Garbage collection time notification method

Abstract

The invention relates to a garbage collection time notification method. And the vehicle sends an image indicating that the garbage collection station appears to the server. The server executes the following steps: identifying a to-be-accessed collection station image of a to-be-accessed collection station from a plurality of images acquired from the vehicle, wherein the to-be-accessed collection station is a collection station that the garbage truck does not pass through in a driving route of the garbage truck; calculating an estimated garbage amount gathered at the collection site to be accessed based on the identified image of the collection site to be accessed; calculating an expected arrival time to a collection station passed by the garbage truck after the collection station to be accessed in the driving route, so that the expected arrival time to the collection station becomes later when the estimated garbage amount is large than when the estimated garbage amount is small; and notifying a user terminal of the expected arrival time.

Description

Technical Field

[0001] The invention relates to a garbage collection time notification method. Background Art

[0002] The garbage truck disclosed in Japanese Unexamined Patent Application Publication No. 2022-170463 (JP 2022-170463 A) sequentially visits a plurality of garbage collection sites according to a preset travel route. The garbage truck collects garbage at each collection site. Summary of the invention

[0003] In a technique such as JP 2022-170463 A, a garbage truck visits collection sites in sequence, and the time when the garbage truck arrives at each collection site may vary depending on the situation. In this case, a user who dumps garbage at a collection site cannot know the time when the garbage truck arrives at the collection site used by the user. Therefore, the garbage truck may arrive at the collection site earlier than the predicted time, which is the time that the user has assumed. In this case, before the above-mentioned predicted time, the garbage truck finishes collecting garbage at the collection site and sets off for the next collection site. Therefore, the user cannot dump the garbage.

[0004] A garbage collection time notification method for solving the above-mentioned problem is performed by: a garbage truck including a receiver that acquires information about the current position of the receiver itself; an information processing device capable of communicating with the garbage truck, the information processing device storing position information about a plurality of collection sites where the garbage truck collects garbage and a driving route along which the garbage truck sequentially visits the plurality of collection sites; and a vehicle capable of communicating with the information processing device, the vehicle including a camera that images the surroundings and the receiver that acquires information about the current position of the receiver itself. The vehicle sends a plurality of images in which the collection sites appear among a plurality of images taken by the camera to the information processing device together with imaging information showing the imaging position and imaging date and time of each of the plurality of images. The information processing device executes: acquiring multiple images and imaging information sent by the vehicle; acquiring information about the current position of the garbage truck; identifying, based on the information about the current position of the garbage truck and the imaging information, an image of a collection site to be visited in which a collection site to be visited appears in the multiple images acquired from the vehicle, the collection site to be visited being the collection site that the garbage truck has not passed through in the driving route; calculating an estimated amount of garbage based on the identified image of the collection site to be visited, the estimated amount of garbage being an estimated value of the amount of garbage accumulated at the collection site to be visited; calculating an expected arrival time at a predetermined collection site, so that the expected arrival time at the predetermined collection site becomes later when the estimated amount of garbage is large than when the estimated amount of garbage is small; and outputting notification information for notifying the expected arrival time at the predetermined collection site.

[0005] The above technical concept can provide users of garbage collection sites with accurate information about the expected arrival time of garbage trucks. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will be described below with reference to the accompanying drawings, wherein like symbols represent like elements, and wherein:

[0007] Figure 1 is a schematic configuration diagram of a notification system;

[0008] Figure 2 is a flowchart showing the processing procedure of notification processing; and

[0009] Figure 3 is a view showing an example of a notification image. DETAILED DESCRIPTION

[0010] <Overall Configuration>

[0011] An embodiment of the garbage collection time notification method will be described below with reference to the accompanying drawings. Figure 1 As shown, the notification system 100 includes a plurality of vehicles 70, a plurality of user terminals 50, a plurality of garbage trucks 30 and a server 10. Figure 1 , one vehicle 70 among the plurality of vehicles 70 is shown as a representative. The same applies to the user terminal 50 and the garbage truck 30.

[0012] <Vehicle>

[0013] The plurality of vehicles 70 are vehicles that are pre-registered in the server 10 as vehicles that provide images of garbage collection sites. Each vehicle 70 includes a control device 72, a camera 82, and a receiver 84. The control device 72 includes a CPU 74, a memory 76, a communication module 78, and a real-time clock 79. The memory 76 has pre-stored various programs in which the processing to be executed by the CPU 74 is written. There are three types of memory 76: RAM, ROM, and electrically rewritable non-volatile types. In this embodiment, these three types are collectively referred to as memories. The same applies to other control devices and servers 10 that will be described later. The communication module 78 is a communication circuit for wirelessly communicating with the outside through an external communication line network. The communication module 78 sends information to the outside when receiving an instruction from the CPU 74, or obtains information from the outside and transmits the information to the CPU 74. The real-time clock 79 is a circuit that generates information about date and time.

[0014] The camera 82 is, for example, an imaging device constituting a driving recorder. The camera 82 images the surroundings of the vehicle 70 with the exterior of the vehicle 70 as a target. The camera 82 generates the image thus obtained. The camera 82 images the surroundings of the vehicle 70 and repeatedly generates images during the travel of the vehicle 70.

