Information providing device, information providing method, and program

Abstract

To provide an information providing device, an information providing method, and a program that provide a sufficient amount of information to improve a satisfaction degree of a user in a technology of providing information specified to a region.SOLUTION: An information providing device 10 comprises: a submission information acquisition unit 11; a sensor information acquisition unit 12; a section information generation unit 13; and an output unit 14. The submission information acquisition unit 11 acquires a submission content submitted on the Internet and submission information including position information. The sensor information acquisition unit 12 acquires sensor information which includes data generated by a sensor and installation position information on the sensor. The section information generation unit 13 generates section information associated with each of a plurality of observation sections on the basis of the submission information and the sensor information. The output unit 14 outputs the section information.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an information providing device, an information providing method, and a program. [Background technology]

[0002] Patent Document 1 discloses an information sharing system that publishes information specific to a region. The information sharing system publishes information registered by information providers and information generated by sensors.

[0003] Non-patent documents 1 to 3 provide a detailed explanation of the heat index, which is related to the risk of heat stroke. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2013-214905 A [Non-patent literature]

[0005] [Non-Patent Document 1] Ministry of the Environment, "Heat Stroke Prevention Information Site - Detailed Explanation of Heat Index (WBGT) -", [online], [Retrieved December 4, 2020], Internet<URL: https: / / www.wbgt.env.go.jp / doc_observation.php> [Non-Patent Document 2] Ministry of the Environment, "Detailed explanation of heat stroke prevention information site - Learn about the heat index (WBGT) -" [online], [Retrieved December 4, 2020], Internet<URL:https: / / www.wbgt.env.go.jp / wbgt_lp.php> [Non-Patent Document 3] Document submitted by the Occupational Health and Safety Division, Labor Standards Bureau, Ministry of Health, Labor and Welfare, "Prevent heat stroke," [online], [Retrieved December 4, 2020], Internet<URL:https: / / www.wbgt.env.go.jp / pdf / ic_rma / 2301 / mat05_3.pdf> Summary of the Invention [Problem to be solved by the invention]

[0006] In the case of the "means for publishing information registered by information providers" disclosed in Patent Document 1, if the frequency of registration is low, the amount of information provided to users will be small, resulting in low user satisfaction. In the technology for providing information specialized to a region, it may be difficult to increase the frequency of registration, since the registrants of information are limited to those related to that region.

[0007] In addition, in the case of the "means for disclosing information generated by sensors" disclosed in Patent Document 1, if the number of sensors installed is small, the places where information is disclosed will be limited, resulting in low user satisfaction. It may be difficult to install sensors to cover every place in an area, taking into account costs and maintenance after installation.

[0008] An object of the present invention is to provide a sufficient amount of information and increase user satisfaction in a technology for providing information specific to a region. [Means for solving the problem]

[0009] According to the present invention, A posting information acquiring means for acquiring posting information including posted content and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for generating zone information for each of a plurality of observation zones based on the posted information and the sensor information; an output means for outputting the partition information; An information providing device is provided, comprising:

[0010] Further, according to the present invention, The computer Acquire posted content and posted information including location information posted on the Internet, Acquire sensor information including data generated by a sensor and installation location information of the sensor; generating zone information for each of a plurality of observation zones based on the posted information and the sensor information; An information providing method is provided that outputs the partition information.

[0011] Further, according to the present invention, Computer, A posted information acquisition means for acquiring posted information including posted contents and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for generating zone information for each of a plurality of observation zones based on the posted information and the sensor information; an output means for outputting the partition information; A program is provided to function as a

[0012] Further, according to the present invention, a zone information generating means for generating zone information for each of a plurality of observation zones based on posted content posted on the Internet, the posted content including location information, and sensor information including data generated by a sensor and installation location information of the sensor; an output means for outputting an image in which the block information is mapped on a map; An information providing device is provided, comprising: Effect of the Invention

[0013] According to the present invention, in a technique for providing information specific to a region, a sufficient amount of information can be provided, thereby increasing user satisfaction. [Brief description of the drawings]

[0014] [Figure 1] FIG. 2 is a diagram illustrating an example of a hardware configuration of an information providing device according to the present embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of a functional block diagram of the information providing device according to the present embodiment. [Diagram 3] FIG. 2 is a diagram for explaining an example of an observation section in the present embodiment. [Figure 4] 5 is a flowchart showing an example of a process flow of the information providing device of the present embodiment. [Diagram 5] 10A and 10B are diagrams for explaining the effects of the information providing device according to the present embodiment; [Figure 6] 10A and 10B are diagrams for explaining the effects of the information providing device according to the present embodiment; [Figure 7] FIG. 2 is a diagram illustrating an example of a functional block diagram of the information providing device according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same components are given the same reference numerals and the description will be omitted as appropriate.

[0016] <First embodiment> "overview" The information providing device of this embodiment acquires "content posted on the Internet" and "data generated by sensors installed in the area" as information related to the area. The information providing device then combines the acquired posted content and sensor data to generate new information and outputs it to the user.

[0017] When the acquired information is simply output to the user as is, the amount of information that can be output is limited to the amount of acquired information. In contrast, when multiple types of information are acquired and new information is generated by combining them, it is possible to output information that exceeds the amount of acquired information. For example, by predicting the situation of a location that cannot be detected by a sensor based on data from surrounding sensors and posted content, the information of the location that cannot be detected by the sensor can be supplemented. As a result, it is possible to disclose information of every place within the area. In addition, by predicting the situation of a location that cannot be detected by a sensor based on multiple pieces of information such as data from surrounding sensors and posted content, more reliable information can be supplemented. As a result, it is possible to provide information that is excellent not only in quantity but also in quality, thereby increasing user satisfaction.

[0018] "Function Configuration" Next, the configuration of the information providing device will be described in detail. First, an example of the hardware configuration of the information providing device will be described. FIG. 1 is a diagram showing an example of the hardware configuration of the information providing device. Each functional unit of the information providing device is realized by any combination of hardware and software, centering on a CPU (Central Processing Unit) of any computer, memory, programs loaded into the memory, a storage unit such as a hard disk for storing the programs (programs stored beforehand at the stage of shipping the device, as well as programs downloaded from storage media such as CDs (Compact Discs) or servers on the Internet, can be stored), and a network connection interface. Those skilled in the art will understand that there are various variations in the methods and devices for realizing the above.

[0019] As shown in FIG. 1, the information providing device has a processor 1A, a memory 2A, an input / output interface 3A, a peripheral circuit 4A, and a bus 5A. The peripheral circuit 4A includes various modules. The information providing device does not have to have the peripheral circuit 4A. The information providing device may be composed of multiple devices that are physically and / or logically separated, or may be composed of a single device that is physically and logically integrated. In the former case, each of the multiple devices that make up each device can have the above hardware configuration.

[0020] The bus 5A is a data transmission path for the processor 1A, memory 2A, peripheral circuit 4A, and input / output interface 3A to transmit and receive data to each other. The processor 1A is an arithmetic processing device such as a CPU or a GPU (Graphics Processing Unit). The memory 2A is a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The input / output interface 3A includes an interface for acquiring information from an input device, an external device, an external server, an external sensor, etc., and an interface for outputting information to an output device, an external device, an external server, etc. Examples of the input device include a keyboard, a mouse, a microphone, etc. Examples of the output device include a display, a speaker, a printer, a mailer, etc. The processor 1A can issue commands to each module and perform calculations based on the results of those calculations.

