Evaluation device, evaluation method, and evaluation system

Abstract

To provide an evaluation device, an evaluation method, and an evaluation system for efficiently evaluating a measure.SOLUTION: An evaluation device is configured to: store a first satisfaction level for each group to which a sample object belongs, which is defined for each activity pattern of life activities performed by the sample object and have a first DB that associates the sample object with a group thereof; estimate the life activities and activity patterns of the sample object upon acquiring behavioral data from a sample object terminal; extract, in the first DB, from the first satisfaction level in the estimated life activities for each activity pattern of the group to which the sample object belongs, the first satisfaction level of the estimated activity pattern to register it in a second DB; extract, in the second DB, from the first satisfaction level for each life activity stored for each sample object in the second DB, the first satisfaction level of a specific life activity corresponding to the evaluation object; and calculate, on the basis of the extracted first satisfaction level of the specific life activity, a second satisfaction level on the evaluation object.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an evaluation device, an evaluation method, and an evaluation system that execute evaluation.

Background Art

[0002] The following Patent Document 1 discloses a satisfaction estimation device that estimates satisfaction information of a person belonging to a group such as a family while taking into account information of the group. This satisfaction estimation device is a device that estimates satisfaction information of a person belonging to a group having an area as an activity base, and uses behavior-related data, and is constructed for a person to be estimated for satisfaction belonging to this group. An action identification means for determining action information including information on actions related to communication between the person to be estimated for satisfaction and other persons belonging to this group by a learned action identification model, and based on this action information, Communication score determination means for determining a communication score indicating the degree of communication of the person to be estimated for satisfaction in this group, and satisfaction determination means for determining the satisfaction of the person to be estimated for satisfaction based on this communication score.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the satisfaction estimation device of Patent Document 1 described above indirectly estimates satisfaction from emotions estimated from life activities. Therefore, direct estimation of satisfaction from life activities is not considered. Therefore, an efficient evaluation of the determination of measures and the implemented measures cannot be obtained.

[0005] An object of the present invention is to perform an efficient evaluation of measures. [Means for solving the problem]

[0006] An evaluation device comprising one aspect of the invention disclosed herein is an evaluation device having a processor that executes a program and a storage device that stores the program, wherein it stores a first satisfaction level for each activity pattern of the life activities performed by the sample subject in each group to which the sample subject belongs, and is able to access a first database that associates the sample subject with the group to which the sample subject belongs, and when the processor obtains behavioral data indicating the behavior of the sample subject from the sample subject's terminal capable of detecting such behavioral data, it performs an estimation process to estimate the life activities and activity patterns of the sample subject based on the behavioral data, and stores in the first database the estimated by the estimation process The method is characterized by performing the following steps: a registration process in which the first satisfaction level for each activity pattern of the group to which the sample subject belongs is extracted from the first satisfaction levels for each activity pattern of the [Effects of the Invention]

[0007] According to a typical embodiment of the present invention, it is possible to evaluate the effectiveness of measures. Other issues, configurations, and effects not mentioned above will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0008] [Figure 1]Figure 1 is an explanatory diagram showing an example of the system configuration of the evaluation system. [Figure 2] Figure 2 is an explanatory diagram showing an example of an activity list database. [Figure 3] Figure 3 is an explanatory diagram showing an example of a database. [Figure 4] Figure 4 is an explanatory diagram showing an example of a QoL calculation database. [Figure 5] Figure 5 is an explanatory diagram showing an example of the identification code management table shown in Figure 4. [Figure 6] Figure 6 is an explanatory diagram showing an example of a derived QoLDB. [Figure 7] Figure 7 is an explanatory diagram showing an example of a list of accessible information. [Figure 8] Figure 8 is an explanatory diagram showing the correspondence between a sample participant's daily life activities and their activity environment over time. [Figure 9] Figure 9 is a block diagram showing an example of the hardware configuration of the evaluation device. [Figure 10] Figure 10 is an explanatory diagram showing example screen 1 of a sample participant's terminal. [Figure 11] Figure 11 is an explanatory diagram showing example screen 2 of a sample participant's terminal. [Figure 12] Figure 12 is an explanatory diagram showing example screen 3 of a sample participant's terminal. [Figure 13] Figure 13 is an explanatory diagram showing example screen 4 of a sample participant's terminal. [Figure 14] Figure 14 is a sequence diagram showing an example of the database generation process performed by the database generation unit. [Figure 15] Figure 15 is a sequence diagram showing an example of the process for calculating the target QoL value. [Figure 16] Figure 16 is an explanatory diagram illustrating examples of its application in park management. [Figure 17] Figure 17 is a conceptual diagram illustrating the urban management cycle realized by the evaluation system. [Figure 18]FIG. 18 is an explanatory diagram showing an example of the relationship between administrative services and measures for the elderly and the expected results.

Mode for Carrying Out the Invention

[0009] It is important to evaluate the effects on urban policies such as the maintenance and management of infrastructure, urban planning, and the provision of public services. In particular, in recent years in Japan, the declining birthrate and aging population, as well as the aging of infrastructure, have become prominent, and the importance of evaluating the effects of urban operation within limited budgets and human resources has been increasing.

[0010] The indicators adopted in the effect evaluation are used for grasping the current situation and setting goals when formulating policies by government agencies and local governments, as well as for visualizing the effects after the implementation of the policies, and for justifying and giving meaning to the provision of infrastructure and public services. Entities such as the government and local governments determine the selection of infrastructure and public services and the operation policy based on these indicator values, and operate the region after obtaining the consent of stakeholders related to the region such as residents and corporations. These have become the mainstream of policy-making and local government operation as a methodology for urban operation called EBPM (Evidence Based Policy Making).

[0011] For example, local governments in Japan have started formulating KPIs (Key Performance Indicators) as various effect evaluation values related to policy formulation, formulating policies by setting numerical targets for KPIs, and proceeding with the verification of their effects. Furthermore, the government is leading the attempt to organize, comprehensively summarize, visualize, and utilize indicators for objectively grasping the situation of cities in urban planning.

[0012] In such attempts, as evaluation indicators for cities and policies, mainly indicators such as the number of facilities, green area, and accommodation capacity in parks, hospitals, and public facilities are selected. These indicators are physical quantities. That is, these indicators can be objectively quantified and have the advantage of being able to clearly conduct effectiveness evaluations such as comparison between cities and setting of target values and thresholds. However, it is not always the case that high values of these indicators coincide with residents enjoying a comfortable, vibrant, and high-quality life.

[0013] On the other hand, in recent years, methods for evaluating residents' satisfaction with policies and administrative measures have been explored. For example, the subjective satisfaction of residents obtained through questionnaires and the like is aggregated and made into an indicator for evaluating cities and policies. According to the indicators derived from these methods, it becomes possible to evaluate cities and policies from the perspective of the quality of residents' lives and satisfaction.

[0014] In these methods, data is obtained through questionnaire surveys of residents. Since questionnaire surveys are in the form of residents answering a large number of questions, the burden on residents is large. Also, a lot of budget and human resources are required for conducting questionnaires. Therefore, the problem is that the implementation frequency cannot be increased. On the other hand, it is desirable that the effectiveness evaluation of urban services be carried out regularly and continuously during the process from service design, before service introduction, after service introduction, until it becomes established, and a questionnaire survey is required each time.

[0015] Developing and putting into practical use a tool that can constantly observe the life and satisfaction of each individual living in the city and new urban evaluation indicators based on it is considered essential for leading to urban management that achieves both optimization of society as a whole and improvement of residents' life satisfaction.

[0016] Quality of Life (QoL) is an indicator related to life satisfaction and fulfillment. QoL is a concept devised as an indicator to evaluate human health not only from the perspective of physical ability, but also including the quality of daily life, such as psychology, social relationships, and the surrounding activity environment. For example, the World Health Organization (WHO) QoL assessment method is an international indicator for measuring QoL. This QoL assessment method derives a QoL value from responses to 100 or 26 questions based on the above perspectives, selected on a 5-point scale. The QoL value derived using this QoL assessment method can be used to estimate the perceived level of life satisfaction and fulfillment.