[0015] The receiver 84 acquires information about the current position of the receiver 84 itself from the global positioning satellite. The information about the current position is specifically the coordinates of the current position indicated by latitude and longitude. The current position of the receiver 84 corresponds to the current position of the vehicle 70.

[0016] The CPU 74 repeatedly acquires the current position of the vehicle 70 from the receiver 84. When the current position of the vehicle 70 matches one of the plurality of registered places, that is, when the vehicle 70 has passed through the registered place, the CPU 74 performs data generation processing. The registered place is a collection site as a target of which an image is to be provided. The memory 76 has stored the position coordinates of a plurality of registered places in advance. In the data generation processing, the CPU 74 acquires from the camera 82 an image that has been captured by the camera 82 when the vehicle 70 has passed through the registered place. The CPU 74 processes the image as an image in which the collection site appears. Therefore, the CPU 74 acquires from the camera 82 an image in which the collection site appears in the image that the camera 82 is capturing as required. Then, the CPU 74 generates a data set in which the acquired image is provided with imaging information and a vehicle number as data to be provided. The imaging information is the imaging position and imaging date and time of the acquired image. The CPU 74 processes the position coordinates of the registered place that has triggered the execution of the data generation processing as the imaging position of the acquired image. The CPU 74 processes the date and time when the vehicle 70 has passed the registration place that has triggered the execution of the data generation process as the imaging date and time of the acquired image. The vehicle number is a single identification number assigned to each vehicle 70. When the CPU 74 has generated the data to be provided, the CPU 74 transmits the generated data to be provided to the server 10.

[0017] <User Terminal>

[0018] A plurality of user terminals 50 are mobile terminals owned by respective users who dump garbage at a collection site. Each user terminal 50 is, for example, a smart phone or a tablet terminal. Each user terminal 50 includes a control device 52 and a user interface 60. The control device 52 includes a CPU 54, a memory 56, and a communication module 58. The memory 56 has pre-stored various programs in which the processing to be executed by the CPU 54 is written. The functions of the communication module 58 are the same as those described for the control device 72 of the vehicle 70. The user interface 60 includes, for example, a touch panel display screen. Therefore, when the user performs an input operation on the user interface 60, information corresponding to the input operation is input into the control device 52.

[0019] The CPU 54 may perform a display process according to the operation of the user. The display process is a process for displaying the expected arrival schedule of the garbage truck 30 on the user interface 60. Specifically, when the display process is instructed to be executed, the CPU 54 outputs a request for transmitting notification information related to the expected arrival time of the garbage truck 30 to the server 10. When the CPU 54 acquires notification information from the server 10 as a response to the transmission request, the CPU 54 displays an image corresponding to the acquired notification information on the user interface 60.

[0020] <Garbage Truck>

[0021] A plurality of garbage trucks 30 are pre-registered in the server 10 as vehicles of which the server 10 is to track the position. Each garbage truck 30 includes a control device 32 and a receiver 39. The control device 32 includes a CPU 34, a memory 36, and a communication module 38. The memory 36 has pre-stored various programs in which processes to be executed by the CPU 34 are written. The function of the communication module 38 is the same as that described for the control device 72 of the vehicle 70. The receiver 39 acquires information on the current position of the receiver 39 itself from a global positioning satellite. The current position of the receiver 39 corresponds to the current position of the garbage truck 30. The CPU 34 repeatedly transmits a data set in which the current position acquired by the receiver 39 is provided with a vehicle number as position data to the server 10. The vehicle number is a single identification number assigned to each garbage truck 30.

[0022] As is well known, the garbage truck 30 is a special vehicle for collecting garbage. Operated by a worker, the garbage truck 30 sequentially visits a plurality of collection sites. The garbage truck 30 collects garbage at each collection site through work performed by the worker.

[0023] <Server>

[0024] The server 10 is an information processing device owned by a local government or an operator commissioned by the local government. The server 10 includes a CPU 12, a memory 14, a communication module 16, and a real-time clock 18. The memory 14 has previously stored various programs in which processes to be executed by the CPU 12 are written. The functions of the communication module 16 and the real-time clock 18 are the same as those described for the control device 72 of the vehicle 70.

[0025] The memory 14 has previously stored the vehicle numbers of a plurality of garbage trucks 30 as targets whose positions are to be tracked. The CPU 12 always receives the position data transmitted from these garbage trucks 30.

[0026] The memory 14 has previously stored the vehicle numbers of the plurality of vehicles 70 that provide images of the garbage collection site. The CPU 12 always receives the data to be provided that are transmitted from the plurality of vehicles 70. When the CPU 12 acquires the data to be provided from the vehicle 70, the CPU 12 causes the memory 14 to continue to store the acquired data to be provided only on the day on which the data to be provided has been acquired.