[0021] 2 shows an example of a functional block diagram of the information providing device 10. As shown in the figure, the information providing device 10 includes a post information acquiring unit 11, a sensor information acquiring unit 12, a section information generating unit 13, and an output unit 14.

[0022] The posted information acquisition unit 11 acquires posted information including posted content and location information posted on the Internet. The posted information may further include information indicating the posting timing (date and time, etc.).

[0023] The posted content is text data, images (still images, moving images), etc. The posted information acquisition unit 11 acquires posted content posted on, for example, social media, SNS (social networking service), or homepages of entities related to the region.

[0024] The location information is information indicating the location of the poster (a location where the poster has stayed at present or in the past) or a destination to which the poster is heading. The posted information acquisition unit 11 may acquire location information indicating the posted location included in metadata (such as a geotag) of the posted content, for example. The posted information acquisition unit 11 may also acquire location information indicating the shooting location included in metadata of an image acquired as posted content. The posted information acquisition unit 11 may also specify the shooting location of an image based on the background of the image acquired as posted content, and acquire the specified shooting location as location information. The posted information acquisition unit 11 may also extract location-related words (such as addresses, place names, and facility names) from text data acquired as posted content, and acquire the extracted location-related words as location information. The posted information acquisition unit 11 can infer whether the location information acquired by the above method indicates the current location, a past location, or a destination to which the poster is heading, by analyzing the wording of the text data acquired as posted content.

[0025] The sensor information acquisition unit 12 acquires sensor information including data generated by the sensor and information on the installation location of the sensor. The sensor information may further include information indicating the timing (date and time, etc.) at which the data was generated. The sensor may be installed in the area to be observed, or may be provided in a terminal (smartphone, smart watch, tablet terminal, portable game console, mobile phone, car navigation system, etc.) owned by the user.

[0026] The sensor includes at least one of an image sensor that generates an image, a temperature sensor that generates temperature data, a humidity sensor that generates humidity data, an illuminance sensor that generates illuminance data, a wind speed sensor that generates wind speed data, a monitoring sensor that generates data indicating the operation status of an air conditioner, a sensor that is installed in a car or on a road and generates probe information (traffic volume and speed), a sensor that acquires route information set in a car navigation system, a sensor (beacon or GPS sensor) that generates position information and acceleration information of people, and a microphone that acquires environmental sounds and sounds based on people's traffic. Examples of cameras that are sensors include visible light cameras, infrared cameras, and stereo cameras. The camera may acquire two-dimensional image information, or may acquire depth information in addition to two-dimensional image information. The sensor continues to generate data. The image generated by the image sensor may be a moving image, or may be multiple still images repeatedly generated at a predetermined time interval.

[0027] The sensor information acquisition unit 12 acquires data generated by a sensor installed in the area to be observed. The sensor information acquisition unit 12 may acquire the data generated by the sensor in real time processing via any communication network. The sensor information acquisition unit 12 may also acquire the data generated by the sensor in batch processing by any method. Which method to adopt can be determined according to the contents of the block information (information generated by the block information generation unit 13) provided to the user. Examples of the area to be observed include, but are not limited to, one ward, city, town, one shopping street, one theme park, one station, one street, one large-scale commercial facility, one airport, one platform, one leisure facility, one sports facility, one stadium, etc.

[0028] The zone information generating unit 13 generates zone information for each of the multiple observation zones based on the posted information and the sensor information.

[0029] First, a description will be given of a plurality of observation sections. In this embodiment, a plurality of observation sections are set within an area to be observed. There are various ways of setting the observation sections, and one example will be described below.

[0030] - Observation area setting example 1 - In this example, as shown in FIG. 3, the area S to be observed is divided into a plurality of sections (sections divided vertically and horizontally by dotted lines). All sections may be the observation section A, or a part of the plurality of sections extracted by any method may be the observation section A. There is no particular limitation on the method of dividing the area S to be observed into a plurality of sections, and any method may be adopted. The smaller the size of the section, the more fine-grained information can be provided. On the other hand, the smaller the size of the section, the greater the processing load on the computer becomes, and there are also problems such as the need for more sensors to make the section information of the plurality of sections different from each other. The size of the section can be determined based on the required performance, the status of available resources, and the like.

[0031] - Observation area setting example 2 - In this example, an observation section is set for each facility that exists in the area to be observed. That is, all or part of the facilities that exist in the area to be observed are set as the observation section. Examples of facilities include stores, stations, cities, streets, large-scale commercial facilities, airports, terminal stations, platforms, leisure facilities, sports facilities, stadiums, etc.

[0032] Next, the section information will be described. The section information is information indicating the status of each observation section. Examples of the status of each observation section indicated by the section information include, but are not limited to, the congestion status of each observation section, a prediction result of the future congestion status of each observation section, and the risk of heat stroke in each observation section.

[0033] The area information for each observation area is generated based on at least one of the following: "data for each observation area generated by the sensor," "data for other observation areas related to each observation area generated by the sensor," "posted information related to the area being observed," and "other information."

[0034] "Data for each observation section generated by a sensor" refers to data generated by a camera installed to photograph each observation section, data generated by a sensor installed in each observation section, etc.

[0035] "Data of other observation sections related to each observation section generated by a sensor" is data generated by a camera installed to photograph the inside of other observation sections related to each observation section, data generated by a sensor installed in other observation sections related to each observation section, etc. "Other observation sections related to each observation section" is an observation section that has a predetermined positional relationship with each observation section, for example, an observation section adjacent to each observation section, or an observation section whose distance to each observation section (shortest distance, etc.) is less than a threshold value, etc.

[0036] "Posted information related to the region being observed" is posted information that includes location information related to the region being observed. The location information related to the region being observed is location information that indicates a location within the region being observed.

[0037] The "other information" is information other than the above-mentioned examples related to the area to be observed. The details will be described in the following embodiment.

[0038] The section information generating unit 13 combines the above multiple data to generate section information such as the congestion status of each observation section, the prediction result of the future congestion status of each observation section, the risk of heat stroke in each observation section, etc. The details will be described in the following embodiment.

[0039] The output unit 14 outputs the section information for each of the multiple observation sections generated by the section information generation unit 13.

[0040] As an example, the output unit 14 can output an image in which the section information is mapped on a map. For example, the output unit 14 may display the color of each observation section A in a color corresponding to the status of each observation section A (congestion status, future congestion status, risk of heat stroke, etc.) in an image as shown in FIG. 3. In addition, the output unit 14 may display marks, letters, numbers, etc. corresponding to the status of each observation section A in association with each observation section A in the image as shown in FIG. 3. In addition, when the output unit 14 receives a user operation (operation of aligning the cursor position to a specific observation section, operation of aligning the cursor position to a specific observation section and clicking, operation of touching a specific observation section, etc.) of designating one observation section A in the image as shown in FIG. 3, the output unit 14 may display information (text data, image data, etc.) indicating the status of the designated observation section A on the screen in response to the user operation.

[0041] Additionally, the output unit 14 may present the section information to a user who has been registered in advance. Examples of the present invention include, but are not limited to, sending the section information by email, displaying the section information on a page after logging in to an app or web page, or sending a push notification of an app.

[0042] Next, an example of the flow of processing by the information providing device 10 will be described with reference to the flowchart of FIG.