[0017] The following embodiment describes an evaluation system that extends this concept to the field of urban planning. In this embodiment, the evaluation system does not impose a burden on residents when designing and conducting questionnaires for subjective evaluation each time. If a single QoL survey and behavioral history data (where, how much, under what conditions, and what was done) can be obtained, the system automatically acquires the behavioral history data of the target group and evaluates the satisfaction of people living in the city using the QoL value of life activities 201. This evaluation system then quantitatively calculates the QoL value of life activities 201 for people living in the city and evaluates urban planning, management, and policies by calculating objective QoL values ​​related to urban planning, management, and policies based on this QoL value of life activities 201.

[0018] <Example of a system configuration for an evaluation system> Figure 1 is an explanatory diagram showing an example of the system configuration of the evaluation system. The evaluation system 10 includes an evaluation device 100. The evaluation device 100 is connected to a sample subject terminal 141, an external site 150, and a local government servicer terminal 161 via a network 170 such as the Internet, LAN (Local Area Network), or WAN (Wide Area Network).

[0019] The sample subject terminal 141 is a communication terminal owned by the sample subject 140, and is, for example, a smartphone, wearable device, tablet, or personal computer. The sample subject terminal 141 acquires the behavioral history data of the sample subject 140 and transmits it to the evaluation device 100.

[0020] External sites 150 include, for example, a map server 151 and a weather server 152. Map server 151 transmits map data upon request from evaluation device 100. Map server 151 also maintains facility information on the map data, such as government agencies, parks, convenience stores, restaurants, theme parks, fitness clubs, and office buildings where companies are located. Map server 151 also maintains routes and schedules for public transportation such as trains and buses.

[0021] When the map server 151 receives latitude and longitude from, for example, the evaluation device 100 or the sample subject terminal 141, it returns two-dimensional or three-dimensional map data containing the latitude and longitude, as well as the facility name and address corresponding to the latitude and longitude.

[0022] The weather server 152 transmits weather information upon request from the evaluation device 100. For example, the weather server 152 returns weather information indicating the climate, weather, or weather conditions at the time of the request from the evaluation device 100 or the sample subject terminal 141 to the evaluation device 100 or the sample subject terminal 141.

[0023] The municipal service terminal 161 performs operations such as adding, changing, or deleting data in the evaluation device 100, based on the operation of the municipal servicer 160.

[0024] The evaluation device 100 includes a generation unit 101, a list generation unit 102, a QoL calculation unit 103103, a QoL calculation DB 120, and a derived QoL DB 130.

[0025] The generation unit 101 generates various data and estimates the QoL value of daily living activities. The QoL value of daily living activities is an index value that indicates how satisfied the sample subjects 140 are with the daily living activities they performed. Specifically, for example, the generation unit 101 includes an activity list DB 111, a database 112, a question generation unit 114, a database generation unit 115, and an estimation unit 116. Here, the activity list DB 111 will be explained in detail.

[0026] [Activity List DB111] Figure 2 is an explanatory diagram showing an example of the activity list DB111. The activity list DB111 is a database that lists daily living activities, and specifically includes, for example, daily living activities 201, activity environments 202, and questions 203 to confirm the QoL value of daily living activities 201. Daily living activities 201 are information that shows what activities the sample subject 140 is currently doing in their life, and are selected by the sample subject 140.

[0027] The activity environment 202 is a set of environmental conditions 221-225 that indicate the activity environment and evaluation conditions under which the sample subject 140 performed the daily activities 201 entered from the sample subject terminal 141, and is selected by the sample subject 140. Environmental conditions 221-225 are examples, and other environmental conditions (for example, for whom) may be included, and any of the environmental conditions 221-225 may be excluded.

[0028] Question 203, which confirms the QoL value of daily living activity 201, is an example of a question used in calculating QoL values ​​in the WHO QoL Brief. Figure 2 shows an example from WHO, but it is not limited to this, and the most appropriate QoL indicator will be adopted as needed. Question 203 within Question 203, which confirms the QoL value of daily living activity 201, is transmitted as question data to the sample subject terminal 141 via the network 170. The sample subject terminal 141 is answered by the sample subject 140 using a multiple-choice format, and the answer results are transmitted as answer data to the evaluation device 100.

[0029] The question generation unit 114 generates question data to determine the calculation rules before calculating the QoL value of the daily living activity 201. Specifically, for example, the question data consists of the daily living activity 201 performed by the sample subject 140, the activity environment 202 in which the sample subject 140 performed the daily living activity 201, and a question 203 to confirm the QoL value of the daily living activity 201, as shown in Figure 2. When the question generation unit 114 receives a survey trigger from the sample subject terminal 141, it sends the generated question data to the sample subject terminal 141 that sent the survey trigger.

[0030] The database generation unit 115 generates the database 112. Specifically, for example, the database generation unit 115 collects response data to the question data generated by the question generation unit 114 from the sample subject terminal 141, and analyzes the environmental conditions 221-225 of the daily activities 201 and preferred activity environments 202 based on the responses.

[0031] The database generation unit 115 then generates a column vector of QoL values ​​for each activity pattern under environmental conditions 221-225 that define the activity environment 202, for each sample subject 140 in each daily activity 201. This column vector is a vector whose elements are the QoL values ​​of activity patterns P1, P2, P3, ... The database generation unit 115 clusters the column vectors so that those with close Euclidean distances belong to the same cluster.

[0032] Initially, there are as many clusters as there are column vectors, and the database generation unit 115 sequentially clusters the column vector pairs that have the shortest Euclidean distance. The database generation unit 115 calculates the average value of each element of the multiple column vectors that belong to the same cluster, or obtains the median or mode, to generate a column vector that represents the cluster and makes it the target of clustering.

[0033] The database generation unit 115 performs this clustering until the number of clusters reaches a predetermined number, or until the number of column vectors belonging to each cluster exceeds a predetermined number. As a result, a cluster-specific QoL management table is generated for each life activity 201 (see Figure 3).

[0034] Furthermore, the database generation unit 115 associates the responding sample subjects 140 with their respective clusters for each life activity 201. This generates a cluster management table for each life activity 201 (see Figure 3).

[0035] [Database 112] Figure 3 is an explanatory diagram showing an example of database 112. Database 112 is generated by the database generation unit 115. Database 112 has a cluster-specific QoL management table 300 and a cluster affiliation management table 310 for each life activity 201. In Figure 3, as an example, the cluster-specific QoL management table 300 and the cluster affiliation management table 310 are shown when the life activity 201 is work.

[0036] The cluster-based QoL management table 300 is a table showing the results of clustering the sample subjects 140 according to their daily activities 201, and has two fields: activity pattern 301 and cluster-based QoL value 302. Activity pattern 301 is the type of activity performed by the sample subjects 140 under environmental conditions 221-225. The value of activity pattern 301, "P#" (# is a number), is sometimes denoted as activity pattern P#. If activity patterns P1, P2, ... are not distinguished, they are referred to as activity pattern 301.

[0037] For example, in activity pattern P1 where the activity 221 is "work," the environmental condition 221 (where) is "XX ward," the environmental condition 222 (what kind of facility) is "workplace," the environmental condition 223 (by what means) is "meeting," the environmental condition 224 (with whom) is "colleagues," and the environmental condition 225 is "2 hours."

[0038] For example, activity pattern P2, where life activity 221 is "work," is an activity pattern where environmental condition 221 (where) is "△△ city," environmental condition 222 (what kind of facility) is "shared office," environmental condition 223 (by what means) is "PC," environmental condition 224 (with whom) is "alone," and environmental condition 225 is "3 hours."

[0039] The cluster-specific QoL value 302 is a set of QoL values ​​for each activity pattern 301, and exists for each cluster. The cluster-specific QoL value 302 is a cluster column vector obtained by calculating the average value of each element of the multiple column vectors belonging to the cluster, or by obtaining the median.

[0040] Furthermore, the relationship between the activity pattern 301 and the cluster-specific QoL value 302 may be defined not only in the cluster-specific QoL management table 300, but also in a function. Specifically, for example, the database generation unit 115 may perform machine learning using the activity pattern 301 as the ground truth data and the column vector of QoL values ​​belonging to the cluster as the training data, and define the relationship between the activity pattern 301 and the cluster-specific QoL value 302 using a machine learning model.

[0041] The cluster management table 310 has two fields: cluster ID 311 and sample subject ID 312. Cluster ID 311 is identification information that uniquely identifies a cluster. Sample subject ID 312 is identification information that uniquely identifies sample subject 140. This makes it possible to determine which cluster sample subject 140, identified by sample subject ID 312, belongs to.