[0027] The memory 14 has pre-stored map data. The map data has a plurality of nodes and a plurality of links. Each node represents a position coordinate indicated by latitude and longitude. Each node provides a plurality of accompanying information. An example of the accompanying information is the type of node such as an intersection or a fork. Each link is designated as a line segment connecting adjacent nodes. Each link represents a road. Each link provides a plurality of accompanying information. An example of the accompanying information is the type of road such as a national road or a county road.

[0028] The map data includes location information about a plurality of collection sites. Specifically, in the map data, each node corresponding to a collection site is provided with an identification value indicating that the node is a collection site, a collection site number assigned to each collection site, and an identification value indicating the area name of each collection site as incidental information. The collection site number corresponds to the sequential number of garbage collected by a garbage truck 30. Specifically, the collection site first visited by the garbage truck 30 is assigned "1" as the collection site number. The collection site number of the collection site becomes larger according to the sequential number of the garbage truck 30 visiting the collection site. The collection site last visited by the garbage truck 30 is provided with an identification value indicating that the collection site is the last collection site. Collection site numbers are assigned to each collection area. A collection area is an area including a plurality of collection sites visited by a garbage truck 30 on a certain day of the week.

[0029] The map data includes information about the driving route of the garbage truck 30 that visits multiple collection sites in sequence. Specifically, in the map data, the link corresponding to the driving route is provided with an identification value and a route number as incidental information, the identification value indicating that the link is a road passed by the garbage truck 30, and the route number indicating the number of the driving route. The route number can also be called an identification number indicating a collection area. When viewing a collection area, the driving route starts from the base of the garbage truck 30 as the starting point, and connects the nodes of the collection sites present in the collection area in the order of increasing collection site numbers. The end point of the driving route is the base of the garbage truck 30. In this embodiment, a responsible garbage truck 30 is pre-assigned for each collection area (i.e., each driving route). The route number reflects the vehicle number of the responsible garbage truck 30.

[0030] <Notification Processing>

[0031] The CPU 12 can perform notification processing. The notification processing is a processing for notifying each user terminal 50 of the expected arrival time of the garbage truck 30 at each collection site. The CPU 12 performs the notification processing for each collection area. In the following, the content of the notification processing will be described with one collection area as the target. When a day of the week for garbage collection in the target collection area arrives, the CPU 12 identifies the garbage truck 30 that should travel around the collection area based on the route number included in the map data. Subsequently, the CPU 12 repeatedly obtains information about the current position from the garbage truck 30. When the garbage truck 30 departs from the base, the CPU 12 starts the notification processing. The CPU 12 repeats the notification processing until the garbage truck 30 arrives at the last collection site in the collection area. The CPU 12 starts the notification processing at a predetermined time interval (e.g., ten minutes). When the garbage collection day arrives, the CPU 12 performs the following processing before executing the first notification processing. First, the CPU 12 identifies the travel route assigned with the route number corresponding to the target collection area from the map data. When the CPU 12 has identified the travel route, the CPU 12 identifies the advancing direction of the garbage truck 30 on the travel route with reference to the collection site number of the garbage collection site. Thereafter, the CPU 12 identifies the collection site number of the collection site that is the second-to-last collection site on the travel route as the analysis final number. The CPU 12 uses this identified information in each notification process. Although a point-by-point description will be omitted, the CPU 12 stores a plurality of pieces of information that the CPU 12 has identified or generated in the memory 14 as needed.

[0032] like Figure 2 As shown in FIG. 1 , when the CPU 12 has started the notification process, the CPU 12 resets the destination site number to zero before executing the process of step S1. In step S1, the CPU 12 updates the destination site number. Specifically, the CPU 12 adds "1" to the previous value of the destination site number set at the current time point. Then, the CPU 12 uses the obtained value as the new destination site number. Thereafter, the CPU 12 moves to the process of step S2.

[0033] In step S2, the CPU 12 determines whether the collection site corresponding to the target site number is a collection site to be visited. The collection site to be visited is a collection site that the garbage truck 30 has not passed in the driving route. As a specific process of step S2, the CPU 12 first identifies the collection site corresponding to the target site number in the driving route that has been previously identified. Then, the CPU 12 compares the position of the identified collection site with the current position of the garbage truck 30 in the driving route. When the current position of the garbage truck 30 is a position that is further forward than the collection site corresponding to the target site number in the driving route, the CPU 12 determines that the collection site corresponding to the target site number is not a collection site to be visited (step S2: No). In this case, the CPU 12 moves to the process of step S12. Similarly, when the current position of the garbage truck 30 matches the collection site corresponding to the target site number, the CPU 12 determines "No" in step S2. Then, the CPU 12 moves to the process of step S12. The process of step S12 will be described later.

[0034] On the other hand, in step S2, when the current position of the garbage truck 30 is a position before the collection site corresponding to the target site number in the driving route, the CPU 12 determines that the collection site corresponding to the target site number is the collection site to be visited (step S2: Yes). In this case, the CPU 12 moves to the processing of step S3. Hereinafter, the collection site to be visited corresponding to the target site number will be referred to as the analysis target site.