[0043] The posted information acquisition unit 11 acquires posted information including posted content posted on the Internet and location information (S10). The sensor information acquisition unit 12 acquires sensor information including data generated by a sensor and installation location information of the sensor (S11). S10 and S11 may be performed in parallel or sequentially in any order.

[0044] The section information generating unit 13 generates section information for each of the multiple observation sections based on the posted information acquired in S10 and the sensor information acquired in S11 (S12). Then, the output unit 14 outputs the section information generated in S12 (S13).

[0045] S10 to S13 may be performed in real time or in batch. When the congestion status and the risk of heat stroke in each observation section are generated as section information and output, real time processing is preferable. When the predicted result of the future congestion status in each observation section is generated as section information and output, real time processing or batch processing may be used.

[0046] "Action and effect" The information providing device of this embodiment acquires "content posted on the Internet" and "data generated by sensors installed in the area" as information related to the area. The information providing device then combines the acquired posted content and sensor data to generate new information and outputs it to the user.

[0047] When the acquired information is simply output to the user as is, the amount of information that can be output is limited to the amount of acquired information. In contrast, when multiple types of information are acquired and new information is generated by combining them, it is possible to output information in excess of the amount of acquired information. For example, by predicting the situation of a location that cannot be detected by a sensor based on data from surrounding sensors and posted information, the information of the location that cannot be detected by the sensor can be supplemented. As a result, it is possible to disclose information of every location within the area. In addition, by predicting the situation of a location that cannot be detected by a sensor based on multiple pieces of information such as data from surrounding sensors and posted information, more reliable information can be supplemented. As a result, it is possible to provide information that is excellent not only in quantity but also in quality, thereby increasing user satisfaction.

[0048] <Second embodiment> The information providing device 10 of this embodiment sets a plurality of observation sections A as shown in Fig. 3 in the above-mentioned observation section setting example 1, and generates and outputs section information indicating the congestion state of each observation section A. This will be described in detail below.

[0049] The sensor information acquisition unit 12 acquires an image generated by a camera as sensor information.

[0050] The posted information acquisition unit 11 acquires posted information indicating at least one of the poster's location and the poster's destination.

[0051] The section information generating unit 13 generates section information indicating the congestion state in each of the multiple observation sections based on the image analysis result and the posted information. The process of generating the section information will be described in detail below.

[0052] The section information generating unit 13 can estimate the number of people in the observation section based on the following calculation formula.

[0053] (Number of people in the first observation section at time t) = (Number of people in the first observation section at time t-1) + (Number of people entering the first observation section at the time when time t-1 changes to time t) - (Number of people leaving the first observation section at the time when time t-1 changes to time t)

[0054] The section information generating unit 13 may input the calculated number of people as section information indicating the congestion state of each observation section to the output unit 14. Then, the output unit 14 may output the calculated number of people in each observation section as section information indicating the congestion state of each observation section.

[0055] Alternatively, the section information generating unit 13 may convert the calculated number of people into another index according to a predetermined rule, and input the converted index to the output unit 14 as section information indicating the congestion state of each observation section. Then, the output unit 14 may output the calculated index of each observation section as section information indicating the congestion state of each observation section. Examples of the conversion rules include, but are not limited to, "less than X1 number of people: empty, number of people X1 or more but less than X2: slightly crowded, number of people X2 or more but less than X3: crowded, number of people X3 or more: very crowded".

[0056] Here, a calculation example of each element of the above calculation formula will be described.

[0057] -Example of calculation of the number of people entering and leaving each observation area- The block information generating unit 13 calculates the number of people entering and leaving each observation block based on the sensor information and the posted information, and then integrates these to calculate the number of people entering and leaving each observation block.

[0058] First, the process of calculating the number of people entering and leaving based on the sensor information will be described. The block information generating unit 13 analyzes the image of the observation target area acquired by the sensor information acquiring unit 12, detects people in the image, and calculates the movement direction and movement speed of each detected person. Then, based on the calculation result, the block information generating unit 13 calculates the number of people entering and leaving each observation block at each timing.

[0059] In addition, sensors such as beacons may be installed, and the direction and speed of movement of each user may be calculated from the time and order of passing the beacon installation position, and the number of people entering and leaving each observation section may be calculated based on the calculation results. Also, the number of mobile phones connected to the base station and the signal strength may be obtained, and the number of people in each observation section may be calculated based on that information. Also, the trend of the number of people entering and leaving between observation sections at that time and period may be used from past survey results such as traffic volume surveys. Furthermore, images generated by cameras installed on mobile terminals (smartphones, mobile phones, etc.) carried by people in the observation section may be obtained by any means, and the images may be analyzed to detect people, calculate the direction and speed of movement, and calculate the number of people entering and leaving each observation section. In this case, images obtained from multiple users may be combined (by complementing blind spots) and used.

[0060] Next, the process of calculation based on the posted information will be described. First, the block information generating unit 13 estimates the poster's future movement route based on the posted information. For example, the block information generating unit 13 searches for a route from the poster's position to the destination based on the poster's position included in the posted information and the destination to which the poster is heading, and estimates the result as the poster's future movement route. The route search can be realized by using an existing method. Note that in tourist spots, shopping streets, etc., the movement trajectories of people therein may be patterned. In this case, the block information generating unit 13 may estimate the poster's future movement route based on this patterned movement trajectory of people. Specifically, the block information generating unit 13 estimates that the poster will move along this movement trajectory.

[0061] Then, based on the poster's location, the time, and the estimated movement route, the section information generating unit 13 identifies the observation section in which the poster is present at each timing. Based on the identification result, the section information generating unit 13 calculates the number of people entering and leaving each observation section at each timing.

[0062] The section information generating unit 13 may estimate the number of people accompanying the poster based on the posted content of the poster. For example, the number of people accompanying the poster may be estimated by analyzing the wording of text data acquired as the posted content or by analyzing the posted image. The section information generating unit 13 may add the number of people accompanying the poster to the calculation of the number of people entering and leaving each observation section based on the movement trajectory of the poster. That is, when it is estimated that the first poster moves from the first observation section to the second observation section at the first timing and the number of people accompanying the first poster is estimated to be two, the number of people moving from the first observation section to the second observation section at the first timing is counted up by "3" based on the information of the first poster.

[0063] Next, we will explain the process of calculating the number of people entering and leaving each observation area by integrating the number of people entering and leaving each observation area calculated based on sensor information with the number of people entering and leaving each observation area calculated based on posted information.

[0064] The block information generating unit 13 may calculate the number of people entering each observation block by adding up the number of people entering each observation block calculated based on the sensor information and the posted information. Alternatively, the block information generating unit 13 may calculate the number of people entering each observation block by adding up values ​​obtained by multiplying the number of people entering each observation block calculated based on the sensor information and the posted information by a predetermined weighting factor. The block information generating unit 13 may then calculate the number of people leaving each observation block in the same manner as above. Note that the values ​​calculated using the above calculation method may not match the actual number of people entering and leaving each observation block. However, it is possible to obtain a value that allows a rough estimate of the congestion situation to be made with sufficient accuracy.

[0065] - Calculation example of the number of people in each observation area at time 0 - When estimating the number of people in each observation section based on the above calculation formula, it is necessary to estimate the number of people in each observation section at time t0. A specific example will be explained below. Note that, here, it is sufficient to obtain a value that allows a rough estimate of the congestion situation with sufficient accuracy, and the calculated value does not necessarily have to be an accurate value.