[0042] Returning to Figure 1, the estimation unit 116 calculates estimated QoL values ​​for each activity 201 after generating the database 112. Specifically, for example, the estimation unit 116 obtains the sample subject ID 312 and detection data from the sample subject terminal 141, which can be a smartphone, wristband sensor, or smartwatch. The detection data is, for example, data detected by sensors built into the sample subject terminal 141 (such as acceleration, latitude and longitude, voice such as conversation and ambient sounds, and heart rate).

[0043] Furthermore, the estimation unit 116 obtains information on attendees who have given their consent from the sample subject terminal 141. For example, suppose that event information for a certain date, time, and facility is registered in the schedule management software on the sample subject terminal 141. Suppose that another sample subject 140, with sample subject ID 312, is registered as an attendee for that event. At the date and time of the event, the sample subject terminal 141 includes the other sample subject 140's sample subject ID 312 as attendee information in the event information and transmits it to the evaluation device 100 as detection data. As a result, the estimation unit 116 can obtain the attendee information from the received event information.

[0044] Furthermore, the estimation unit 116 acquires environmental information such as location and weather information obtained from public websites when the daily activity 201 is performed, as well as service information (such as point accrual) obtained at the location where the daily activity 201 is performed.

[0045] The sample subject ID 312, detection data, environmental information, service information, and sample subject terminal 141 are referred to as the behavioral data of sample subject 140.

[0046] The estimation unit 116 then refers to the acquired behavioral data to estimate the daily activities 201 and the activity patterns 301 under the environmental conditions 221-225 when performing the daily activities 201.

[0047] Specifically, the estimation unit 116 estimates which category the daily activities 201 of the sample subject 140 fall into, based on behavioral data from the sample subject terminal 141.

[0048] For example, the estimation unit 116 determines which of the following categories the lifestyle activity 201 of the sample subject 140 during a predetermined period of time corresponds to, based on the heart rate included in a series of detection data acquired within that predetermined period. For example, if the heart rate is a value indicating sleep, the lifestyle activity is determined to be sleep; if the heart rate is a value indicating eating, the lifestyle activity is determined to be eating.

[0049] Furthermore, the estimation unit 116 may estimate the lifestyle activity 201 using not only heart rate but also latitude and longitude information, time of day, and facility information. For example, if the facility identified by the facility information is a fitness club, the detected heart rate is a value indicating exercise, the latitude and longitude information indicates the location of the fitness club, and the time the detected data was acquired is during the fitness club's business hours and outside of the sample subject 140's working hours, the estimation unit 116 will identify the lifestyle activity 201 as "leisure."

[0050] Furthermore, for example, the estimation unit 116 may estimate which category the lifestyle activity 201 of the sample subject 140 falls into, based on the movement history of the location identified by the latitude and longitude information of a series of detection data acquired within a predetermined time, the movement speed, and the route of the public transport on the map data corresponding to that location. For example, if the acquisition time of the detection data is during the operating hours of the railway, the movement history of the latitude and longitude information is a railway route, and the movement speed is the speed of the railway, the generation unit 101 will identify the lifestyle activity 201 as "movement".

[0051] Alternatively, the estimation unit 116 may generate a machine learning model by performing machine learning in advance, using behavioral data from the sample subject terminal 141 as training data and the daily activities 201 selected by the sample subject 140 at that time as ground truth data, and then estimate the daily activities 201 by inputting the behavioral data from the sample subject terminal 141 into this machine learning model.

[0052] In this way, the estimation unit 116 can estimate which category the daily activities 201 of the sample subject 140 fall into, based on the behavioral data from the sample subject terminal 141.

[0053] Furthermore, the estimation unit 116 estimates which of the behavioral patterns 301 the sample subject 140 corresponds to, based on the behavioral data from the sample subject terminal 141. Since the behavioral pattern 301 is a type of environmental condition 221-225, the estimation unit 116 uses the behavioral data to specifically identify the environmental conditions 221-225.

[0054] Environmental condition 221 (where) is identified, for example, by latitude and longitude information in the behavioral data. Environmental condition 222 (what kind of facility) is identified by facility information on map data located at the location indicated by the latitude and longitude information in the behavioral data.

[0055] The environmental condition 223 (by what means) is identified, for example, by the environmental condition 222 and the voice data in the behavioral data. For example, if the environmental condition 222 indicates that the facility is the "workplace" of the sample subject 140, and the behavioral data includes voice data such as "We're having a meeting," the estimation unit 116 performs speech recognition on the voice data, thereby identifying the environmental condition 223 as "meeting." Alternatively, if the voice data contains speech recognition of utterances from multiple people, the estimation unit 116 may also identify the environmental condition 223 as "meeting."

[0056] Regarding environmental condition 224 (who with), for example, if there is event information in the behavioral data that includes the aforementioned information about those present, it will be identified by the event information.

[0057] For example, if information about a co-existing person exists in the behavioral data, and the workplace information of the individual and the co-existing person matches, then environmental condition 224 is identified as "colleague". Workplace information is registered for each sample subject ID 312 in the QoL calculation DB 120.

[0058] Environmental information 225 (how long) is determined by the estimated start and end times of the lifestyle activity 201.

[0059] In this way, the estimation unit 116 can estimate which of the behavioral patterns 301 of the sample subject 140 corresponds to, based on the behavioral data from the sample subject terminal 141.

[0060] The estimation unit 116 then refers to the cluster management table 310 of the estimated lifestyle activity 201 and identifies the cluster ID 311 of the cluster to which the sample subject 140 belongs from the sample subject ID 312 included in the behavioral data. The estimation unit 116 then obtains the cluster-specific QoL value 302 of the estimated activity pattern 301 from the column of cluster-specific QoL values ​​302 of all activity patterns 301 of the cluster identified by cluster ID 311 as the estimated QoL value of the sample subject 140.

[0061] For example, if sample subject ID 312 is "00001", then cluster ID 311 is "A", and therefore sample subject 140 belongs to cluster A. Also, if the activity pattern 301 is identified as "P2" based on the behavioral data, then the cluster-specific QoL value 302 for cluster A in the case of activity pattern 301 "P2" is "5". Therefore, the estimation unit 116 obtains "5" as the estimated QoL value for the current life activity 201, which is "work".

[0062] The estimation unit 116 stores the estimated activity pattern 301, behavioral data, and QoL values ​​of the life activities 201 obtained as estimated values ​​in the QoL calculation DB 120 as logs.

[0063] The QoL calculation DB120 is a database that holds the data necessary for calculating the QoL values ​​of 201 daily living activities. The QoL calculation DB120 will be explained in detail below.

[0064] [QoL Calculation DB120] Figure 4 is an explanatory diagram showing an example of the QoL calculation DB 120. The QoL calculation DB 120 has QoL calculation source data 400 for each of the 140 sample subjects and an identification code management table 403. The QoL calculation source data 400 has upper layer data 401 and lower layer data 402.

[0065] The upper layer data 401 defines the sample subject ID 312, demographics 411, and psychographics 412 at line number 001. Demographics 411 are identification codes that identify demographic attributes such as gender, age, and occupation. Psychographics 412 are identification codes that indicate psychological attributes such as hobbies, preferences, inclinations, and religion. The sample subject 140 is characterized by at least one of the demographics 411 and psychographics 412. In addition, relationships with other sample subjects 140 (relatives, friends, colleagues, etc.) may also be included. In this case, identification codes indicating the relationship with other sample subjects 140 and the sample subject IDs 312 of the other sample subjects 140 are defined in the upper layer data 401. Furthermore, regarding occupation, although not illustrated, workplace information including facility information (including latitude and longitude information) is included.

[0066] The lower layer data 402 defines the availability status 420, the QoL value 421 for daily living activities 201, daily living activities 422, means of living 423, number of people living 424, start time of daily living activities 425, end time of daily living activities 426, latitude and longitude information 427, facilities 428, and service information 429, starting from row 002.

[0067] Figure 5 is an explanatory diagram showing an example of the identification code management table 403 shown in Figure 4. The identification code management table 403 is a table that defines the values ​​of the identification codes 502 for each of the categories: daily living activities 422, means of living 423, number of residents 424, facilities 428, and service information 429.