[0035] In step S3, the CPU 12 identifies an analysis target image, which is an image in which the analysis target site appears in the images included in the multiple pieces of data to be provided stored in the memory 14. The analysis target image corresponds to the collection site image to be visited as an image in which the collection site to be visited appears. The CPU 12 identifies the analysis target image as follows. First, for each piece of data to be provided, the CPU 12 refers to the imaging position in the multiple pieces of imaging information attached to the image. The CPU 12 identifies the image whose imaging position matches the position coordinates of the analysis target site known from the map data as a candidate image. Here, in some cases, there are multiple candidate images, and in other cases, there is only one candidate image. When there are multiple candidate images, the CPU 12 refers to the imaging date and time attached to the candidate image. The CPU 12 identifies the image whose imaging date and time is the latest among the multiple candidate images as the analysis target image. On the other hand, when there is only one candidate image, the CPU 12 directly identifies the candidate image as the analysis target image. When the CPU 12 has identified the analysis target image, the CPU 12 moves to the processing of step S4. Therefore, through the processing of step S3 and the processing of step S2 described above, the CPU 12 identifies the analysis target image where the analysis target site appears based on the current position of the garbage truck 30 and the imaging position and imaging date and time included in each piece of data to be provided. Depending on how much data to be provided is collected, there may be no analysis target image. In this case, the CPU 12 skips step S4, step S5, and step S6 to be described later. In step S7, the CPU 12 sets the pre-specified standard collection time to the required collection time to be described later. The memory 14 has stored the standard collection time in advance.

[0036] In step S4, the CPU 12 calculates an estimated garbage amount based on the analysis target image identified in step S3. The estimated garbage amount is an estimated value of the amount of garbage gathered at the collection site to be visited. The CPU 12 calculates the estimated garbage amount using a first model pre-stored in the memory 14. The first model is a learning model that has been learned by supervised learning before the first model has been installed in the server 10. The first model receives the collection site image to be visited as an input and outputs the estimated garbage amount. By inputting the analysis target image into the first model, the CPU 12 calculates the estimated garbage amount at the analysis target site.

[0037] Here, data associating an image of a collection site to be visited with a specific amount of garbage and a specific amount of garbage as correct answer information is referred to as first teacher data. The first model has been learned using such first teacher data. Specifically, in order to learn the first model, numerous pieces of first teacher data generated based on various images of collection sites to be visited with different amounts of garbage are prepared in advance. Then, the parameters of the first model are repeatedly adjusted so that the output of the first model when the first model is executed using each first teacher data as a target is close to the correct answer information included in the first teacher data. In this way, the learning of the first model is performed. The amount of garbage of the correct answer information is specified as the number of garbage bags. Therefore, the amount of garbage increases as the number of garbage bags increases.

[0038] When CPU 12 calculates the estimated garbage amount in step S4, CPU 12 moves to the processing of step S5. In step S5, CPU 12 calculates the level of littering of garbage based on the analysis target image identified in step S3. Here, the garbage bags gathered together at the collection site may be messed up by, for example, wild animals. As a result, the garbage bag may be torn open, and the garbage in it may be thrown out. In this case, the collection site is in a state of littering with garbage thrown out from the garbage bag. The littering level represents the degree of littering that the garbage is rated in multiple levels under the state of being thrown out of the garbage bag. CPU 12 uses the second model pre-stored in the memory 14 to calculate the littering level. The second model is a learning model that has been learned by supervised learning before the second model has been installed in the server 10. The second model receives the collection site image to be visited as input, and outputs the littering level. By inputting the analysis target image into the second model, CPU 12 calculates the littering level at the analysis target site.

[0039] Here, data associating an image of a collection site to be visited of a certain littering level with a certain littering level as correct answer information is referred to as second teacher data. The second model has been learned using such second teacher data. Specifically, in order to learn the second model, numerous pieces of second teacher data generated according to various images of collection sites to be visited of different littering levels are prepared in advance. Then, the parameters of the second model are repeatedly adjusted so that when the second model is executed using each second teacher data as a target, the output of the second model is close to the correct answer information included in the second teacher data. In this way, the learning of the second model is performed. The littering level of the correct answer information becomes higher as the amount of garbage thrown out of the garbage bag increases.

[0040] When the CPU 12 has calculated the littering level in step S5, the CPU 12 moves to the processing of step S6. In step S6, the CPU 12 sets a time period flag. The time period flag is a flag used to separate the time period in which the amount of garbage at the target site of the analysis is particularly large from other time periods. As a prerequisite for the CPU 12 to execute step S6, the memory 14 has pre-stored a time period division list of each collection area. Each of the 24 time periods into which a year is divided on a half-month basis will be referred to as a single time period. In a time period division list, the following content is specified in association with each of the multiple collection site numbers included in the target collection area. In a time period division list, a single time period corresponding to the first time period and a single time period corresponding to the second time period are specified for each collection site. The first time period is a time period in which the amount of garbage gathered at the target collection site in a garbage collection becomes equal to or greater than a set value. The second time period is a time period in which the amount of garbage gathered at the target collection site in a garbage collection becomes less than a set value. As described above, the amount of garbage is the number of garbage bags. The set value is pre-specified as, for example, twice the standard amount of garbage. For example, the standard amount of garbage is the annual average value of the amount of garbage in various collection areas as a whole.

