which were identified in the mobile notification processing. In the illustrated example, the mobile result image 371 shows the text, "A significant change in sensor value was detected." The prompt image 372 displays information to prompt the administrator, corresponding to the conditions met during the administrator output processing. In the illustrated example, the prompt image 372 displays the text, "To identify the type and individual of the detected object, please continue the measurement near the most recent measurement location." The information generation unit 210 generates a mobile result image 371 and a promotion image 372 so that the content corresponds to the fulfillment of the significant change condition.

[0291] The mobile location image 380 is an image showing the location of the target mobile sensor 12. The mobile location image 380 shows the mobile object description section 381, the nearest description section 382, ​​the map image 390, the mobile object display section 391, and the nearest display section 392. The mobile object description unit 381 describes the current location of the mobile object M. In the illustrated example, the mobile object description unit 381 shows a mark and the text "Current location of the mobile object". The most recent description section 382 describes the position of the target mobile sensor 12 in the most recent measurement. The most recent measurement is the measurement that triggered the mobile notification processing (see Figures 32 to 34). In the illustrated example, the most recent description section 382 shows a mark and the text "Most recent measurement position".

[0292] Map image 390 shows a map. In the illustrated example, map image 390 shows a map of an area that includes the location of the most recent measurement of the target mobile sensor 12 and the current location of the mobile object M. The mobile object display unit 391 shows the current location of the mobile object M. If the mobile object M is an administrator, the current location of the mobile object M may be determined from the location information transmitted from the administrator terminal 30 to the management server 20. In the illustrated example, the same mark shown in the mobile object description unit 381 is displayed as the mobile object display unit 391 in the area of ​​the map image 390 corresponding to the current location of the mobile object M. The information generation unit 210 determines the display position of the mobile object display unit 391 on the map image 390 based on the location information of the mobile object M. The most recent display unit 392 shows the most recent measurement position of the target mobile sensor 12. In the illustrated example, the most recent display unit 392 is the same mark as shown in the most recent explanation unit 382, ​​and is shown in the area of ​​the map image 390 that corresponds to the most recent measurement position of the target mobile sensor 12. The information generation unit 210 determines the display position of the most recent display unit 392 on the map image 390 based on the "position" in the result management table (see Figure 8) related to the most recent measurement by the target mobile sensor 12.

[0293] Next, we will describe other examples of information that is notified to the administrator as a result of administrator output processing. In the following, we assume that the type identification condition is not met in the mobile notification processing (No in S408 of Figure 32). Also, in the administrator output processing (see Figure 36), we assume that the significant change condition and the candidate identification condition are met (Yes in S502 and S503), but the high accuracy condition and the result change condition are not met (No in S506 and S508). In this case, the information provision unit 212 of the management server 20 may display the administrator notification screen 370 shown in Figure 37(B) on the administrator terminal 30.

[0294] Note that the administrator notification screen 370 shown in Figure 37(B) has a different configuration from the administrator notification screen 370 shown in Figure 37(A), and the same configuration as the administrator notification screen 370 shown in Figure 37(A) will not be explained. The administrator notification screen 370 shown in Figure 37(B) displays a mobile result image 371, a promotion image 372, a candidate notification image 373, and a mobile location image 380.

[0295] In the illustrated example, the mobile result image 371 shows the text, "A significant change in sensor values ​​was detected, and a candidate for the detected object was identified." In the illustrated example, the facilitator image 372 displays the text, "To identify the species and individual of the detected object, please continue the measurement near the most recent measurement location." The candidate notification image 373 notifies the source identification unit 206 of the identified candidates for the type of source of the specified target during mobile notification processing. In the illustrated example, the candidate notification image 373 shows the text "Candidates for detected object: bear, wild boar, deer". The information generation unit 210 generates a mobile result image 371, a promotion image 372, and a candidate notification image 373, so that the content corresponds to whether the significant change condition and the candidate identification condition have been met.

[0296] In the mobile location image 380 shown in Figure 37(B), the mobile object description section 381, the most recent description section 382, ​​the map image 390, the mobile object display section 391, and the most recent display section 392 show the same content as shown in Figure 37(A).

[0297] Next, we will describe other examples of information that is notified to the administrator as a result of administrator output processing. In the following, we assume that the type identification condition is not met in the mobile notification processing (No in S408 of Figure 32). Also, in the administrator output processing (see Figure 36), we assume that the significant change condition and the result change condition are not met (No in S502, No in S508), and the high accuracy condition is met (Yes in S506). In this case, the information provision unit 212 of the management server 20 may display the administrator notification screen ...

Claims

1. Equipped with one or more processors, The one or more processors described above are: The results of measurements taken by a measuring device for components generated from a source or substances released from that source are obtained for measurements taken by the same measuring device at multiple locations where the measuring device is located differently. The system acquires type result information regarding the results of the measurement by the measuring device for components generated from a predetermined type of source or from a substance released from such source. In accordance with the result information and type result information relating to the measurement at the plurality of locations by the one measuring device, the device outputs information relating to the type identified for the source that is the subject of the measurement relating to the result information. Information processing system.