[0066] -Calculation example 1- The zone information generating unit 13 can analyze the image captured in each observation zone at time 0 to detect people and count the number of people detected, thereby calculating the number of people in each observation zone at time 0. This example is applicable to observation zones where cameras are installed.

[0067] -Calculation example 2- Even if a camera is installed, there are cases where an image is not generated that includes the entire observation area. In such cases, the accuracy of the result obtained in the above calculation example 1 is insufficient. Therefore, the area information generating unit 13 calculates a more accurate value by integrating the value obtained in the above calculation example 1 with the value calculated based on the posted information.

[0068] Here, the process of calculating the number of people in each observation section at time 0 based on the posted information will be described. First, the section information generating unit 13 identifies the poster's location at time 0 based on the posted information. By using the metadata of the posted content, the poster's location can be identified with finer granularity, but when identifying the poster's location based on the content of the posted content (e.g., "Shibuya now," "X Park now"), the granularity becomes larger. In order to use information from more posters, the section information generating unit 13 identifies the poster's location in a relatively wide area (such as a place name or facility name). In other words, the section information generating unit 13 identifies which area the poster is in. Each area includes multiple observation sections. Through this process, the section information generating unit 13 can calculate the congestion status (number of people staying) in each area.

[0069] The section information generating unit 13 may estimate the number of accompanying people of the poster based on the posted content of the poster. For example, the number of accompanying people may be estimated by analyzing the wording of text data acquired as the posted content or by analyzing the posted image. The section information generating unit 13 may add the number of accompanying people to the calculation of the number of people staying in each area at each timing.

[0070] Alternatively, the section information generating unit 13 may analyze the posted image and calculate the number of people appearing in the image. The section information generating unit 13 may further include the number of people appearing in the image when calculating the number of visitors to each area at each timing.

[0071] After calculating the congestion status (number of visitors) of each area in the above process, the zone information generating unit 13 calculates the congestion status (number of visitors) of each of the multiple observation zones included in each area based on the calculated congestion status (number of visitors) of each area. For example, the zone information generating unit 13 may equally allocate the number of visitors in each area to the multiple observation zones included in each area. Alternatively, the number of visitors in each area may be proportionally allocated to the multiple observation zones included in each area based on an allocation coefficient set for each of the multiple observation zones.

[0072] Next, we will explain the process of calculating the number of people in each observation section at time 0 by combining the number of people in each observation section at time 0 calculated based on sensor information and the number of people in each observation section at time 0 calculated based on posted information.

[0073] The zone information generation unit 13 may calculate the number of people in each observation zone at time 0, for example, by adding up the number of people in each observation zone at time 0 calculated based on the sensor information and the posted information. Alternatively, the zone information generation unit 13 may calculate the number of people in each observation zone at time 0 by adding up a value obtained by multiplying the number of people in each observation zone at time 0 calculated based on the sensor information and the posted information by a predetermined weighting coefficient.

[0074] -Calculation example 3- The block information generating unit 13 calculates a more accurate value by integrating the value obtained in the above calculation example 1 with a value calculated based on other information.

[0075] Other information is the trend of the number of people (by time period) present in a given area, which is obtained in advance by any means. The data is generated by any statistical means and provided to the information providing device 10. Each area includes multiple observation sections.

[0076] Then, the section information generating unit 13 calculates the number of visitors in each of the multiple observation sections by equally allocating the number of visitors in each area at time 0 to the multiple observation sections included in each area. Alternatively, the section information generating unit 13 may calculate the number of visitors in each of the multiple observation sections by proportionally allocating the number of visitors in each area in each time period to the multiple observation sections included in each area based on the allocation coefficient set for each of the multiple observation sections.

[0077] Next, we will explain the process of calculating the number of people in each observation area at time 0 by combining the number of people in each observation area at time 0 calculated based on sensor information and the number of people in each observation area at time 0 calculated based on the above-mentioned other information.

[0078] The zone information generation unit 13 may calculate the number of people in each observation zone at time 0, for example, by adding up the number of people in each observation zone at time 0 calculated based on the sensor information and the posted information. Alternatively, the zone information generation unit 13 may calculate the number of people in each observation zone at time 0 by adding up a value obtained by multiplying the number of people in each observation zone at time 0 calculated based on the sensor information and the posted information by a predetermined weighting coefficient.

[0079] -Calculation example 4- The block information generating unit 13 calculates a more accurate value by integrating the value obtained in the above calculation example 1 with a value calculated based on other information.

[0080] Other information is the number of people (for each time period) present in a given area, predicted based on the event information for that day. Based on past performance, the data is generated and provided to the information providing device 10. Each area includes multiple observation sections.

[0081] Then, the section information generating unit 13 calculates the number of visitors in each of the multiple observation sections by equally allocating the number of visitors in each area at time 0 to the multiple observation sections included in each area. Alternatively, the section information generating unit 13 may calculate the number of visitors in each of the multiple observation sections by proportionally allocating the number of visitors in each area in each time period to the multiple observation sections included in each area based on the allocation coefficient set for each of the multiple observation sections.

[0082] Next, we will explain the process of calculating the number of people in each observation area at time 0 by combining the number of people in each observation area at time 0 calculated based on sensor information and the number of people in each observation area at time 0 calculated based on the above-mentioned other information.

[0083] The zone information generation unit 13 may calculate the number of people in each observation zone at time 0, for example, by adding up the number of people in each observation zone at time 0 calculated based on the sensor information and the posted information. Alternatively, the zone information generation unit 13 may calculate the number of people in each observation zone at time 0 by adding up a value obtained by multiplying the number of people in each observation zone at time 0 calculated based on the sensor information and the posted information by a predetermined weighting coefficient.

[0084] -Calculation example 5- The section information generation unit 13 calculates more accurate values ​​by combining the value obtained in calculation example 1 above with the number of people in each observation section at time 0 calculated based on the posted information, and the number of people in each observation section at time 0 calculated based on other information.

[0085] The process of calculating the number of people in each observation block at time 0 based on the posted information is as described in Calculation Example 2. The process of calculating the number of people in each observation block at time 0 based on other information is as described in Calculation Examples 3 and 4.

[0086] Next, we will explain the process of calculating the number of people in each observation section at time 0 by combining the number of people in each observation section at time 0 calculated based on sensor information, the number of people in each observation section at time 0 calculated based on posted information, and the number of people in each observation section at time 0 calculated based on other information.

[0087] The zone information generation unit 13 may calculate the number of people in each observation zone at time 0, for example, by adding up the number of people in each observation zone at time 0 calculated based on the sensor information, posted information, and other information. Alternatively, the zone information generation unit 13 may calculate the number of people in each observation zone at time 0 by adding up a value obtained by multiplying the number of people in each observation zone at time 0 calculated based on the sensor information, posted information, and other information by a predetermined weighting coefficient.

[0088] -Calculation example 6- This example is applied to observation sections where no cameras are installed. In this example, the number of people in each observation section at time 0 is calculated based on images of other observation sections related to each observation section. For example, the section information generation unit 13 may use the number of people in other observation sections at time 0 calculated based on images of the other observation sections (the value calculated in calculation example 1) as the number of people in each observation section at time 0. Alternatively, the section information generation unit 13 may use a value obtained by multiplying the number of people in other observation sections at time 0 calculated based on images of the other observation sections (the value calculated in calculation example 1) by a predetermined coefficient as the number of people in each observation section at time 0.

