JP2024009456A - Evaluation device, evaluation method, and evaluation system - Google Patents

Abstract

PROBLEM TO BE SOLVED: 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

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present invention relates to an evaluation device, an evaluation method, and an evaluation system that perform evaluation.

Patent Document 1 listed below discloses a satisfaction level estimation device that takes into consideration information on groups such as families and estimates satisfaction level information of people belonging to the group. This satisfaction estimation device is a device that estimates the satisfaction information of a person who belongs to a group whose behavior is based in a certain area, and uses behavior-related data to perform learning that is constructed for the person whose satisfaction level is to be estimated and belongs to this group. a behavior identification means that determines behavior information including behavior information related to communication between a person whose satisfaction level is to be estimated and other people belonging to this group using a behavior recognition model that has already been used; A communication score determining means for determining a communication score indicating the degree of communication in this group by a person to be estimated; and a satisfaction determining means for determining the degree of satisfaction of the person to be estimated based on the communication score. have.

JP2020-154938A

However, the satisfaction level estimating device of Patent Document 1 described above indirectly estimates the satisfaction level from emotions estimated from daily life activities. Therefore, no consideration is given to estimating satisfaction directly from daily life activities. Therefore, it is not possible to obtain an efficient evaluation of policy decisions and implemented measures.

The present invention aims to efficiently evaluate measures.

An evaluation device that is an aspect of the invention disclosed in the present application is an evaluation device that includes a processor that executes a program, and a storage device that stores the program, and that is configured to be used for each activity pattern of daily life activities performed by a sample subject. storing a first satisfaction level for each of the groups to which the sample subject belongs as defined in the above for each of the living activities, and accessing a first database in which the sample subject and the group to which the sample subject belongs are associated. and when the processor acquires the behavior data from the sample target's terminal capable of detecting behavior data indicating the sample target's behavior, the processor determines the sample target's daily life activities and the sample target's life activities based on the behavior data. and an estimation process for estimating an activity pattern, and in the first database, among the first satisfaction levels for each of the activity patterns of the group to which the sample subject belongs in the daily life activities estimated by the estimation process. a registration process of extracting the first satisfaction level of the activity pattern estimated by the estimation process and registering it in a second database; an acquisition process of acquiring an evaluation target defined by a specific daily activity; The first satisfaction level for the specific life activity that corresponds to the evaluation target acquired by the acquisition process from among the first satisfaction levels for each of the life activities stored for each sample target in the second database. an extraction process for extracting a second satisfaction level for the evaluation target based on the first satisfaction level for the specific life activity extracted by the extraction process; The present invention is characterized by performing an output process of outputting the second satisfaction level.

According to a typical embodiment of the present invention, efficient measures can be evaluated. Problems, configurations, and effects other than those described above will become clear from the description of the following examples.

FIG. 1 is an explanatory diagram showing an example of the system configuration of an evaluation system. FIG. 2 is an explanatory diagram showing an example of the activity list DB. FIG. 3 is an explanatory diagram showing an example of a database. FIG. 4 is an explanatory diagram showing an example of the QoL calculation DB. FIG. 5 is an explanatory diagram showing an example of the identification code management table shown in FIG. 4. FIG. 6 is an explanatory diagram showing an example of a derived QoLDB. FIG. 7 is an explanatory diagram showing an example of a referenceable information list. FIG. 8 is an explanatory diagram showing the correspondence between daily life activities and activity environments of a certain sample subject in chronological order. FIG. 9 is a block diagram showing an example of the hardware configuration of the evaluation device. FIG. 10 is an explanatory diagram showing example 1 of the screen of the sample target person's terminal. FIG. 11 is an explanatory diagram showing a second example screen of the sample target person's terminal. FIG. 12 is an explanatory diagram showing example 3 of the screen of the sample target person's terminal. FIG. 13 is an explanatory diagram showing example 4 of the screen of the sample target person's terminal. FIG. 14 is a sequence diagram illustrating an example of database generation processing by the database generation unit. FIG. 15 is a sequence diagram illustrating an example of a procedure for calculating a target QoL value. FIG. 16 is an explanatory diagram showing an example of utilization for park management. FIG. 17 is a conceptual diagram showing the city management cycle realized by the evaluation system. FIG. 18 is an explanatory diagram showing an example of the relationship between administrative services and measures for the elderly and expected results.