2. The first measuring device is mounted on a moving body, The one or more processors described above are: Information about the mobile body is obtained regarding the results of measurement of the components generated from the mobile body or the substances released from the mobile body by the measuring device. The information processing system according to claim 1, which outputs information relating to the type identified for the source that is the target of the measurement relating to the result information, in accordance with the result information relating to the measurement at the plurality of locations, the type result information and the moving body information.

3. The one or more processors described above are: The result information relating to the results of the measurement of the component generated from the source using the one measuring device is newly acquired. The information processing system according to claim 1, which outputs change information relating to a change in the positional relationship between the measuring device and the source, in accordance with the change in the result identified from the newly acquired result information relating to the measuring device from the result identified from the result information relating to the measuring device that was already acquired.

4. The one or more processors described above are: Wind information regarding the wind conditions in the same space as the aforementioned measuring device is acquired. The information processing system according to claim 3, wherein if a condition is met regarding the relationship between the change in the result identified from the newly acquired result information relating to the one measuring device and the wind information, the output of the change information is restricted and information regarding the wind conditions is output.

5. The time required for the measurement related to the result information used to identify the aforementioned type is the first hour. The one or more processors described above are: When the source of the aforementioned type of specific target does not exist, non-existence result information is obtained regarding the measurement results by the measuring device. Short-time result information is obtained regarding the measurement results for a time shorter than the first time using the one measuring device. The information processing system according to claim 1, which outputs information regarding the fulfillment of a condition defined for the relationship between the non-existent result information and the short-time result information.

6. The time required for the measurement related to the result information used to identify the aforementioned type is the first hour. The one or more processors described above are: Short-time result information is obtained regarding the measurement results for a time shorter than the first time using the one measuring device. The information processing system according to claim 1, which outputs information regarding the identified candidate types of the source that is the target of the measurement related to the short-time result information.

7. The one or more processors described above are: When the measurement is performed by the aforementioned measuring device, positional information relating to the position of the aforementioned measuring device is acquired for the measurements at the aforementioned multiple locations. The information processing system according to claim 1, which outputs information regarding a region identified for the location of the source, in accordance with the result information and location information related to the measurements at the plurality of locations.

8. The one or more processors described above are: When the measurement is performed by the aforementioned measuring device, position information relating to the position of the aforementioned measuring device is acquired. If the specified conditions for identifying the type of the source are not met, the information processing system according to claim 1 outputs additional information regarding the measurement location necessary for such identification to the one measuring device, in accordance with the result information and the location information.

9. The one or more processors described above are: Based on the aforementioned source, time information relating to the period from when the component is generated in the same space as the measuring device until the measurement of the component by the measuring device is obtained for multiple periods with different durations. Obtain the result information for the measurement corresponding to each of the periods identified from the multiple period information obtained, The information processing system according to claim 1, which outputs information about the time when a component was generated in the same space as the first measuring device based on the source, in accordance with the period information corresponding to other result information that satisfies conditions defined in relation to the result information relating to the source of the target whose type is specified.

10. The aforementioned source, which is a specific target of the aforementioned type, is an animal. The one or more processors described above are: Based on the aforementioned source, time information relating to the period from when the component is generated in the same space as the measuring device until the measurement of the component by the measuring device is obtained for multiple periods with different durations. Obtain the result information for the measurement corresponding to each of the periods identified from the multiple period information obtained, The information processing system according to claim 1, wherein when the source, which is a specific target of the aforementioned type, is identified as an animal of the predetermined type, the system outputs information relating to a region identified as the current location of the source, in accordance with the period information corresponding to other result information for which conditions defined in relation to the result information relating to the source are met.

11. The aforementioned source of the subject whose species is identified is an animal. The one or more processors described above are: Based on the aforementioned source, time information relating to the period from when the component is generated in the same space as the measuring device until the measurement of the component by the measuring device is obtained for multiple periods with different durations. Obtain the result information for the measurement corresponding to each of the periods identified from the multiple period information obtained, The aforementioned period information and result information are obtained for multiple measurements targeting components generated from the aforementioned sources, each of which is of a different type for each measurement. First result information is obtained, which is the result information related to the measurement of the component generated from the first source by the first measuring device. The second result information, which is the result information related to the measurement by the first measuring device of a component generated from a second source of a different type from the first source, is obtained. The information processing system according to claim 1, which, when the source of the first source and the source of the second source are identified as the same individual, outputs information regarding the movement path identified for that individual in accordance with the first result information and the second result information.

12. A step of obtaining result information regarding the measurement results of a measuring device for components generated from a source or substances released from said source, for measurements taken by the same measuring device at multiple locations where the measuring device is located differently. A step of obtaining type result information regarding the measurement results by the measuring device of components generated from a predetermined type of source or from a substance released from said source, A step of outputting information relating to the type identified for the source that is the target of the measurement, in accordance with the result information and type result information relating to the measurement at the plurality of locations by the one measuring device, A method having

13. A program for causing a computer to function as an information processing system according to any one of claims 1 to 11.

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