[0089] Furthermore, the section information generating unit 13 may correct the value obtained by the above method in the same manner as in the above calculation examples 2 to 5, and use the corrected value as the number of people in each observation section at time 0.

[0090] Other configurations of the information providing device 10 of this embodiment are similar to those of the first embodiment.

[0091] Here, a modification of the information providing device 10 of the present embodiment will be described.

[0092] -Variation 1- The information providing device 10 may provide a route search service using the congestion situation calculated as described above. That is, when the information providing device 10 acquires information indicating the current location and the destination from the user terminal, it searches for a route that avoids observation sections where the congestion situation is at a predetermined level or higher, and returns the route to the user terminal. The route search from the current location to the destination can be realized by using an existing method.

[0093] The effect achieved by this modified example will be described with reference to FIG. 5. Each square shown corresponds to an observation section. The congestion status of each observation section is calculated based on each of a plurality of pieces of information (the sensor information, posted information, and other information described above), and the calculation results based on each piece of information are mapped onto a plurality of squares. Specifically, squares for which the congestion status is determined to be at or above a predetermined level based on each piece of information are filled with a pattern corresponding to each piece of information. The more overlapping the filling, the more crowded the area is. This display is one example of a method for outputting section information by output unit 14.

[0094] When the current location (S) and the destination (G) are set as shown in the figure, the shortest route indicated by the dashed line arrow passes through the congested observation area. Therefore, the information providing device 10 does not set the route as a search result, but instead searches for and outputs a route that does not pass through the congested observation area as indicated by the solid line arrow in the figure.

[0095] -Variation 2- When the information providing device 10 acquires information indicating the current location from the user terminal, the information providing device 10 may determine whether the congestion situation at the current location is equal to or higher than a predetermined level. If the congestion situation at the current location is equal to or higher than the predetermined level, the information providing device 10 may return a notification to the user terminal to encourage the user to move to another location by presenting a predetermined incentive. The notification may be sent by a method via the terminal held by the user (such as a push notification of an app or an email).

[0096] The content of the incentive is not particularly limited, but the information providing device 10 may present different content of the incentive depending on the attributes of the user. The attributes of the user are registered in advance in the information providing device 10. The information providing device 10 can identify the user and attributes of each user terminal based on, for example, login information (user ID (identifier), etc.) received from the user terminal.

[0097] In this case, if the movement to another location is confirmed within a predetermined time from the notification, the information providing device 10 can give a predetermined incentive to the user. The information providing device 10 can confirm the presence or absence of the movement based on, for example, information indicating the current location received from the user terminal.

[0098] -Variation 3- The zone information generation unit 13 obtains by any means information such as probe information (traffic volume, speed, etc.) installed on cars and roads, and route information to the destination installed in the car navigation system, and based on that information, calculates the number of people flowing into each observation zone, the number of people flowing out of each observation zone, and the number of people in each observation zone at time 0. Then, using the same method as above, it integrates it with values ​​calculated based on sensor information, posted information, etc.

[0099] -Variation 4- Based on information indicating the user's current location and acceleration information obtained from beacons installed around town and user terminals, the block information generation unit 13 calculates the number of people flowing into each observation block, the number of people flowing out of each observation block, and the number of people in each observation block at time 0. Then, using the same method as above, it integrates these values ​​with values ​​calculated based on sensor information, posted information, etc.

[0100] As described above, according to the information providing device 10 of the present embodiment, the same operational effects as those of the first embodiment are realized. Moreover, according to the information providing device 10 of the present embodiment, it is possible to grasp the congestion state of the observation target area in detail.

[0101] <Third embodiment> The information providing device 10 of this embodiment sets multiple observation sections A as shown in Fig. 3 in the above-mentioned observation section setting example 1, and generates and outputs section information indicating the risk of heat stroke for each observation section A. A detailed description will be given below.

[0102] The sensor information acquisition unit 12 acquires at least one of the following as sensor information: an image generated by a camera, temperature data generated by a temperature sensor, humidity data generated by a humidity sensor, illuminance data generated by an illuminance sensor, wind speed data generated by a wind speed sensor, and data indicating the operating status of an air conditioner generated by a monitoring sensor.

[0103] The zone information generating unit 13 generates zone information indicating the risk of heat stroke for each of a plurality of observation zones based on the sensor information and the heat conditions indicated in the posted content. The process of generating zone information will be described in detail below.

[0104] The zone information generating unit 13 can calculate the risk of heat stroke in the observation zone based on the following formula.

[0105] (Heat stroke risk [℃]) = (Heat index [℃]) + (Correction index [℃])

[0106] The output unit 14 may output the value of each observation section calculated by the formula as section information indicating the risk of heat stroke in each observation section.

[0107] Alternatively, the section information generating unit 13 may convert the value calculated by the formula into another index according to a predetermined rule, and input the converted index to the output unit 14 as section information indicating the risk of heat stroke in each observation section. The output unit 14 may then output the calculated index for each observation section as section information indicating the risk of heat stroke in each observation section. Examples of the conversion rules include, but are not limited to, "risk of heat stroke less than Y1 [°C]: safe, risk of heat stroke between Y1 [°C] and Y2 [°C]: slightly dangerous, risk of heat stroke between Y2 [°C] and Y3 [°C]: dangerous, risk of heat stroke over Y3 [°C]: very dangerous."

[0108] Here, a calculation example of each element of the above calculation formula will be described.

[0109] -Example of heat index calculation- The zone information generating unit 13 can calculate the heat index using the methods disclosed in Non-Patent Documents 1 and 2. An observation zone where a sensor is installed can calculate the heat index based on sensor information generated by that sensor. An observation zone where a sensor is not installed can calculate the heat index based on sensor information generated by sensors in other observation zones related to each observation zone. The heat index is expressed in units of "°C", and the higher the value, the higher the risk of heat stroke.

[0110] -Example of calculation of correction index- The section information generating unit 13 can calculate the correction index based on the image (sensor information) or the posted information. In addition, the section information generating unit 13 can calculate the correction index based on each of the image (sensor information) and the posted information, and calculate the correction index by adding them together. The unit of the correction index is "°C", and the higher the value, the higher the risk of heat stroke.

[0111] -An example of calculating the correction index based on an image- The section information generating unit 13 analyzes the images captured in each observation section, and detects the gestures, movements, and external features of people observed when it is hot. Examples of the movements and external features to be detected include, but are not limited to, fanning with a hand or an object, wiping sweat, staggering, a relaxed state, a pale face, a bright red face, sweating at a predetermined level or more, etc. The section information generating unit 13 counts the number of detections or the number of people detected with the above gestures, etc. for each observation section and for each predetermined unit time (e.g., every 5 minutes, every 10 minutes, every 30 minutes, every hour). Then, the section information generating unit 13 calculates a correction index for each observation section and for each unit time based on the count number and a predetermined calculation formula. The details of the calculation formula are design matters, but it is defined so that the larger the count number, the larger the correction index. The section information generating unit 13 may also perform the above-mentioned counting for each detected movement or appearance feature, and calculate a correction index for each observation section and for each unit time based on the product of the count number and a weighting value (a weighting value according to the detected movement or appearance feature) and a predetermined arithmetic expression. The weighting value becomes smaller for gestures of lower seriousness, such as wiping sweat, and the weighting value becomes larger for gestures of higher seriousness, such as unsteadiness.

[0112] In addition, for observation sections where images are not generated, the section information generation unit 13 can calculate a correction index for that observation section as a correction index calculated based on images of other observation sections related to each observation section, or a value obtained by multiplying that value by a predetermined coefficient.