It is important to evaluate the effectiveness of urban policies such as infrastructure maintenance and management, urban planning, and public service provision. Particularly in recent years, Japan's declining birthrate, aging population, and aging infrastructure have become more pronounced, and the importance of evaluating effectiveness in operating cities with limited budgets and human resources has increased.

The indicators used in effectiveness evaluations are used to understand the current situation and set goals when formulating government and local government policies and city plans. Furthermore, it will be used to visualize the effects of measures, and to provide meaning and evidence for the provision of infrastructure and public services. Governments, local governments, and other entities use these index values as a basis to select infrastructure and public services, decide on operational policies, and operate the region with the consent of stakeholders related to the region, such as residents and corporations. These are EBPM (Evidence Based Policy Making), which has become the mainstream of policy making and local government management as a methodology for city management.

For example, local governments in Japan have begun attempts to formulate KPIs (Key Performance Indicators) as various effect evaluation values related to policy formulation, formulate policies by setting numerical targets for KPIs, and proceed with verification of their effectiveness. There is. Furthermore, the government is leading efforts to organize, centralize, visualize, and utilize indicators for objectively understanding urban conditions in urban planning.

In the above-mentioned attempts, indicators such as the number of facilities in parks, hospitals, and public facilities, the area of green spaces, and the capacity of facilities are mainly selected as evaluation indicators for cities and policies. These indicators are physical quantities. In other words, these indicators can be objectively quantified, and have the advantage of making comparisons between cities and effect evaluations such as setting target values and thresholds clear. However, high scores on these indicators do not necessarily mean that residents are enjoying a comfortable, vibrant, and high-quality life.

On the other hand, in recent years, methods for evaluating residents' satisfaction with policies and administrative measures have been sought. For example, residents' subjective satisfaction levels obtained through questionnaires are aggregated and indexed, and are used as evaluation indicators for cities and policies. Indicators derived from these methods make it possible to evaluate cities and policies from the perspective of residents' quality of life and satisfaction.

In these methods, data is obtained through questionnaire surveys of residents. Questionnaire surveys place a heavy burden on residents, as they require residents to respond to a large number of questions. Also, conducting surveys requires a large amount of budget and human resources. Therefore, the problem is that it is not possible to increase the frequency of implementation. On the other hand, it is desirable that the effectiveness evaluation of urban services be conducted regularly and continuously during the process of service design, before service introduction, after service introduction, and until it becomes established, and a questionnaire survey is required each time.

Developing and putting into practical use tools that can constantly monitor the lives and satisfaction levels of each person living in a city, and new city evaluation indicators based on those tools, is an urban management approach that both optimizes society as a whole and improves residents' life satisfaction. It is considered indispensable to lead to.

QoL (Quality of Life) is an index related to life satisfaction and fulfillment. QoL is a concept devised as an index for evaluating human health not only from the perspective of physical ability but also from the quality of daily life such as psychology, social relationships, and surrounding activity environment. For example, as an international index for measuring QoL, there is the QoL evaluation method of the World Health Organization (WHO). This QoL evaluation method is a method of deriving a QoL value from answers selected using a 5-point rule for 100 or 26 questions based on the above-mentioned viewpoints. It is possible to estimate the degree of satisfaction and sufficiency of a person's life based on the QoL value derived using this QoL evaluation method.

In the embodiment shown below, an evaluation system in which this concept is extended to the urban planning field will be described. The evaluation system according to this embodiment can conduct a single QoL survey and behavioral history data (where, how much, If we can obtain the following information (what they did under what conditions), we can automatically obtain the target behavioral history data and evaluate the life satisfaction of people living in the town using the QoL value of daily life activities 201. do. This evaluation system quantitatively calculates the QoL value of daily life activities 201 of people living in the town, and based on the QoL value of this daily life activity 201, calculates the objective QoL value regarding urban planning, management, and measures. Evaluate urban planning, management, and policies.