[0041] As a specific process of step S6, the CPU 12 first identifies the time period division list of the target collection area from the time period division lists of each collection area. Each time period division list is provided with the above-mentioned route number. The CPU 12 identifies the time period division list of the target collection area based on the route number. When the CPU 12 has identified the time period division list, the CPU 12 identifies the collection site corresponding to the collection site number of the analysis target site from the multiple collection sites specified in the time period division list. Then, the CPU 12 refers to the first time period and the second time period related to the collection site. The CPU 12 compares these time periods with the imaging date and time attached to the analysis target image identified in step S3 (that is, the imaging date and time of the collection site image to be visited based on which the estimated garbage amount has been calculated in step S4). The CPU 12 determines whether the imaging date and time of the analysis target image is a date and time within the first time period or a date and time within the second time period. When the imaging date and time of the analysis target image is a date and time within the first time period, the CPU 12 sets the time period flag to "1". On the other hand, when the imaging date and time is a date and time within the second period, the CPU 12 sets the period flag to “2.” Thereafter, the CPU 12 moves to the process of step S7.

[0042] In step S7, the CPU 12 calculates the required collection time. The required collection time is the time required for the worker to collect the garbage into the garbage truck 30 at the analysis target site. The CPU 12 calculates the required collection time based on the estimated garbage amount calculated in step S4, the littering level calculated in step S5, and the time period flag calculated in step S6. When the littering level is the same and the time period flag is also the same, the CPU 12 calculates the required collection time so that the required collection time becomes longer as the estimated garbage amount becomes larger. When the estimated garbage amount is the same and the time period flag is also the same, the CPU 12 calculates the required collection time so that the required collection time becomes longer as the littering level becomes higher. When the estimated garbage amount is the same and the littering level is also the same, the CPU 12 calculates the required collection time so that the required collection time becomes longer when the time period flag is "1" than when the time period flag is "2". The CPU 12 calculates the required collection time based on the following relational expression, for example. The CPU 12 calculates the sum of the value obtained by multiplying the estimated garbage amount by the first coefficient, the value obtained by multiplying the littering level by the second coefficient, and the correction value as the required collection time. When the time period flag is "1", the CPU 12 sets the correction value to a pre-specified positive value. The memory 14 has already stored the correction value in advance. When the time period flag is "2", the CPU 12 sets the correction value to zero. The first coefficient is a coefficient for converting the estimated garbage amount into the garbage collection time. The second coefficient is a coefficient for converting the littering level into the garbage collection time. When the CPU 12 has calculated the required collection time, the CPU 12 moves to the processing of step S8.

[0043] In step S8, the CPU 12 calculates the travel time from the analysis target site to the next collection site. The next collection site is a collection site to be visited that is visited by the next garbage truck 30 of the analysis target site in the travel route of the garbage truck 30. Therefore, the next collection site corresponds to a predetermined collection site, which is a collection site to be visited that the garbage truck 30 passes after the analysis target site. For example, the CPU 12 calculates the travel time based on the travel distance of the garbage truck 30 from the analysis target site to the next collection site and the estimated travel speed of the garbage truck 30. In this case, the CPU 12 calculates the travel time so that the travel time becomes shorter as the travel distance becomes shorter. The CPU 12 calculates the travel time so that the travel time becomes shorter as the estimated travel speed becomes higher. For example, the CPU 12 can calculate the travel distance as the distance from the analysis target site to the next collection site based on the travel route in the map data. The CPU 12 can calculate the estimated travel speed, for example, based on whether there is traffic congestion from the analysis target site to the next collection site. In this case, CPU 12 can determine whether there is traffic congestion from the analysis target site to the next collection site by acquiring the latest traffic information from the traffic information distribution sensor. When CPU 12 has calculated the travel time from the analysis target site to the next collection site, CPU 12 moves to the processing of step S9.

[0044] In step S9, the CPU 12 determines whether the analysis target site as the target at the current time point is the first collection site to be visited for the first time that has been identified in the current notification process. Hereinafter, the collection site to be visited for the first time will be referred to as the first collection site. When the analysis target site is not the first collection site (step S9: No), the CPU 12 skips the subsequent step S10 and moves to the processing of step S11. On the other hand, when the analysis target site is the first collection site (step S9: Yes), the CPU 12 moves to the processing of step S10.

[0045] In step S10, the CPU 12 calculates the expected arrival time to the first collection site. First, the CPU 12 calculates the travel time from the current position of the garbage truck 30 to the first collection site through the same process as step S8. When the CPU 12 has calculated the travel time, the CPU 12 sets the time from the current time point to the calculated travel time as the expected arrival time to the first collection site. When the CPU 12 has calculated the expected arrival time to the first collection site, the CPU 12 performs the following operations. The CPU 12 stores the collection site number of the first collection site and the expected arrival time to the first collection site in association with each other as the first data of the calculation result information in the memory 14. Through the subsequent processing of step S11, the expected arrival time of other collection sites to be visited is sequentially added to the calculation result information. The collection site number of the first collection site is the target site number at the current time point. Thereafter, the CPU 12 moves to the processing of step S11.