[0113] -An example of calculating the correction index based on posted information- The section information generating unit 13 identifies the location of the poster based on the posted information. Specifically, the section information generating unit 13 identifies which area the poster is in. Each area includes a plurality of observation sections. The areas have been described in the second embodiment, and therefore will not be described here.

[0114] The block information generating unit 13 also analyzes the wording of the text data acquired as the posted content, and extracts words related to heat. Examples of words to be extracted include, but are not limited to, "hot," "too hot," and "dizzy." The block information generating unit 13 then counts the number of times the above words are extracted from the posted content posted in each area for each area and for each predetermined unit of time (e.g., every 5 minutes, every 10 minutes, every 30 minutes, every first hour). The block information generating unit 13 then calculates a correction index based on the count number and a predetermined arithmetic formula. Note that the details of the arithmetic formula are a design matter, but it is defined so that the larger the count number, the larger the correction index. The correction index is applied to all observation blocks included in the area.

[0115] Next, an example of information output by the output unit 14 will be described with reference to FIG. 6. Each square shown corresponds to an observation section. The risk of heat stroke in each observation section is calculated based on each of a plurality of pieces of information (the sensor information, posted information, and other information described above), and the calculation results based on each piece of information are mapped onto a plurality of squares. Specifically, squares for which the risk of heat stroke is determined to be equal to or higher than a predetermined level based on each piece of information are filled with a pattern corresponding to each piece of information. The greater the overlap of the filled areas, the higher the risk of heat stroke.

[0116] Other configurations of the information providing device 10 of this embodiment are similar to those of the first embodiment.

[0117] Here, a modification of the information providing device 10 of the present embodiment will be described.

[0118] -Variation 1- The zone information generating unit 13 identifies the behavior and clothing of each person detected in the image by image analysis, and calculates the risk of heat stroke for each person detected based on the identification result. Specifically, the risk of heat stroke for each person is calculated by adding a value calculated according to the behavior and clothing of each person detected to the risk of heat stroke for the observation zone in which the person exists, calculated by the above method. The correction method is disclosed in Non-Patent Document 3. The value added increases as the clothing increases the risk of heat stroke (no hat, wearing thick clothes, etc.). Also, the value added increases as the behavior increases the risk of heat stroke (intense exercise, physical labor, etc.).

[0119] When the detected risk of heat stroke of a person is equal to or higher than a predetermined level, the output unit 14 issues a warning to the person.

[0120] For example, if the face information (feature of appearance) of a user (a user who receives the warning service of the information providing device 10) is configured to be registered in advance (if the warning service is designed in such a way), the information providing device 10 may use face recognition technology or the like to determine whether a person detected in an image is a pre-registered user. If the person detected in an image is a pre-registered user, the output unit 14 may issue a warning to the user by a method via a terminal held by the user (such as a push notification of an app or an email).

[0121] Alternatively, the output unit 14 may output the warning information via an output device (such as a speaker or a display) installed near the location of the person to be warned.

[0122] Additionally, the output unit 14 may report to a predetermined notification recipient of people whose risk of heat stroke is at or above a predetermined level. The predetermined notification recipient may be a manager of the area under observation, a patrol staff member, a security guard, etc. The notification content may include an image, attributes, location, risk of heat stroke, etc. of people whose risk of heat stroke is at or above a predetermined level. The output unit 14 may realize the report to the predetermined notification recipient by a method via a terminal held by the predetermined notification recipient (such as a push notification of an app or an email).

[0123] If it is determined that a registered user is present in a section where the congestion status is equal to or higher than a certain level, the output unit 14 may issue a warning to the terminal carried by the user. The warning may include a display of a map showing the status of the observation section as shown in FIG. 6.

[0124] -Variation 2- When an observation section exists where the risk of heat stroke is equal to or higher than a predetermined level, the output unit 14 notifies the manager of the observation target area including the observation section and pre-registered users of that fact. The notification may be made via a terminal owned by the user (such as a push notification of an app or email). In addition, the information providing device 10 may post information indicating that fact on a predetermined SNS or social media.

[0125] -Variation 3- The section information generating unit 13 may generate the above-mentioned correction index for each group with similar attributes (gender, age). That is, the section information generating unit 13 analyzes an image to detect attributes of people detected from the image, and counts the above-mentioned "number of detections, or number of people detected by the above-mentioned gestures, etc." for each group with similar attributes. Then, the section information generating unit 13 calculates a correction index for each group based on the count number for each group.

[0126] The block information generating unit 13 also identifies the attributes of the poster from the poster's account information. The block information generating unit 13 then counts the number of times the above-mentioned "predetermined keyword is extracted" for each group with similar attributes. The block information generating unit 13 then calculates a correction index for each group based on the count for each group.

[0127] Then, the block information generating unit 13 integrates the correction index for each group generated based on the sensor information and the posted information in the same manner as described above. In this example, the block information generating unit 13 calculates the risk of heat stroke for each group of people with similar attributes. Then, the output unit 14 outputs the risk of heat stroke for each group.

[0128] -Variation 4- The area information generation unit 13 identifies the area where a specified event is taking place based on pre-registered information, and adds a specified correction index corresponding to the event being held to the heatstroke risk level [°C] of the observation area included in that area.

[0129] -Variation 5- The zone information generating unit 13 calculates a correction index to be added to the risk of heat stroke [°C] in the observation zone based on data indicating the operating status of the air conditioner generated by the monitoring sensor in that observation zone. If the temperature and humidity outside the building in which the air conditioner is installed are above the reference values ​​but the operating status of the air conditioner is below the reference level, the risk of heat stroke in that building increases. Therefore, in such a case, the zone information generating unit 13 determines a correction index greater than 0. The higher the temperature and humidity outside the building are and the lower the operating status of the air conditioner is (high set temperature, weak airflow, etc.), the larger the correction index determined by the zone information generating unit 13.

[0130] -Variation 6- Based on data indicating the operating status of an air conditioner generated by a monitoring sensor, the zone information generating unit 13 calculates a correction index to be added to the risk of heat stroke [°C] in the observation zone (exterior space) adjacent to the building in which the air conditioner is installed. In the observation zone adjacent to the building in which the air conditioner is installed, the risk of heat stroke increases as the operating status of the air conditioner increases due to the heat generated by the operation of the air conditioner. Therefore, the zone information generating unit 13 determines a larger correction index the higher the operating status of the air conditioner (lower set temperature, stronger airflow, etc.).

[0131] -Variation 7- The zone information generating unit 13 analyzes the image, calculates the proportion of shade in the observation zone, and calculates a correction index to be added to the heat stroke risk level [°C] of that observation zone according to that proportion. If the proportion of shade is equal to or less than a reference value, the zone information generating unit 13 determines a correction index greater than 0. The smaller the proportion of shade, the larger the correction index determined by the zone information generating unit 13.

[0132] In addition, for an observation section where no image is generated, a correction index calculated based on images of other observation sections related to each observation section, or a value obtained by multiplying this value by a predetermined coefficient, can be calculated as the correction index of that observation section. Considering that the direction of the shadow changes depending on the time of day, the predetermined coefficient may be different for each time of day.