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

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

The external site 150 is, for example, a map server 151 or a weather server 152. The map server 151 transmits map data in response to a request from the evaluation device 100. The map server 151 also holds facility information such as administrative agencies, parks, convenience stores, restaurants, theme parks, fitness clubs, and office buildings where companies are located on the map data. The map server 151 also holds routes and operation schedules for public transportation such as trains and buses.

For example, when the map server 151 receives latitude and longitude from the evaluation device 100 or the sample subject terminal 141, it returns two-dimensional or three-dimensional map data including the latitude and longitude, and the facility name and address corresponding to the latitude and longitude.

The weather server 152 transmits weather information in response to a request from the evaluation device 100. The weather server 152 returns, to the evaluation device 100 or the sample subject terminal 141, weather information indicating the climate, weather, or meteorology at the time of the request from the evaluation device 100 or the sample subject terminal 141, for example.

The local government servicer terminal 161 executes processing such as adding, changing, or deleting data in the evaluation device 100 in response to the operation of the local government servicer 160.

The evaluation device 100 includes a generation section 101, a list generation section 102, a QoL calculation section 103103, a QoL calculation DB 120, and a derivation QoLDB 130.

The generation unit 101 generates various data and estimates the QoL value of daily life activities. The QoL value of daily life activities is an index value indicating how satisfied the sample subject 140 is with the daily life activities that the sample subject 140 has 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 specifically explained.

[Activity list DB111]
FIG. 2 is an explanatory diagram showing an example of the activity list DB 111. The activity list DB 111 is a database listing daily life activities, and specifically includes, for example, a daily life activity 201, an activity environment 202, and a question 203 for checking the QoL value of the daily life activity 201. Life activity 201 is information indicating what kind of activities sample subject 140 is currently doing in his/her life, and is selected by sample subject 140 .

The activity environment 202 is a set of environmental conditions 221 to 225 indicating what kind of activity environment and under what evaluation conditions the sample subject 140 was active regarding the daily life activities 201 inputted from the sample subject terminal 141. 140 is selected. The environmental conditions 221 to 225 are just examples; other environmental conditions (for example, for whom) may be included, or any of the environmental conditions 221 to 225 may be excluded.

A question 203 for confirming the QoL value of the daily life activity 201 is an example of a question used to calculate the QoL value of the WHO QoL Brief. Although FIG. 2 shows the WHO example, the QoL index is not limited to this, and an appropriate QoL index may be adopted. The question 203 in the question 203 for confirming the QoL value of the daily life activity 201 is transmitted to the sample subject terminal 141 via the network 170 as question data. The sample subject terminal 141 responds in a multiple-choice manner through the operation of the sample subject 140, and transmits the answer results to the evaluation device 100 as answer data.

Before calculating the QoL value of the daily life activity 201, the question generation unit 114 generates question data for determining calculation rules. Specifically, for example, the question data includes the daily life activities 201 performed by the sample subject 140, the activity environment 202 in which the sample subject 140 performed the daily life activities 201, and the QoL of the daily life activities 201, shown in FIG. and a question 203 for confirming the value. When the question generation unit 114 receives a survey trigger from the sample subject terminal 141, it transmits the generated question data to the sample subject terminal 141 that has transmitted the survey trigger.

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 target person terminal 141, and based on the response content, creates a living activity 201 and a preferred activity environment. The environmental conditions 221 to 225 of 202 are analyzed.

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

In the initial state, there are as many clusters as there are column vectors, and the database generation unit 115 performs clustering sequentially starting from the pair of column vectors with the shortest Euclidean distance. The database generation unit 115 calculates the average value of each element of a plurality of column vectors that belong to the same cluster, or obtains the median value or mode, and generates a column vector representing the cluster. , to be subjected to clustering.