[0068] Returning to Figure 4, the QoL value 421 for daily living activity 201, daily living activity 422, means of living 423, number of people living 424, start time of daily living activity 425, end time of daily living activity 426, latitude and longitude information 427, facility 428, and service information 429 are stored in the QoL calculation DB 120 as behavioral history data for the sample subjects 140.

[0069] The availability status 420 indicates whether the sample subject 140 is willing to provide the lower-level data 402 to the evaluation device 100 for each daily living activity 422. The availability status 420 can be changed for each daily living activity 422 by access from the sample subject terminal 141. The evaluation device 100 can extract and utilize the data for the row numbers of daily living activities 422 for which the availability status 420 is set to "OK" for the calculation of the target QoL value, but cannot extract the data for the row numbers of daily living activities 422 for which the availability status 420 is set to "NG" for the calculation of the target QoL value.

[0070] The QoL value 421 for daily living activity 201 is the cluster-specific QoL value 302 obtained for daily living activity 422 as an estimated value from the estimation unit 116.

[0071] Life activity 422 is a category 501 representing life activity 201 estimated based on behavioral data from the sample participant terminal 141, and is designated by identification code 502.

[0072] The means of living 423 is a category 501 that indicates how the daily activities 201 were carried out, and is specified by an identification code 502. For example, the estimation unit 116 estimates how the means of living 423 of the sample subject 140 are carried out (e.g., walking, public transport, automobile) based on the movement history of the location identified by the latitude and longitude information of a series of detection data acquired within a predetermined time, the movement speed, and the route of the public transport on the map data corresponding to that location. For example, if the acquisition time of the detection data is during the operating hours of a railway, the movement history of the latitude and longitude information is a railway route, and the movement speed is the speed of a railway, the estimation unit 116 identifies the means of living 423 as "public transport".

[0073] The number of people living together 424 is a category 501 indicating how many people carried out the living activities 201, and is specified by an identification code 502. For example, the estimation unit 116 estimates the number of people living together 424 by using the information of people present if there is information about people present in the behavior data, using the audio data if there is audio data about people present, and using the latitude and longitude information and facility information of the behavior data of its own and other sample subject terminals 141 if there is such latitude and longitude information and facility information from the behavior data of the sample subject terminals 141 of the people present. The estimation unit 116 may also use the environmental conditions 224 as the number of people living together 424.

[0074] The start time of daily activity 425 is the estimated start time of daily activity 201 based on behavioral data from the sample participant's terminal 141.

[0075] The end time of the daily activity 426 is the estimated end time of the daily activity 201 based on behavioral data from the sample participant's terminal 141. In other words, the start time of the daily activity 425 and the end time of the daily activity 426 correspond to the environmental conditions 225.

[0076] The latitude and longitude information 427 is acquired as behavioral data from the sample subject's terminal 141 and corresponds to the environmental conditions 221.

[0077] Facility 428 is a category 501 obtained from the facility information within the behavioral data from the sample participant terminal 141, and is specified by identification code 502. Facility 428 corresponds to environmental condition 222.

[0078] Service information 429 is category 501, obtained as service information within the behavioral data from the sample subject terminal 141, and is specified by identification code 502.

[0079] In this way, the estimation unit 116 generates the means of living 423, the number of people living 424, the start time of living activities 425, the end time of living activities 426, latitude and longitude information 427, facilities 428, and service information 429 based on the QoL value 421 and living activities 422 of the living activities 201, as well as the behavioral data, and registers them in the QoL calculation DB 120 as behavioral history data. The estimation unit 116 may also register the behavioral data as is as behavioral history data.

[0080] Returning to Figure 1, the Derived QoLDB130 is a database that holds the data necessary for deriving the target QoL value. The Derived QoLDB130 will be explained in detail.

[0081] [Derived QoLDB] Figure 6 is an explanatory diagram showing an example of a derived QoLDB 130. The derived QoLDB 130 includes a list of referenceable information 131 and a list of calculation methods 132, as well as derived QoL data 600 for each sample subject 140. The derived QoL data 600 consists of upper layer data 601 and lower layer data 602.

[0082] The upper layer data 601 defines the sample subject ID 312 of sample subject 140 at line number 001. The upper layer data 601 may also be the ID of a cluster of multiple sample subjects 140 that share common attributes, rather than the sample subject ID 312 of sample subject 140.

[0083] The lower layer data 602 defines the evaluation target 621, the model 622, and the model parameters 623 from line number 002 onwards. The evaluation target 621 is an identification code for the viewpoint to be evaluated by the evaluation device 100. In this embodiment, for example, if the evaluation target 621 has the identification code "000", it is defined as "daily life activities in XX Park", and if the evaluation target 621 has the identification code "001", it is defined as "daily life activities of women participating in an event planned at facility ZZ".

[0084] Model 622 is an identification code that uniquely identifies the function used to calculate the target QoL value for the daily living activity 201 defined in evaluation target 621. The correspondence between the function and the identification code is defined in calculation method list 132.

[0085] Model parameter 623 is a parameter that is input to the function identified in model 622. Since the level of satisfaction and fulfillment felt from the relevant life activity 201 differs among the sample subjects 140, model parameter 623 is set for each sample subject 140. Model 622 and model parameter 623 can be modified by the municipal service terminal 161 or the sample subject terminal 141.

[0086] The calculation method list 132 specifies model 622 and function definition 630 in each row. Function definition 630 defines a function to calculate the target QoL value related to the daily living activity 201 defined in evaluation target 621. The correspondence between evaluation target 621 and function definition 630 can be arbitrarily changed from the municipal service terminal 161.

[0087] Figure 7 is an explanatory diagram showing an example of a referenceable information list 131. The referenceable information list 131 is data that defines the evaluation target 621 and has a reference target information area 701 and a reference condition information area 702.

[0088] The referenced information area 701 includes, for example, the evaluation target 621, male 710, female 711, occupation 712, reference occupation information 713, time 714, reference time information 715, latitude and longitude 716, reference geographic information 717, facility 718, and reference facility information 719.

[0089] Male 710 is an identification code that indicates whether or not males are included among the participants in the life activity defined in evaluation subject 621. If it is "000", no males are included, and if it is "001", males are included.

[0090] "Women 711" is an identification code that indicates whether or not women are included among the participants in the life activities defined in "Evaluation Subject 621". If it is "000", women are not included, and if it is "001", women are included.

[0091] Occupation 712 is an identification code that indicates whether or not the occupation of the participant in the life activity defined in the evaluation target 621 is referenced. The evaluation device 100 identifies the occupation by not referring to the reference occupation information 713 if the value of occupation 712 is "000", and by referring to the reference occupation information 713 if it is "001".

[0092] Reference occupation information 713 defines the reference condition number 721 defined in the reference condition information area 702. For example, if it is "005", then the reference condition 723 identifies "company employee, self-employed" which corresponds to the reference condition number 721 "005" at line number 006 of the reference condition information area 702.

[0093] Time 714 is an identification code that indicates whether or not the activity time of the daily living activity 201 defined in the evaluation target 621 is referenced. If the value of time 714 is "000", the evaluation device 100 does not refer to the reference time information 715, and if it is "001", it refers to the reference time information 715 to identify the activity time of the daily living activity.

[0094] The reference time information 715 defines the reference condition number 721 defined in the reference condition information area 702. For example, if the value of the reference time information 715 is "003", then the reference condition 723 will be "2021.6.10.13:30,2021.6.10.15:30", which corresponds to "003", the reference condition number 721 of line number 004 in the reference condition information area 702.

[0095] The latitude and longitude 716 is an identification code that indicates whether or not the activity location of the life activity 201 defined in the evaluation target 621 is referenced. The evaluation device 100 identifies the activity location of the life activity 201 by not referring to the reference geographic information 717 if the value of latitude and longitude 716 is "000", and by referring to the reference geographic information 717 if it is "001".

[0096] Reference geographic information 717 defines reference condition number 721 defined in reference condition information area 702. For example, if the value of reference geographic information 717 is "001", then as reference condition 723, polygon data for the latitude and longitude of the four vertices of a rectangle corresponding to reference condition number 721 "001" in line 002 of reference condition information area 702 is identified as "(35.709,139.761),(35.711,139.760),(35.712,139.762),(35.711,139.762)". Polygon data is obtained, for example, from map server 151.