[0133] -Variation 8- The zone information generating unit 13 calculates a correction index to be added to the risk of heat stroke [°C] for each observation zone based on at least one of the humidity data generated by the humidity sensor, the illuminance data generated by the illuminance sensor, and the wind speed data generated by the wind speed sensor. The zone information generating unit 13 determines a correction index greater than 0 when at least one of the humidity being equal to or greater than a reference value, the illuminance being equal to or greater than a reference value, and the wind speed being equal to or less than a reference value is satisfied. The zone information generating unit 13 then determines a larger correction index the higher the humidity, the higher the illuminance, and the lower the wind speed.

[0134] In addition, in observation sections where these sensor information are not generated, a correction index calculated based on the sensor information of other observation sections related to each observation section, or a value obtained by multiplying that value by a predetermined coefficient, can be calculated as the correction index for that observation section.

[0135] -Variation 9- In this modified example, the information providing device 10 is capable of remotely controlling heat control devices such as air conditioners and mist devices installed in the area to be observed. The output unit 14 then operates heat control devices installed in the observation area where the risk of heat stroke is at or above a predetermined level, or in the vicinity of the observation area (within a predetermined distance from the observation area).

[0136] As described above, according to the information providing device 10 of the present embodiment, the same action and effect as in the first embodiment is realized. Moreover, according to the information providing device 10 of the present embodiment, it is possible to grasp the risk of heat stroke of the observed subject in detail.

[0137] <Fourth embodiment> The information providing device 10 of this embodiment sets observation sections in units of facilities (stores, stations, etc.) existing in the area to be observed in the above-mentioned observation section setting example 2, and generates and outputs section information indicating the future congestion state of each observation section. This will be described in detail below.

[0138] The sensor information acquisition unit 12 acquires an image generated by a camera as sensor information.

[0139] The section information generating unit 13 generates section information indicating the future congestion state of the observed facility based on the congestion state of the location related to the observed facility estimated based on the image and the relevance between the observed facility and the trendy item identified in the posted content. The process of generating the section information will be described in detail below.

[0140] The block information generating unit 13 can estimate the future congestion state of the facility being observed based on the following calculation formula.

[0141] (Predicted number of visitors) = (degree of association with popular items) x (congestion status of locations related to the facility under observation / number of competing facilities) x (1 / coefficient according to distance from congested points) x (coefficient based on average number of visitors)

[0142] The section information generating unit 13 may input the calculated predicted number of visitors as section information indicating the future congestion state of each observation section to the output unit 14. Then, the output unit 14 may notify each facility of the input section information (predicted number of visitors) of each observation section.

[0143] In addition, the section information generating unit 13 may convert the calculated predicted number of visitors into another index according to a predetermined rule, and input the converted index to the output unit 14 as section information indicating the future congestion state of each observation section. Then, the output unit 14 may notify each facility of the input section information (converted index) of each observation section. Examples of conversion rules include, but are not limited to, "less than X1 number of people: vacant, between X1 and X2 number of people: slightly crowded, between X2 and X3 number of people: crowded, and over X3 number of people: very crowded."

[0144] The output unit 14 can realize the notification to each facility by using a means such as sending by email, displaying on a page after logging in to an app or web page, push notification of an app, etc. The notification may be a notification to a terminal associated with each facility.

[0145] Here, a calculation example of each element of the above calculation formula will be described.

[0146] -An example of calculating the relevance to trendy items- The degree of association is either 1 or 0. The block information generating unit 13 determines the degree of association for each facility based on information (business type, products handled, etc.) of each facility that has been registered in advance. For example, the block information generating unit 13 may set the degree of association for a facility that handles trendy items to 1, and the degree of association for a facility that does not handle trendy items to 0. Additionally, the block information generating unit 13 may set the degree of association for a facility that corresponds to a business type that handles trendy items to 1, and the degree of association for a facility that corresponds to a business type that does not handle trendy items to 0.

[0147] Next, a process for identifying a trendy item will be described. The section information generating unit 13 can identify a trendy item based on posted information. For example, the section information generating unit 13 may analyze posted content within a recent predetermined period to calculate the number of occurrences of words included in the posted content, and identify a product indicated by a word whose number of occurrences is equal to or exceeds a reference value as a trendy item. Note that the section information generating unit 13 may analyze only posted information that includes location information related to the observation target area to calculate the number of occurrences and identify a trendy item, or may analyze any posted information without being bound by location information to perform the process.

[0148] - Example of calculating the congestion status of locations related to the facility being observed - The block information generating unit 13 calculates the congestion status (number of people) of the area including the facility to be observed as the congestion status of the position related to the facility to be observed. The congestion status (number of people) of the area including the facility to be observed can be realized by adopting the process of calculating the congestion status (number of people) of a predetermined area described in the second embodiment. By estimating the current congestion status, the number of visitors to each facility several minutes to several hours later can be estimated.

[0149] -Example of calculating the number of competing facilities- The block information generating unit 13 determines the above-mentioned relevance of each facility to the first popular item based on pre-registered information of each facility (business type, products handled, etc.). Then, the block information generating unit 13 calculates the number of facilities with a relevance of "1" as the number of competing facilities for the first popular item.

[0150] - Example of coefficient calculation according to distance from congested points - The block information generating unit 13 identifies a point where the congestion level is equal to or higher than a reference level in an area including the facility to be observed. When there are multiple points where the congestion level is equal to or higher than the reference level, the block information generating unit 13 identifies multiple points. For example, the block information generating unit 13 identifies a point where the number of people detected from images generated by each of multiple cameras installed in the area is equal to or higher than a reference value as a point where the congestion level is equal to or higher than the reference level. Then, the block information generating unit 13 determines a coefficient according to the distance from the identified point. The distance can be calculated based on the position information of each facility registered in advance and the installation position information of the camera. The method of determining the coefficient is a design matter, but the coefficient is determined so that the coefficient increases as the distance increases.

[0151] -Example of coefficient calculation based on average number of visits- The block information generating unit 13 determines the coefficient for each facility based on pre-registered information about each facility (average number of visits calculated based on past performance). The method of determining the coefficient is a design matter, but the coefficient is determined so that the coefficient is larger for a facility with a higher average number of visits. For example, the block information generating unit 13 may determine the coefficient for each facility based on the ratio of the average number of visits for each facility to the total average number of visits for multiple competing facilities.

[0152] Other configurations of the information providing device 10 of this embodiment are similar to those of the first embodiment.

[0153] Here, a modification of the information providing device 10 of the present embodiment will be described.

[0154] -Variation 1- The block information generating unit 13 estimates the future (several hours later, the next day, etc.) congestion state as the above-mentioned "congestion state at the position related to the facility to be observed." Then, the block information generating unit 13 estimates the number of visitors to each facility in the future (several hours later, the next day, etc.) based on the "congestion state at the position related to the facility to be observed."

[0155] Predicting future crowding conditions can be achieved using any technology. For example, a prediction model can be generated based on machine learning based on past performance data that links factors that may affect the number of people coming there (weather, temperature, humidity, month, day of the week, season, surrounding events, number of reservations for facilities in the area, number of people in the area several hours ago, number of people in the area the previous day, etc.) with the actual number of people who came, and a prediction can be made based on the prediction model to generate an estimation model that estimates the number of people who will come there based on the factors mentioned above.

[0156] As described above, according to the information providing device 10 of the present embodiment, the same operational effects as those of the first embodiment are realized. Moreover, according to the information providing device 10 of the present embodiment, it becomes possible to grasp in detail the future congestion state of the facility that is the observation target.