[0046] In step S11, the CPU 12 calculates the expected arrival time to the next collection site. First, the CPU 12 retrieves the expected arrival time of the collection site to be visited (i.e., the target site number for the current time point) immediately before the next collection site from the multiple calculation result information stored in the memory 14. The CPU 12 calculates the expected arrival time to the next collection site based on the expected arrival time and the travel time to the next collection site calculated in step S8. Specifically, the CPU 12 sets the time from the aforementioned expected arrival time to the travel time calculated in step S8 as the expected arrival time to the next collection site. Thereafter, the CPU 12 adds the expected arrival time to the next collection site to the calculation result information in association with the collection site number of the next collection site. Thereafter, the CPU 12 moves to the processing of step S12.

[0047] In step S12, the CPU 12 determines whether the analysis has been completed for all the collection sites for which the expected arrival time should be calculated. Specifically, in step S12, the CPU 12 determines whether the target site number at the current time point matches the aforementioned analysis final number that has been identified before the notification process has started. When the target site number at the current time point does not match the analysis final number (step S12: No), the CPU 12 returns to step S1. On the other hand, when the target site number at the current time point matches the analysis final number (step S12: Yes), the CPU 12 moves to the process of step S13.

[0048] In step S13, the CPU 12 generates a notification image. The notification image is an image for notifying the users of the collection sites of the expected arrival time of the garbage truck 30 at each collection site. The CPU 12 generates the notification image to reflect the content of the calculation result information. Figure 3 As shown, the notification image is, for example, a list in which necessary information of each collection site is arranged from the top in order of increasing collection site numbers. The necessary information includes the collection site number, the area name of the collection site, and the expected arrival time. For the area name of the collection site, the CPU 12 converts the identification value representing the area name of the collection site included in the map data into a character string of the actual area name, and writes the character string into the notification image. The CPU 12 processes the expected arrival time in the following manner. For a collection site among multiple collection sites for which the expected arrival time has been calculated (i.e., for a collection site to be visited), the CPU 12 writes the expected arrival time included in the calculation result information into the map image. On the other hand, for a collection site for which the expected arrival time has not yet been calculated, the CPU 12 writes in the notification image that the garbage has been collected. As shown in FIG. Figure 2 As shown, when the CPU 12 has generated the notification image, the CPU 12 moves to the process of step S14.

[0049] The collection site corresponding to the analysis final number (i.e., the second to last collection site in the driving route) will be referred to as the analysis final site. Here, with respect to step S13, when the current position of the garbage truck 30 is between the analysis final site and the last collection site in the driving route when the notification process is performed, the CPU 12 reaches step S13 without calculating the expected arrival time to the last collection site due to the relationship with step S2, step S12, etc. Therefore, only when the current position of the garbage truck 30 is between the analysis final site and the last collection site when the notification process is performed, the CPU 12 performs the following processing in step S13. The CPU 12 calculates the expected arrival time to the last collection site in consideration of the travel distance from the current position of the garbage truck 30 to the last collection site, etc. Then, the CPU 12 generates a notification image in which the calculated time is indicated as the expected arrival time to the last collection site. In this notification image, it is indicated that the garbage of all other collection sites has been collected.

[0050] In step S14, the CPU 12 enters a standby state waiting for a sending request from the user terminal 50. When the CPU 12 obtains the sending request from the user terminal 50, the CPU 12 outputs the notification image generated in step S13 as notification information to the user terminal 50. When making a sending request to the server 10, the user terminal 50 includes the route number of the collection area where the owner of the user terminal 50 lives in the sending request. Based on the route number, the CPU 12 can determine which collection area is requested as the target notification image. In step S14, the CPU 12 outputs the notification image at the time of the sending request for the target collection area. After the processing of step S14 is started, when the time to execute the next notification processing comes, the CPU 12 ends the processing of step S14 after deleting the calculation result information and the notification image from the memory 14. Then, the CPU 12 temporarily ends the notification processing.

[0051] As described above, the CPU 12 does not perform the notification process during the time window before the garbage truck 30 departs from the base. When there is a request for the arrival time from the user terminal 50 during the time window, the CPU 12 outputs an image to the user terminal 50 indicating that garbage collection has not started. The CPU 12 also does not perform the notification process during the time window after the garbage truck 30 has arrived at the last collection site. When there is a request for the arrival time from the user terminal 50 during the time window, the CPU 12 outputs an image to the user terminal 50 indicating that garbage collection has ended.

[0052] <Functions and Effects of the Embodiment>

[0053] (1) When the amount of garbage gathered at a collection site is large, it takes time to collect garbage at the collection site. Therefore, in this case, the time to arrive at the subsequent collection site to be visited becomes later. The CPU 12 takes into account the amount of garbage collected at each collection site when calculating the expected arrival time to each subsequent collection site to be visited. Specifically, when calculating the expected arrival time to the next collection site, the CPU 12 calculates the expected arrival time to the next collection site so that the expected arrival time becomes later when the estimated amount of garbage at the analysis target site is large than when the estimated amount of garbage at the analysis target site is small. Therefore, by calculating the expected arrival time in this way taking into account whether the estimated amount of garbage is large or small, the CPU 12 can accurately calculate the expected arrival time to each collection site to be visited. Then, the CPU 12 outputs a notification image reflecting this expected arrival time to the user terminal 50. Thus, the CPU 12 can provide the user with more accurate information as the expected arrival time to each collection site to be visited. With such information, the user is less likely to be late for taking out the garbage.