[0097] Facility 718 is an identification code that indicates whether or not a facility where the daily living activity 201, as defined in the evaluation target 621, was performed was referenced. If the value of facility 718 is "000", the evaluation device 100 does not refer to the reference facility information 719, and if it is "001", it refers to the reference facility information 719 to identify the facility where the daily living activity 201 was performed.

[0098] Reference facility information 719 defines reference condition number 721, which is defined in reference condition information area 702. As reference condition 723, text data such as the facility name, address, and facility overview, which are defined in reference condition information area 702, are identified.

[0099] The reference condition information area 702 is an area that defines reference conditions and includes a reference condition number 721, a condition definition 722, and a reference condition 723, which are defined in the reference occupation information 713, reference time information 715, reference geographic information 717, and reference facility information 719 in the reference target information area 701. The condition definition 722 is text data that becomes the name of the reference condition 723.

[0100] Returning to Figure 1, the list generation unit 102, based on operations from the municipal service terminal 161, references the activity history data (QoL value 421 for daily activities 201, daily activities 422, means of living 423, number of people living 424, start time of daily activities 425, end time of daily activities 426, latitude and longitude information 427, facilities 428, and service information 429) from the QoL calculation DB 120 to generate a list of referable information 131. This allows the user of the municipal service terminal 161 to create an appropriate list of referable information 131.

[0101] The QoL calculation unit 103 refers to the QoL calculation DB 120 and the calculation method list 132, extracts the QoL values ​​421 for the daily activities 201 corresponding to the evaluation target 621 from the QoL calculation DB 120, and calculates the target QoL value according to the calculation method in the calculation method list 132. The evaluation device 100 transmits the calculated target QoL value to the municipal service terminal 161.

[0102] [QoL value] Here, we will explain the QoL value in detail. The QoL value calculated by the evaluation device 100 includes the QoL value 421 for the daily activity 201 and the target QoL value. The QoL value 421 for daily activity 201 is, as mentioned above, an index value that indicates how satisfied the sample subject 140 is with the daily activity 201 that they performed. In other words, the QoL value 421 for daily activity 201 is, as mentioned above, the cluster-specific QoL value 302 obtained for daily activity 422 as an estimated value from the estimation unit 116.

[0103] On the other hand, the objective QoL value is an index value that indicates how satisfied the group of 140 sample subjects who performed the life activity 201 defined in evaluation target 621 are. The objective QoL value is calculated by substituting the QoL value 421 of the life activity 201 defined in evaluation target 621 and the model parameters 623 of the 140 sample subjects who performed the life activity 201 into the function defined in function definition 630.

[0104] The QoL calculation unit 103 calculates a target QoL value from the QoL values ​​421 of the life activities 201 estimated by the estimation unit 116. The target QoL value is a QoL value used to evaluate the effectiveness of life activities 201 defined by evaluation targets 621, such as specific policies, specific public services, people with disabilities, gender, age groups, and other specific attributes of urban life.

[0105] Specifically, for example, the QoL calculation unit 103 extracts the QoL values ​​421 of the daily activities 201 of 140 sample subjects that meet the objective from the QoL calculation DB 120, extracts a function definition 630 that meets the objective from the calculation method list 132, and substitutes the extracted QoL values ​​421 of the daily activities 201 into the extracted function definition 630. This allows the QoL calculation unit 103 to calculate the objective QoL value.

[0106] [Example of calculating the target QoL value for evaluation target 621] Here, we will explain Example 1 of calculating the target QoL value for evaluation target 621. Here, evaluation target 621 is defined as "Daily life activities in XX Park," which has the identification code "000." In the case of "Daily life activities in XX Park," a QoL value of 421 for daily life activities 201 performed in XX Park is required. For this reason, the latitude and longitude 716 of line number 002 in the reference target information area 701 is set to "001." In addition, the reference condition number 721 referenced by the reference geographic information 717 of line number 002 is polygon data identified by the four latitudes and longitudes (reference condition 723) that form the four vertices of a rectangle indicating the location of XX Park.

[0107] Based on the four latitudes and longitudes of XX Park identified by this reference condition 723, the QoL calculation unit 103 refers to the QoL calculation DB 120 and extracts the QoL value 421 of the lifestyle activity 201 with the same row number as the latitude and longitude information 427 included in the four latitudes and longitudes of XX Park from the lower-level data 402 of the sample subject 140 as the QoL value 421 that matches the purpose, if the usability status 420 is "OK".

[0108] Furthermore, the QoL calculation unit 103 specifies a function definition 630 from the calculation method list 132. Specifically, for example, in the model 622 for the lower layer data 602 of each sample subject 140, the identification code "000" is defined as the function definition 630 that identifies a function definition 630 that defines a weighted averaging, corresponding to the identification code "000" of the evaluation target 621.

[0109] In this case, the QoL calculation unit 103 uses the function definition 630 of identification code "000" as the function definition 630 that matches the purpose, and calculates a weighted average of the QoL values ​​421 of the extracted daily living activities 201 as the purpose QoL value for "daily living activities in XX Park".

[0110] Furthermore, a model parameter 623 is set in the lower-level data 602 for each of the 140 sample subjects. In the example in Figure 6, the model parameter 623 is set to "3.00" in row 002 of the evaluation subject 621, whose sample subject ID 312 is "ID00001", and whose identification code is "000". Therefore, when applying the QoL value 421 of the daily activity 201 of sample subject 140, whose sample subject ID 312 is "ID00001", to the function definition 630 for the identification code "000", the model parameter 623, "3.00", is applied as the weight of the function definition 630.

[0111] This section describes example 2 of calculating the target QoL value for evaluation target 621. Here, evaluation target 621 is defined as "the daily life activities of women participating in an event planned at facility ZZ," which has the identification code "001." In the case of "the daily life activities of women participating in an event planned at facility ZZ," a QoL value of 421 for daily life activities 201 conducted within facility ZZ is required. For this reason, the latitude and longitude 716 of line number 002 in the reference target information area 701 is set to "001." In addition, the reference condition number 721 referenced by the reference geographic information 717 of line number 002 is polygon data identified by the four latitudes and longitudes (reference condition 723) that form the four vertices of a rectangle indicating the location of facility ZZ.

[0112] Furthermore, the QoL value 421 of the lifestyle activity 201 performed during the activity time of "lifestyle activities of women participating in events planned at facility ZZ" is also required. For this reason, the time 714 of line number 002 in the reference target information area 701 is set to "001". Also, the reference condition number 721 referenced by the reference time information 715 of line number 002 is, for example, the reference condition 723 that indicates the time period of line number 004 in the reference condition information area 702.

[0113] Additionally, the QoL value of 421 for the women's lifestyle activity 201, which is the target of participation in the "Women's lifestyle activities of the events planned at facility ZZ," is also required. For this reason, the woman 711 in line 002 of the referenced information area 701 is set to "001," and the man 710 in line 002 of the referenced information area 701 is set to "000."

[0114] Based on the four latitudes and longitudes of facility ZZ, the time zone, and the identification code "001" indicating that female 711 are included in the reference condition 723, the QoL calculation unit 103 refers to the QoL calculation DB 120 and extracts the QoL value 421 of the life activity 201 with the same row number as the time zone of the event planned at facility ZZ, which is included in the four latitudes and longitudes of facility ZZ, from the lower-level data 402 of the sample subject 140 as the QoL value 421 that matches the purpose, if the availability status 420 is "OK".

[0115] Furthermore, the QoL calculation unit 103 specifies a function definition 630 from the calculation method list 132. Specifically, for example, in the model 622 for the lower layer data 602 of each sample subject 140, the identification code "001" is defined as the function definition 630 that identifies a function definition 630 that defines a weighted mean square.

[0116] In this case, the QoL calculation unit 103 uses the function definition 630 of identification code "001" as the function definition 630 that matches the purpose, and calculates the weighted square mean of the QoL values ​​421 of the extracted life activities 201 as the purpose QoL value for "life activities of women participating in events planned at facility ZZ".

[0117] Furthermore, a model parameter 623 is set in the lower-level data 602 for each of the 140 sample subjects. In the example in Figure 6, the model parameter 623 is set to "3.00" in row 002 of the evaluation subject 621, whose sample subject ID 312 is "ID00001", and whose identification code is "000". Therefore, when applying the QoL value 421 of the daily activity 201 of sample subject 140, whose sample subject ID 312 is "ID00001", to the function definition 630 for identification code "001", the model parameter 623, "3.00", is applied as the weight of the function definition 630.