The database generation unit 115 executes this clustering until the number of clusters reaches a predetermined number or until the number of column vectors belonging to each cluster reaches a predetermined number or more. As a result, a cluster-specific QoL management table is generated for each lifestyle activity 201 (see FIG. 3).

In addition, the database generation unit 115 associates the sample subject 140 who responded in each daily life activity 201 with the cluster to which it belongs. As a result, a belonging cluster management table is generated for each lifestyle activity 201 (see FIG. 3).

[Database 112]
FIG. 3 is an explanatory diagram showing an example of the database 112. The database 112 is generated by a database generation unit 115. The database 112 includes a QoL management table 300 by cluster and a cluster management table 310 for each lifestyle activity 201. FIG. 3 shows, as an example, a cluster-based QoL management table 300 and a belonging cluster management table 310 when the daily life activity 201 is work.

The cluster-specific QoL management table 300 is a table showing the results of clustering the sample subjects 140 according to daily activities 201, and has an activity pattern 301 and a cluster-specific QoL value 302 as fields. The activity pattern 301 is a type in which the sample subject 140 was active under the environmental conditions 221 to 225. “P#” (# is a number), which is the value of the activity pattern 301, may be expressed as activity pattern P#. When the activity patterns P1, P2, . . . are not distinguished, they are referred to as an activity pattern 301.

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

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

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 column vector of a cluster in which the average value of each element of a plurality of column vectors belonging to the cluster is calculated or the median value is obtained.

Note that the relationship between the activity pattern 301 and the cluster-specific QoL value 302 is not limited to the cluster-specific QoL management table 300, and may be defined by a function. Specifically, for example, the database generation unit 115 executes machine learning using the activity pattern 301 as correct data and the column vector of QoL values belonging to a cluster as training data, and combines the activity pattern 301 with the cluster-specific QoL value 302. The relationship may be defined using a machine learning model.

The belonging cluster management table 310 has a cluster ID 311 and a sample subject ID 312 as fields. The cluster ID 311 is identification information that uniquely identifies a cluster. The sample subject ID 312 is identification information that uniquely identifies the sample subject 140. This makes it possible to specify which cluster the sample subject 140 identified by the sample subject ID 312 belongs to.

Returning to FIG. 1, after generating the database 112, the estimating unit 116 calculates the QoL value of each daily activity 201 as an estimated value for each daily activity 201. Specifically, for example, the estimation unit 116 acquires the sample subject ID 312 and the detection data from the sample subject terminal 141, which is represented by a smartphone, a wristband type sensor, a smart watch, or the like. The detected data is, for example, data detected by a sensor built into the sample subject terminal 141 (acceleration, latitude and longitude, audio such as conversation and environmental sounds, heart rate, etc.).

Furthermore, the estimating unit 116 acquires information from the sample subject terminal 141 about the attendees whose consent has been obtained. For example, assume that event information at a certain date and time and at a certain facility is registered in the schedule management software in the sample subject terminal 141. It is assumed that the sample subject ID 312 of another sample subject 140 is registered as an attendee in the event. The sample target person terminal 141 includes the sample target person ID 312 of the other sample target person 140 as the attendee information in the event information at the date and time of the event, and transmits the event information to the evaluation device 100 as detected data. Thereby, the estimation unit 116 can acquire the attendee information from the received event information.

Furthermore, the estimation unit 116 acquires environmental information when performing daily life activities 201, such as location and weather information obtained from public sites, etc., and service information (such as point assignment) obtained at the place where daily life activities 201 are performed. .

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

Then, the estimating unit 116 refers to the acquired behavior data and estimates the daily life activity 201 and the activity pattern 301 under the environmental conditions 221 to 225 when performing the daily life activity 201.

Specifically, the estimating unit 116 estimates which category the daily life activity 201 of the sample subject 140 falls under, based on the behavior data from the sample subject terminal 141.