[0157] <Modification> Here, a modified example of the information providing device 10 will be described. FIG. 7 shows an example of a functional block diagram of the information providing device 10 of the modified example. As shown in the figure, the information providing device 10 of the modified example has a block information generating unit 13 and an output unit 14. The information providing device 10 of the modified example differs from the first to fourth embodiments in that it does not have a post information acquiring unit 11 and a sensor information acquiring unit 12. The configurations of the block information generating unit 13 and the output unit 14 are the same as those of the first to fourth embodiments. The information providing device 10 of the modified example also achieves the same effects as those of the first to fourth embodiments.

[0158] Although the embodiments of the present invention have been described above with reference to the drawings, these are merely examples of the present invention, and various configurations other than those described above can also be adopted.

[0159] In this specification, "acquisition" includes at least one of the following: "the device itself goes to retrieve data stored in another device or storage medium (active acquisition)" based on user input or based on program instructions, such as receiving data by making a request or inquiry to another device, or accessing another device or storage medium and reading it, and "the device itself inputs data output from another device (passive acquisition)" based on user input or based on program instructions, such as receiving data that is distributed (or transmitted, push notification, etc.), and selecting and acquiring data from among the received data or information, and "editing data (converting it to text, rearranging data, extracting some data, changing the file format, etc.) to generate new data and acquiring the new data."

[0160] A part or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes. 1. A means for acquiring posted information including posted content and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for generating zone information for each of a plurality of observation zones based on the posted information and the sensor information; an output means for outputting the partition information; An information providing device having the above configuration. 2. An information providing device according to claim 1, wherein the output means outputs an image in which the area information is mapped onto a map. 3. The data generated by the sensor is an image; The posted information indicates at least one of the poster's location and a destination to which the poster is heading, 3. The information providing device according to claim 1, wherein the section information generating means generates the section information indicating the congestion state in each of the plurality of observation sections based on the analysis result of the image and the posted information. 4. The block information generating means 3. An information providing device according to claim 3, which estimates the congestion status of each of the observation sections in which the sensor is not installed based on the image of the observation section in which the sensor is installed. 5. An information providing device as described in 3 or 4, wherein the area information generation means estimates the congestion state in an area including a plurality of the observation areas based on the posted information, and then estimates the congestion state of each of the plurality of observation areas based on the estimated congestion state of the area. 6. The block information generating means estimates the poster's future travel route based on the posted information, 6. The information providing device according to any one of 3 to 5, further comprising: an information providing device that estimates a congestion state of each of the plurality of observation sections based on the estimated movement route. 7. The observation area is the facility to be observed; the data generated by the sensor is an image; The information providing device described in 1, wherein the area information generation means generates the area information indicating the future congestion situation of the facility to be observed based on the congestion situation of the location related to the facility to be observed estimated based on the image and the degree of association between the trendy items identified in the posted content and the facility to be observed. 8. The data generated by the sensor includes at least one of an image, temperature data, humidity data, illuminance data, wind speed data, and data indicating the operation status of an air conditioner; The area information generating means generates the area information indicating the risk of heat stroke in each of the plurality of observation areas based on the sensor information and the heat conditions indicated in the posted content. 9. The computer: Acquire posted content and posted information including location information posted on the Internet, Acquire sensor information including data generated by a sensor and installation location information of the sensor; generating zone information for each of a plurality of observation zones based on the posted information and the sensor information; An information providing method that outputs the partition information. 10. Computer A posted information acquisition means for acquiring posted information including posted contents and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for generating zone information for each of a plurality of observation zones based on the posted information and the sensor information; an output means for outputting the partition information; A program that functions as a 11. A zone information generating means for generating zone information for each of a plurality of observation zones based on posted content posted on the Internet including location information and sensor information including data generated by a sensor and installation location information of the sensor; an output means for outputting an image in which the block information is mapped on a map; An information providing device having the above configuration. [Explanation of symbols]

[0161] 10 Information provision device 11 Posting Information Acquisition Department 12 Sensor information acquisition unit 13. Partition information generation unit 14 Output section 1A Processor 2A Memory 3A input / output I / F 4A Peripheral circuit 5A Bus

Claims

1. A posting information acquiring means for acquiring posting information including posted content and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for integrating information generated based on the posted information and information generated based on the sensor information to generate zone information for each of a plurality of observation zones; an output means for outputting the partition information; having the data generated by the sensor is an image; The posted information indicates at least one of the poster's location and a destination to which the poster is heading, The zone information generating means is an information providing device that generates the zone information indicating the congestion state in each of the plurality of observation zones based on the analysis results of the image and the posted information.

2. The partition information generating means The information providing device according to claim 1 , wherein the congestion state of each of the observation sections where the sensor is not installed is estimated based on the image of the observation section where the sensor is installed.

3. The information providing device according to claim 1 or 2, wherein the section information generating means estimates the congestion state in an area including a plurality of the observation sections based on the posted information, and then estimates the congestion state of each of the plurality of observation sections based on the estimated congestion state of the area.

4. The block information generating means estimates a future movement route of the poster based on the posted information; The information providing device according to claim 1 , further comprising: a step of estimating a congestion state of each of the plurality of observation sections based on the estimated movement route.

5. A posting information acquiring means for acquiring posting information including posted content and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for generating zone information for each of a plurality of observation zones based on the posted information and the sensor information; an output means for outputting the partition information; having The observation area is a facility to be observed, the data generated by the sensor is an image; The area information generation means is an information providing device that generates the area information indicating the future congestion situation of the facility to be observed based on the congestion situation of the location related to the facility to be observed estimated based on the image, and the degree of association between the trendy items identified in the posted content and the facility to be observed.

6. A posting information acquiring means for acquiring posting information including posted content and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for integrating information generated based on the posted information and information generated based on the sensor information to generate zone information for each of a plurality of observation zones; an output means for outputting the partition information; having The data generated by the sensor includes at least one of an image, temperature data, humidity data, illuminance data, wind speed data, and data indicating an operating status of an air conditioner; The zone information generating means is an information providing device that generates the zone information indicating the risk of heat stroke in each of the plurality of observation zones based on the sensor information and the heat conditions indicated in the posted content.

7. 7. The information providing device according to claim 1, wherein the output means outputs an image in which the section information is mapped onto a map.

8. An information providing device described in any one of claims 1 to 7, wherein the area information generating means generates the area information based on both the posted information and the sensor information.

9. The computer Acquire posted content and posted information including location information posted on the Internet, Acquire sensor information including data generated by a sensor and installation location information of the sensor; Integrating the information generated based on the posted information and the information generated based on the sensor information to generate zone information for each of a plurality of observation zones; Outputting the partition information; the data generated by the sensor is an image; The posted information indicates at least one of the poster's location and a destination to which the poster is heading, An information providing method in which the computer generates the area information indicating the congestion status in each of the multiple observation areas based on the analysis results of the image and the posted information.

10. Computer, A posted information acquisition means for acquiring posted information including posted contents and location information posted on the Internet; A sensor information acquisition means for acquiring sensor information including data generated by a sensor and installation location information of the sensor; a zone information generating means for integrating information generated based on the posted information and information generated based on the sensor information to generate zone information for each of a plurality of observation zones; an output means for outputting the partition information; Function as a the data generated by the sensor is an image; The posted information indicates at least one of the poster's location and a destination to which the poster is heading, The area information generation means is a program that generates the area information indicating the congestion status in each of the plurality of observation areas based on the analysis results of the image and the posted information.

Images