[0054] (2) As time goes by, the amount of garbage accumulated at the collection site gradually increases. Therefore, when calculating the estimated amount of garbage based on the image, using an image taken at the latest possible time reduces the possibility of the estimated amount of garbage deviating from the actual amount of garbage when the garbage truck 30 arrives at the collection site. Therefore, when identifying the analysis target image, if there are multiple candidate images for the same collection site to be visited as a target, the CPU 12 selects the image with the latest imaging date and time among the candidate images as the analysis target image. Then, the CPU 12 calculates the estimated amount of garbage based on the analysis target image. Therefore, the CPU 12 calculates the estimated amount of garbage at the analysis target site based on the latest information about the analysis target site. Therefore, by calculating the expected arrival time based on the estimated amount of garbage, the CPU 12 can more accurately calculate the expected arrival time to each collection site to be visited.

[0055] (3) The garbage gathered at the collection site may be messed up by, for example, wild animals. In this case, the garbage is in a state of being littered at the collection site. If the garbage is littered at the collection site, it takes time to collect the garbage at the collection site. CPU 12 takes into account the degree of littering of the garbage and calculates the expected arrival time of each collection site to be visited. Specifically, when calculating the expected arrival time of the next collection site, CPU 12 calculates the expected arrival time of the next collection site so that the expected arrival time becomes later when the level of littering at the analysis target site is high than when the level of littering at the analysis target site is low. Therefore, by calculating the expected arrival time by taking into account the degree of littering of the garbage, CPU 12 can more accurately calculate the expected arrival time of each collection site to be visited.

[0056] (4) The CPU 12 calculates the expected arrival time to each collection site to be visited in consideration of the traffic volume from the current position of the garbage truck 30 to the collection site to be visited. Specifically, when calculating the expected arrival time to the next collection site, the CPU 12 calculates the expected arrival time to the next collection site so that the expected arrival time becomes later when the traffic volume from the analysis target site to the next collection site is large than when the traffic volume from the analysis target site to the next collection site is small. Therefore, by calculating the expected arrival time in consideration of the traffic volume in this way, the CPU 12 can more accurately calculate the expected arrival time to each collection site to be visited.

[0057] (5) For example, at a collection site near an apartment building, the amount of garbage in early spring becomes greater than in other time periods due to moving to a new life in early spring, etc. The CPU 12 calculates the expected arrival time at each collection site to be visited in consideration of such differences in the amount of garbage according to the time period. Specifically, when calculating the expected arrival time at the next collection site, the CPU 12 calculates the expected arrival time at the next collection site so that the expected arrival time becomes later when the imaging date and time of the analysis target image is a date and time within the first time period than when the imaging date and time of the analysis target image is a date and time within the second time period. Therefore, by calculating the expected arrival time in consideration of the differences in the amount of garbage according to the time period in this way, the CPU 12 can more accurately calculate the expected arrival time at each collection site to be visited.

[0058] <Modification example>

[0059] The above-described embodiment can be modified as follows. The above-described embodiment and the following modifications can be combined within the range in which no technical inconsistency occurs.

[0060] -The length of a single period is not limited to the example of the above-mentioned embodiment. A single period should be long enough to be able to grasp the average change in the amount of garbage.

[0061] The method of reflecting the first time period and the second time period on the required collection time and even the expected arrival time is not limited to the example of the above embodiment. The reflecting method should at least satisfy the following condition: the expected arrival time to the next collection site becomes later when the imaging date and time of the analysis target image is the time and date within the first time period than when the imaging date and time of the analysis target image is the time and date within the second time period.

[0062] - It is not necessary to reflect the first time period and the second time period in the expected arrival time.

[0063] - When calculating the littering level, it is not necessary to use an already learned model.

[0064] It is not necessary to assign the littering level based on the amount of garbage thrown out of the garbage bag. The littering level can be assigned according to an appropriate definition so that the littering level becomes higher as the degree of littering of the garbage becomes higher, with respect to the garbage thrown out of the garbage bag and littered.

[0065] -The method of reflecting the littering level on the required collection time and even the expected arrival time is not limited to the example of the above embodiment. The reflecting method should at least satisfy the following condition: the expected arrival time to the next collection site becomes later when the littering level at the analysis target site is high than when the littering level at the analysis target site is low.

[0066] - It is not necessary to reflect the littering level in the expected arrival time.

[0067] -The information showing whether the traffic volume is large or small is not limited to whether there is traffic congestion. For example, the traffic volume may be indicated by a plurality of levels by which the traffic volume is rated.