[0118] Figure 8 is an explanatory diagram showing the correspondence between the time-series daily activities 201 and the activity environment 202 for a sample of 140 individuals. The daily activities 201 are the time-series daily activities 201A1, 201B1, 201C, 201D1, 201E, 201B2, 201F, 201G, 201D2, 201B3, and 201A2 for the sample of 140 individuals. The corresponding activity environment 802 shows the environment in which each of the daily activities 201 was performed. The width of each daily activity 201 indicates the time interval.

[0119] For example, sleep 201A1 and eating 201B1 refer to daily living activities 201 performed in the activity environment 202A of the home in city B where the sample subjects 140 reside. Similarly, childcare 201C also refers to daily living activities 201 performed in the activity environment 202A of the home in city B where the sample subjects 140 reside.

[0120] Furthermore, travel 201D1 refers to daily activities 201 conducted in a car, an activity environment 202B, in city B where the sample subjects 140 reside. Leisure 201E refers to daily activities 201 conducted in a cafe, an activity environment 202C, in city A, the destination of the travel in the activity environment 202B. Eating 201B2 refers to daily activities 201 conducted in an restaurant, an activity environment 202D, in city A.

[0121] Furthermore, work 201F refers to the daily living activities 201 performed by the sample subject 140 in an activity environment 202E, which is an office in city A. Exercise 201G refers to the daily living activities 201 performed by the sample subject 140 in an activity environment 202F, which is a park in city A. Transportation 201D2 refers to the daily living activities 201 performed by the sample subject 140 in an activity environment 202B, which is a car in city B. Eating 201B3 and sleeping 201A2 refer to the daily living activities 201 performed by the sample subject 140 in an activity environment 202A, which is their home in city B where they reside.

[0122] The QoL value 421 for each daily activity 201 is determined by the time spent on the activity, the degree of preference for the activity, and the activity environment 202 in which the activity was performed. As shown in Figure 8, the daily life of the sample subjects 140 consists of a combination of multiple daily activities 201. Therefore, the evaluation device 100 can index the QoL value of the daily activities 201 as satisfaction. Depending on how the QoL values ​​421 of these daily activities 201 are combined, an arbitrary objective QoL value can be defined. For example, if we want to derive an objective QoL value for city A, the evaluation device 100 will refer to the QoL values ​​of daily activities 201E, 201B2, 201F, and 201G performed in city A.

[0123] Furthermore, when it is desired to derive a target QoL value related to means of transportation, the evaluation device 100 will refer to the QoL values ​​of the lifestyle activities 201D1 and 201D2 that represent "mobility." Similarly, when evaluating residents of a specific evaluation target 621 or specific attributes (demographic 411 or psychographic 412), the evaluation device 100 will obtain the QoL value 421 of the relevant lifestyle activity 201 from the QoL calculation DB 120 and calculate the target QoL value. The target QoL value can be used, for example, as an indicator to support urban management and infrastructure evaluation by governments and local authorities.

[0124] [Example Hardware Configuration of Evaluation Device 100] Figure 9 is a block diagram showing an example of the hardware configuration of the evaluation device 100. The evaluation device 100 includes a processor 901, a storage device 902, an input device 903, an output device 904, and a communication interface (communication IF) 905. The processor 901, storage device 902, input device 903, output device 904, and communication IF 905 are connected by a bus 906. The processor 901 controls the evaluation device 100. The storage device 902 serves as the work area for the processor 901. The storage device 902 is a non-temporary or temporary recording medium that stores various programs and data. Examples of storage devices 902 include ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), and flash memory. The input device 903 inputs data. Examples of input devices 903 include a keyboard, mouse, touch panel, numeric keypad, scanner, microphone, and sensor. The output device 904 outputs data. Output devices 904 include, for example, displays, printers, and speakers. The communication IF 905 connects to the network 170 and sends and receives data.

[0125] Furthermore, the sample participant terminal 141, the external site 150, and the local government service terminal 161 have the same hardware configuration as shown in Figure 9.

[0126] <Example screen of sample user's device 141> Next, we will explain the screen examples of sample user terminal 141 using Figures 10 to 13.

[0127] Figure 10 is an explanatory diagram showing example screen 1 of the sample participant terminal 141. The sample participant terminal 141 displays a consent acquisition screen 1001 on the display 1000. The consent acquisition screen 1001 includes a consent button 1002. The consent acquisition screen 1001 displays the subject of the survey 1011 and an explanation of the survey objectives 1012.

[0128] The sample participant 140 reads the survey subject 1011 and the explanation of the survey objectives 1012, and if they agree, they press the consent button 1002 to indicate their consent. Upon pressing the consent button 1002, the sample participant terminal 141 retrieves the question data from the evaluation device 100. The display on the display 1000 then transitions from the consent acquisition screen 1001 to the first questionnaire screen.

[0129] Figure 11 is an explanatory diagram showing example screen 2 of the sample participant terminal 141. Figure 11 shows the first questionnaire screen 1100, which is accessed after transitioning from the consent acquisition screen 1001. The first questionnaire screen 1100 displays the first question content 1101 and the first selection button group 1102. The first selection button group 1102 consists of daily living activities 201 included in the question data from the evaluation device 100.

[0130] The sample participant 140 presses one of the first selection buttons 1102. Upon this press, the display on the display 1000 transitions from the first questionnaire screen 1100 to the second questionnaire screen.

[0131] Figure 12 is an explanatory diagram showing example screen 3 of the sample participant terminal 141. Figure 12 shows the second questionnaire screen 1200, which is accessed from the first questionnaire screen 1100. The second questionnaire screen 1200 displays the second question content 1201 and the second selection button group 1202. The second selection button group 1202 is the activity environment 202 included in the question data from the evaluation device 100.

[0132] The sample participant 140 presses one of the second selection buttons 1202. Since there are multiple activity environments 202 (four in Figure 2), as shown in Figure 2, the second questionnaire screen 1200 for the next question is displayed until all questions about the activity environment 202 are completed. When one of the second selection buttons 1202 is pressed for the last activity environment 202, the display on the display 1000 transitions from the second questionnaire screen 1200 to the QoL survey screen.

[0133] Figure 13 is an explanatory diagram showing example screen 4 of the sample participant terminal 141. Figure 13 shows the QoL survey screen 1300, which is accessed from the second questionnaire screen 1200. The QoL survey screen 1300 displays the third question content 1301 and the third selection button group 1302. The third question content 1301 is question 203, which confirms the QoL value of 421 for daily living activities 201. The third selection button group 1302 consists of five-point answer choices for the third question content 1301.

[0134] As shown in Figure 2, there are multiple (26 in Figure 2) third questions 1301. Therefore, the QoL survey screen 1300 for the next question is displayed until all questions regarding question 203, which confirms the QoL value 421 for the daily living activity 201, are completed. When one of the third selection buttons 1302 is pressed for the last question 203 (Q26) confirming the QoL value 421 for the daily living activity 201, the sample subject terminal 141 transmits the response data, including the sample subject ID 312 of the sample subject 140 and the previously selected options, to the evaluation device 100.

[0135] <Database generation process> Figure 14 is a sequence diagram showing an example of the database generation process by the database generation unit 115. The sample subject terminal 141 receives notification from the terminal 1301 of the survey project entity, such as the government or local authorities, or the survey agency 1300 commissioned by said survey project entity, that it has been selected as a survey subject (step S1400). As a result, the sample subject terminal 141 displays the consent acquisition screen 901 for the survey and data provision, and when the consent button 902 is pressed, it sends a registration request for the sample subject ID 312 of the sample subject 140 and a survey trigger (step S1401).

[0136] When the registration request and survey trigger for sample participant ID 312 of sample participant 140 are received, the question generation unit 114 generates question data and sends it to the sample participant terminal 141 (step S1402).

[0137] As shown in Figures 10 to 13, the sample participant terminal 141 generates response data based on the selection of the sample participant 140 and transmits it to the database generation unit 115 (step S1403).

[0138] The database generation unit 115 receives response data from the sample subject terminal 141, data from the map server 151 and the weather server 152, performs clustering, and generates entries for the cluster-specific QoL management table 300 and the affiliated cluster management table 310 (step S1404).