For example, the estimation unit 116 determines which lifestyle activity 201 of the sample subject 140 falls within the predetermined time period based on the heart rate included in a series of detection data acquired within the predetermined time period. For example, if the heart rate is a value indicating sleep, it is determined that the daily activity is sleeping, and if the heart rate is a value indicating eating, the daily activity is determined to be eating.

Further, the estimation unit 116 may estimate the daily activities 201 using not only the heart rate but also latitude and longitude information, time zone, and facility information. For example, the facility specified by the facility information is a fitness club, the heart rate of the detection data is a numerical value indicating exercise, the latitude and longitude information indicates the location of the fitness club, and the acquisition time of the detection data is the business hours of the fitness club. If it is within the range and outside the working hours of the sample subject 140, the estimating unit 116 specifies that the daily activity 201 is "leisure".

For example, the estimating unit 116 also calculates the movement history and movement speed of a position specified by the latitude and longitude information of a series of detection data acquired within a predetermined period of time, and the transportation route on the map data corresponding to the position. Based on this, it may be estimated to which category the daily life activity 201 of the sample subject 140 falls. For example, if the acquisition time of the detection data is a railway operating time zone, the movement history of the latitude and longitude information is a railway route, and the movement speed is the railway speed, the generation unit 101 generates the living activity 201 as "traveling". ”.

In addition, the estimation unit 116 uses the behavior data from the sample subject terminal 141 as training data, and the daily life activities 201 selected by the sample subject 140 at that time as correct answer data, and performs machine learning in advance to create a machine learning model. The daily activities 201 may be estimated by generating a machine learning model and inputting behavioral data from the sample subject terminal 141 to this machine learning model.

In this way, the estimating unit 116 can estimate which category the daily activity 201 of the sample subject 140 corresponds to, based on the behavior data from the sample subject terminal 141.

Furthermore, the estimation unit 116 estimates which behavior pattern 301 of the sample subject 140 corresponds to, based on the behavior data from the sample subject terminal 141. Since the behavior pattern 301 is a type of the environmental conditions 221 to 225, the estimation unit 116 specifically identifies the environmental conditions 221 to 225 using the behavior data.

The environmental condition 221 (where) is specified, for example, by latitude and longitude information in the behavior data. The environmental condition 222 (what kind of facility) is specified by the facility information on the map data that exists at the position indicated by the latitude and longitude information in the behavior data.

The environmental condition 223 (by what means) is specified, for example, by the environmental condition 222 and the audio data in the behavior data. For example, in the environmental condition 222, the facility is the "workplace" of the sample subject 140, and the behavior data includes voice data such as "I'm going to have a meeting." The estimation unit 116 converts the voice data into voice recognition. By doing so, the estimating unit 116 specifies that the environmental condition 223 is "meeting". Furthermore, when the utterances of a plurality of people are voice-recognized based on voice data, the estimating unit 116 may specify that the environmental condition 223 is a "meeting".

The environmental condition 224 (with whom) is specified by the event information, for example, if there is event information including the above-mentioned attendee information in the behavior data.

For example, the environmental condition 224 is specified to be "co-worker" when the attendee information is present in the behavior data and the workplace information of the attendee and the attendee match. Work place information is registered for each sample subject ID 312 in the QoL calculation DB 120.

The environmental information 225 (for how long) is specified by the estimated start time and end time of the daily activity 201.

In this way, the estimation unit 116 can estimate which behavior pattern 301 of the sample subject 140 corresponds to, based on the behavior data from the sample subject terminal 141.

Then, the estimating unit 116 refers to the belonging cluster management table 310 of the estimated daily 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 behavior data. Then, the estimating unit 116 converts the QoL value 302 of the estimated activity pattern 301 into a cluster-specific QoL value 302 of the sample subject 140 from among the cluster-specific QoL values 302 of all the activity patterns 301 of the cluster identified by the cluster ID 311. Obtained as an estimated value.