[0068] -The method of reflecting the traffic volume on the travel time and even the expected arrival time is not limited to the example of the above embodiment. The reflection method should at least satisfy the following condition: the expected arrival time to the next collection site becomes later when the traffic volume from the analysis target site to the next collection site is large than when the traffic volume from the analysis target site to the next collection site is small.

[0069] - It is not necessary to reflect traffic volume in the expected arrival time.

[0070] - Using the learned model when calculating the estimated waste volume is not necessary.

[0071] - It is not necessary to specify the amount of garbage based on the number of garbage bags. The amount of garbage can be specified by appropriate definitions.

[0072] -The method of reflecting the estimated garbage amount on the required collection time and even the expected arrival time is not limited to the example of the above embodiment. The reflecting method should at least satisfy the following condition: the expected arrival time to the next collection site becomes later when the estimated garbage amount at the analysis target site is large than when the estimated garbage amount at the analysis target site is small.

[0073] - Regarding the recognition of the analysis target image, when there are multiple identical candidate images, it is not necessary to select the image whose imaging date and time is the latest among these candidate images. If the image is an image taken on a garbage collection day, even an image whose imaging date and time is not the latest is effective information in calculating the estimated garbage amount.

[0074] - The notification information is not limited to the notification image. The notification information can be in any form as long as it can notify the expected arrival time of the collection site to be visited.

[0075] The scheme of outputting notification information to the user terminal 50 is not limited to the example of the above embodiment. For example, the notification information may be automatically notified to the pre-registered user terminal 50 without waiting for a transmission request from the user terminal 50. The notification information may be output to the user terminal 50 using an e-mail or the like.

[0076] -Regarding the data generation processing performed by the control device 72 of the vehicle 70, the following scheme can be adopted: when generating data to be provided, the CPU 74 can analyze the image that the camera 82 has taken when the vehicle 70 has passed the registration location, and can send the image as data to be provided to the server 10 after confirming that the collection site appears in the image.

Claims

1. A garbage collection time notification method, which is performed by: A garbage truck including a receiver that obtains information about the receiver's own current location; an information processing device capable of communicating with the garbage truck, the information processing device storing location information about a plurality of collection sites where the garbage truck collects garbage and a driving route along which the garbage truck sequentially visits the plurality of collection sites; as well as A vehicle capable of communicating with the information processing device, the vehicle comprising a camera for imaging surroundings and the receiver for acquiring information about the current position of the receiver itself, wherein: the vehicle transmitting to the information processing device a plurality of images in which the collection site appears among a plurality of images captured by the camera together with imaging information showing an imaging position and an imaging date and time of each of the plurality of images; and The information processing device executes: acquiring a plurality of the images and the imaging information sent by the vehicle; obtaining information about the current location of the garbage truck; Based on the information about the current position of the garbage truck and the imaging information, identifying a to-be-visited collection site image in which a to-be-visited collection site appears in the plurality of images acquired from the vehicle, the to-be-visited collection site being the collection site that the garbage truck has not passed through in the driving route; calculating an estimated amount of garbage based on the identified image of the collection site to be visited, the estimated amount of garbage being an estimated value of the amount of garbage accumulated at the collection site to be visited; calculating an expected arrival time at a predetermined collection site that the garbage truck passes after the to-be-visited collection site in the driving route so that the expected arrival time at the predetermined collection site becomes later when the estimated garbage amount is large than when the estimated garbage amount is small; and Notification information for notifying the expected arrival time at the scheduled collection site is output.

2. The garbage collection time notification method according to claim 1, wherein: When there are multiple collection site images to be visited for the same collection site to be visited, the information processing device calculates the estimated amount of garbage based on the collection site image to be visited having the latest imaging date and time among the multiple collection site images to be visited for the same collection site to be visited.

3. The garbage collection time notification method according to claim 1, wherein the information processing device executes: calculating a littering level of garbage at the collection site to be visited based on the collection site image to be visited; and The expected arrival time to the predetermined collection site is calculated so that the expected arrival time to the predetermined collection site becomes later when the littering level is high than when the littering level is low.

4. The garbage collection time notification method according to claim 1, wherein the information processing device executes: acquiring traffic information about the travel route from the to-be-visited collection site for which the estimated garbage amount has been calculated to the scheduled collection site; and The expected arrival time to the scheduled collection site is calculated so that the expected arrival time to the scheduled collection site becomes later when the traffic volume from the to-be-visited collection site for which the estimated garbage amount has been calculated to the scheduled collection site is large than when the traffic volume is small.

5. The method for notifying garbage collection time according to claim 1, wherein: The information processing device stores a time period division list, the time period division list showing, for each of the collection sites, a first time period in which the amount of garbage is equal to or greater than a pre-specified setting value and a second time period in which the amount of garbage is less than the setting value; as well as The information processing device calculates the expected arrival time at the predetermined collection site so that the expected arrival time at the predetermined collection site becomes later when the imaging date and time of the image of the collection site to be visited based on which the estimated amount of garbage has been calculated is a date and time within the first time period corresponding to the collection site to be visited for which the estimated amount of garbage has been calculated than when the imaging date and time is a date and time within the second time period.

Images