[0139] Then, the database generation unit 115 registers the entries of the generated cluster-specific QoL management table 300 and the affiliated cluster management table 310 in the database 112 (step S1405). In this database generation process, initially, the database generation unit 115 is executed after accumulating response data for the group of sample subjects 140, and thereafter, the database 112 is updated each time response data is obtained for a new sample subject 140.

[0140] <Calculation process for target QoL value> Figure 15 is a sequence diagram showing an example of the calculation procedure for the target QoL value. Upon receiving a request from the survey agency 1300, the municipal servicer 160 operates the municipal servicer terminal 161 to select the sample subject ID 312 (hereinafter referred to as the survey subject sample subject ID 312) to be surveyed and transmits the selected survey subject sample subject ID 312 to the evaluation device 100 (step S1501). The transmitted survey subject sample subject ID 312 may be the sample subject ID 312 of randomly selected sample subjects 140, or the sample subject ID 312 of sample subjects 140 belonging to a specific cluster.

[0141] When the estimation unit 116 receives the survey target sample subject ID 312, it estimates the QoL value 421 of the daily activity 201 (step S1502). Specifically, for example, the evaluation device 100 sends a sampling trigger to the sample subject terminal 141 associated with each survey target sample subject ID 312, and acquires the current detection data from the sample subject terminal 141.

[0142] Furthermore, the estimation unit 116 obtains weather data corresponding to the time of the detected data from the weather server 152, facility information corresponding to the latitude and longitude at the time of the detected data from the map server 151, and service information from publicly available sites (not shown). In this way, the estimation unit 116 obtains behavioral data.

[0143] The estimation unit 116 uses the acquired behavioral data to refer to the database 112 and estimates the QoL value 421 of the daily living activity 201 for the sample subject 140 with survey subject ID 312. The estimation unit 116 then stores the usability status 420, the estimated QoL value 421 of the daily living activity 201, the daily living activity 422, the means of living 423, the number of people living 424, the start time of the daily living activity 425, the end time of the daily living activity 426, the latitude and longitude information 427, the facility 428, and the service information 429 as behavioral history data in the QoL calculation DB 120 (step S1503).

[0144] When the municipal servicer terminal 161 receives notification that data storage in step S1503 is complete for all survey target sample subject IDs 312 transmitted in step S1501, it transmits the analysis perspective to the evaluation device 100 as an analysis start signal (step S1504). The analysis perspective includes, for example, the identification code of the evaluation target 621, as well as attribute information (demographics 411 and psychographics 412), facility information, and service information. For example, if the municipal servicer 160 wants to analyze "daily activities in XX Park" and obtain the target QoL value, it sets the identification code "000" of the evaluation target 621 to the municipal servicer terminal 161, and the municipal servicer terminal 161 transmits that identification code "000" to the evaluation device 100.

[0145] When the evaluation device 100 receives an analysis perspective, it obtains a function definition 630 corresponding to the identification code of the evaluation target 621 from the municipal service terminal 161 from the derived QoLDB 130 (step S1505) and outputs it to the QoL calculation unit 103. Also, as explained in [Example of calculating the target QoL value for the evaluation target 621], the QoL calculation unit 103 obtains the QoL value 421 of the relevant life activity 201 and the model parameters 623 of the evaluation target 621 and outputs them to the QoL calculation unit 103 (step S1506).

[0146] The QoL calculation unit 103 calculates the target QoL value by substituting the QoL value 421 of the daily living activity 201 and the model parameters 623 of the evaluation target 621 into the function definition 630, and transmits it to the municipal service terminal 161 (step S1507). This completes the calculation process of the target QoL value.

[0147] <Examples of Use> Next, we will describe an example of how the evaluation system 10 according to this embodiment can be used in infrastructure. Here, we will use park management as an example of infrastructure.

[0148] Figure 16 is an explanatory diagram illustrating an example of its application to park management. Conventional effectiveness evaluation indicators in park management include, for example, green coverage ratio, park area, and number of parks. These values ​​basically do not change once the park is designed. In conventional urban planning, while park development increases the amount of green space compared to before the park development, it does not increase after the park development. Furthermore, it is assumed that the park development did not lead to an increase in users.

[0149] Therefore, by applying the evaluation system 10 according to this embodiment to park management, we can analyze the factors that prevent people from using the park and their hidden needs, and then consider or implement soft measures.

[0150] Specifically, for example, the evaluation device 100 collects data from sample participant terminals 141 of sample participants 140 who use the park, as well as from an external site 150, and calculates the QoL value 421 for the sample participants 140's daily activities 201 in the park. Then, the evaluation device 100 uses the greening of the park used by the sample participants 140 as the evaluation target 621 and calculates the target QoL value.

[0151] For example, if it is found that the amount of green space has increased due to park development, but the quality of life (QoL) value for greening is low, then policymakers can obtain the QoL values ​​for the lifestyle activities 201 of people spending time in the park. For instance, if the QoL value for lifestyle activity 201 for 140 sample participants whose lifestyle activity is "childcare" is lower than the QoL value for lifestyle activity 201 for 140 sample participants whose lifestyle activity is other than "childcare" when using the park, then this means that greening did not gain support from the 140 sample participants who are raising children.

[0152] For example, policymakers considered and implemented measures to improve usage among 140 sample participants who are raising children, such as installing benches and holding events that children could participate in. As a result, the quality of life (QoL) for the 140 sample participants whose daily activity 201 was "child-rearing" increased compared to before the bench installation and before the events were held. When the evaluation device 100 calculated the QoL values ​​for the bench installation and the event holding, it was found to be higher than the QoL values ​​for the greening. In this way, the evaluation device 100 can make policymakers aware of the need for measures to enhance the effectiveness of park development and evaluate the effectiveness of those measures in real time. As a result, it becomes possible to operate and improve park facilities in a way that was previously impossible, thereby increasing their value.

[0153] Another example is the scenario involving an autonomous bus. Conventional effectiveness evaluation indicators were efficiency of travel and reduction of travel time. In fact, these indicators improved as a result of the measures, and the effects were confirmed. However, the target area had a large elderly population, and when evaluating the QoL value 421 of daily life activity 201, the amount of conversation inside the autonomous bus revealed that the longer the ride time, the higher the QoL value 421 of daily life activity 201 was when the autonomous bus was used as a means of daily life 423 than when there was only one person living there (identification code 502 of person 424 was "01"). This revealed that the autonomous bus also functions as a place for socializing.

[0154] Therefore, improvements were made by operating autonomous buses with deliberately longer routes and by developing a service that includes a guide to share lifestyle information. As a result, the number of autonomous bus users increased further, and the QoL value of lifestyle activity 201, which uses autonomous buses as a means of transportation, also improved (QoL value 421). In addition, in lifestyle activities defined as evaluation target 621, when autonomous buses were used as a means of transportation, the target QoL value also increased compared to before the improvements.

[0155] In this scenario, by utilizing the evaluation system 10 of this embodiment, it was possible to uncover needs and user appeal values ​​that were not visible with conventional effectiveness evaluation indicators, and this is an example of how the quality of life of residents could be improved without making large infrastructure investments.

[0156] Thus, the evaluation system 10 according to this embodiment can be expected to have similar effects in all infrastructure operations, administration, and urban management by local governments. Furthermore, since the QoL value 421 of daily living activities 201 and the target QoL value can be calculated immediately at the necessary time, a significant improvement in the urban management cycle becomes possible.

[0157] <Urban Management Cycle> Figure 17 is a conceptual diagram illustrating the urban management cycle realized by evaluation system 10. Conventional urban planning mainly involves a long-term cycle of 5 to 10 years, from master plan formulation to implementation, evaluation, and renewal, requiring considerable effort and time at each stage. As a result, the adaptation of policies was limited to the optimization of the conventional system, and the impact on residents and their perceived satisfaction and fulfillment of life was insufficient.

[0158] When the evaluation system 10 is applied, data acquisition for calculating the QoL value 421 for daily activities 201, the QoL value 421 for daily activities 201, and the calculation of the target QoL are performed immediately. This enables short-cycle feedback of a few months or less, promoting effective urban planning that addresses on-site challenges. Furthermore, it enables short-cycle effectiveness evaluation and accumulation of evaluation results for soft improvements in public services and flexible operation of infrastructure, allowing for a short-cycle and reliable cycle of continuously adding new value to existing infrastructure and implemented policies.

[0159] <Relationship between administrative services and policies for the elderly and expected outcomes> Figure 18 is an explanatory diagram illustrating an example of the relationship between administrative services and policies for the elderly and expected outcomes. Initial (short-term), medium-term, and long-term outcomes are linked by causal relationships between specific activities (policies) and their direct results. In the urban management cycle shown in Figure 17, it is possible to evaluate the direct results—the improvement in the QoL value (QoL) of daily activities (QoL) (QoL) (QoL) (QoL) based on residents' perceptions) and the target QoL value—for each policy immediately after its implementation, on a short-term basis. Using evaluation results and causal relationships, it becomes possible to select and eliminate policies that lead to long-term outcomes, such as those in a master plan, immediately after their implementation. This allows for efficient resource utilization and minimizes policy failures in terms of policy sustainability (residents actively enjoying administrative services).

[0160] Thus, according to this embodiment, it is possible to automatically acquire QoL values ​​and target QoL values ​​for lifestyle activities with low implementation burden and immediate results. This enables policymakers to implement effective measures in a timely manner. Furthermore, it becomes possible to immediately measure whether or not the implemented measures are effective, making it easier to change policy directions.

[0161] It should be noted that the present invention is not limited to the embodiments described above, but includes various modifications and equivalent configurations within the spirit of the attached claims. For example, the embodiments described above are described in detail to make the present invention easier to understand, and the present invention is not necessarily limited to having all of the described configurations. Furthermore, some of the configurations of one embodiment may be replaced with those of another embodiment. Furthermore, some of the configurations of one embodiment may be added to those of another embodiment. Furthermore, some of the configurations of each embodiment may be added, deleted, or replaced with other configurations.

[0162] Furthermore, each of the aforementioned configurations, functions, processing units, and processing means may be implemented in hardware, for example, by designing them as integrated circuits, or they may be implemented in software by having a processor interpret and execute programs that realize each function.

[0163] Information such as programs, tables, and files that implement each function can be stored in memory, hard disks, SSDs (Solid State Drives), or on recording media such as IC (Integrated Circuit) cards, SD cards, and DVDs (Digital Versatile Discs).

[0164] Furthermore, the control lines and information lines shown are those deemed necessary for explanation purposes and do not necessarily represent all control lines and information lines required for implementation. In reality, it can be assumed that almost all components are interconnected. [Explanation of Symbols]

[0165] 10. Evaluation System 100 Evaluation device 101 Generation part 102 List Generation Unit 103 QoL Calculation Unit 114 Question generation part 115 Database Generation Unit 116 Estimation Department 120 QoL Calculation Database 130 Derivation QoLDB 140 sample participants 141 Sample participant devices 160 municipal service providers 161 Municipal Service Terminals 201 Life activities 202 Activity environment 203 Questions

Claims

1. An evaluation apparatus having a processor for executing a program and a storage device for storing the program, The system stores a first satisfaction level for each activity pattern of the life activities performed by the sample subject, for each group to which the sample subject belongs, and provides access to a first database that associates the sample subject with the group to which the sample subject belongs. The aforementioned processor, When behavioral data indicating the behavior of the sample subject is obtained from the sample subject's terminal capable of detecting such behavioral data, an estimation process is performed to estimate the sample subject's daily activities and activity patterns based on the behavioral data. A registration process in which, in the first database, the first satisfaction level for each activity pattern of the group to which the sample subject belongs, estimated by the estimation process, is extracted from the first satisfaction level for the activity pattern estimated by the estimation process, and registered in the second database, An acquisition process to obtain evaluation targets defined by specific daily living activities, An extraction process to extract the first satisfaction level for a specific life activity that corresponds to the evaluation target obtained by the acquisition process from among the first satisfaction levels for each life activity stored for each sample target in the second database, A calculation process for calculating a second satisfaction level with respect to the subject of evaluation, based on the first satisfaction level of specific lifestyle activities extracted by the extraction process, An output process that outputs the second satisfaction level calculated by the above calculation process, An evaluation device characterized by performing the following actions.

2. An evaluation apparatus according to claim 1, The aforementioned processor, The process involves generating questions related to the aforementioned daily activities and transmitting them to the terminal, obtaining the first satisfaction level for each activity pattern of the daily activities from the terminal as a result of transmitting the questions to the terminal, and then generating the first database by associating the sample subject with the group to which it belongs, based on the first satisfaction level for each activity pattern for each daily activity. An evaluation device characterized by the following features.

3. An evaluation apparatus according to claim 2, In the generation process, the processor generates the group by clustering the sample subjects according to the lifestyle activity and based on the first satisfaction level for each activity pattern. An evaluation device characterized by the following features.

4. An evaluation apparatus according to claim 2, The aforementioned question includes multiple lifestyle activities that the sample subject can select, An evaluation device characterized by the following features.

5. An evaluation apparatus according to claim 4, The aforementioned question includes a plurality of life activities that the sample subject can select, and a plurality of activity environments that the sample subject can select for the life activity selected from the plurality of life activities, In the generation process, the processor generates the activity pattern based on the plurality of activity environments. An evaluation device characterized by the following features.

6. An evaluation apparatus according to claim 4, The aforementioned questions include questions to confirm the first level of satisfaction, An evaluation device characterized by the following features.

7. An evaluation apparatus according to claim 6, The above question is based on the World Health Organization's QoL assessment methodology. An evaluation device characterized by the following features.

8. An evaluation apparatus according to claim 1, Multiple calculation methods for calculating the aforementioned second satisfaction level are defined and can be selected. In the calculation process, the processor calculates the second satisfaction level using a calculation method selected from the plurality of calculation methods. An evaluation device characterized by the following features.

9. An evaluation method using an evaluation apparatus having a processor for executing a program and a storage device for storing the program, The system stores a first satisfaction level for each activity pattern of the life activities performed by the sample subject, for each group to which the sample subject belongs, and provides access to a first database that associates the sample subject with the group to which the sample subject belongs. The aforementioned processor, When behavioral data indicating the behavior of the sample subject is obtained from the sample subject's terminal capable of detecting such behavioral data, an estimation process is performed to estimate the sample subject's daily activities and activity patterns based on the behavioral data. A registration process in which, in the first database, the first satisfaction level for each activity pattern of the group to which the sample subject belongs, estimated by the estimation process, is extracted from the first satisfaction level for the activity pattern estimated by the estimation process, and registered in the second database, An acquisition process to obtain evaluation targets defined by specific daily living activities, An extraction process to extract the first satisfaction level for a specific life activity that corresponds to the evaluation target obtained by the acquisition process from among the first satisfaction levels for each life activity stored for each sample target in the second database, A calculation process for calculating a second satisfaction level with respect to the subject of evaluation, based on the first satisfaction level of specific lifestyle activities extracted by the extraction process, An output process that outputs the second satisfaction level calculated by the above calculation process, An evaluation method characterized by performing the following.

10. An evaluation system comprising: an evaluation device that stores a first satisfaction level for each activity pattern of the life activities performed by the sample subject, defined for each group to which the sample subject belongs, and which can access a first database that associates the sample subject with the group to which the sample subject belongs; and a terminal that can detect behavioral data indicating the actions of the sample subject, and which can communicate with each other. The aforementioned terminal is The process of acquiring the aforementioned behavioral data and transmitting it to the evaluation device is executed. The evaluation device is Upon acquiring the behavioral data from the terminal, an estimation process is performed to estimate the lifestyle activities and activity patterns of the sample subject based on the behavioral data. A registration process in which, in the first database, the first satisfaction level for each activity pattern of the group to which the sample subject belongs, estimated by the estimation process, is extracted from the first satisfaction level for the activity pattern estimated by the estimation process, and registered in the second database, An acquisition process to obtain evaluation targets defined by specific daily living activities, An extraction process to extract the first satisfaction level for a specific life activity that corresponds to the evaluation target obtained by the acquisition process from among the first satisfaction levels for each life activity stored for each sample target in the second database, A calculation process for calculating a second satisfaction level with respect to the subject of evaluation, based on the first satisfaction level of specific lifestyle activities extracted by the extraction process, An output process that outputs the second satisfaction level calculated by the above calculation process, An evaluation system characterized by performing the following actions.

Images