For example, if the sample subject ID 312 is "00001", the sample subject 140 belongs to cluster A because the cluster ID 311 is "A". Further, assuming that the activity pattern 301 is specified as "P2" by the behavior data, the cluster-specific QoL value 302 of cluster A when the activity pattern 301 is "P2" is "5". Therefore, the estimation unit 116 obtains "5" as the estimated value of the QoL value of "work" which is the current daily life activity 201.

The estimation unit 116 stores the estimated activity pattern 301, the behavioral data, and the QoL value of the daily life activity 201 acquired as the estimated value in the QoL calculation DB 120 as a log.

The QoL calculation DB 120 is a database that holds data necessary for calculating the QoL value of the daily life activity 201. The QoL calculation DB 120 will be specifically explained.

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

The upper layer data 401 defines a sample subject ID 312, a demographic 411, and a psychographic 412 in row number 001. Demographics 411 is an identification code that specifies demographic attributes such as gender, age, and occupation, for example. The psychographic 412 is an identification code that indicates psychological attributes such as hobbies, tastes, orientations, and religions. Sample subject 140 is characterized by at least one of demographics 411 and psychographics 412. In addition, relationships with other sample subjects 140 (relatives, friends, colleagues, etc.) may also be included. In this case, an identification code indicating a relationship with another sample subject 140 and a sample subject ID 312 of another sample subject 140 are defined in the upper layer data 401. Although not shown, the occupation information includes workplace information including workplace facility information (including latitude and longitude information).

The lower layer data 402 includes, from row number 002 onwards, utilization availability status 420, QoL value of daily life activity 201 421, daily life activity 422, means of daily living 423, number of people living 424, daily life activity start time 425, daily life activity end time 426, latitude and longitude. Information 427, facilities 428, and service information 429 are defined.

FIG. 5 is an explanatory diagram showing an example of the identification code management table 403 shown in FIG. 4. The identification code management table 403 is a table that defines the values of the identification code 502 for each of the categories, which are living activities 422, means of living 423, number of people living 424, facilities 428, and service information 429.

Returning to FIG. 4, the QoL value 421 of the daily life activity 201, the daily life activity 422, the daily living means 423, the number of people living 424, the daily life activity start time 425, the daily life activity end time 426, the latitude and longitude information 427, the facilities 428, and the service information 429 are , is stored in the QoL calculation DB 120 as behavior history data of the sample subject 140.

The utilization availability status 420 is information indicating whether the sample subject 140 intends to provide the lower layer data 402 to the evaluation device 100 for each living activity 422. The usage availability status 420 can be changed for each daily life activity 422 by accessing from the sample subject terminal 141. The evaluation device 100 is capable of extracting the line number data of the daily life activities 422 whose usage availability status 420 is set to "OK" for the purpose of calculating the objective QoL value. It is not possible to extract the row number data of the daily life activity 422 for calculating the target QoL value.

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

The daily life activity 422 is a category 501 indicating the daily life activity 201 estimated based on the behavioral data from the sample subject terminal 141, and is specified by the identification code 502.

The means of living 423 is a category 501 indicating by what means the living activities 201 were realized, and is designated by an identification code 502. For example, the estimation unit 116 is based on the movement history and movement speed of a position specified by the latitude and longitude information of a series of detection data acquired within a predetermined period of time, and the transportation route on the map data corresponding to the position. , it is estimated by what means (walking, public transportation, car, etc.) the means of living 423 of the sample subject 140 is achieved. For example, if the acquisition time of the detection data is a railway operating time zone, the movement history of the latitude and longitude information is a railway line, and the movement speed is the railway speed, the estimation unit 116 determines that the means of living 423 is a "public transportation”.

The number of living persons 424 is a category 501 that indicates how many people have fulfilled the living activities 201, and is designated by an identification code 502. For example, the estimating unit 116 uses, for example, the seatmate information if there is seatmate information in the behavior data, the voice data if there is audio data related to the seatmate, and the behavior data from the sample target person terminal 141 of the seatmate. If there is latitude and longitude information and facility information of behavior data of the sample subject terminal 141 and other sample subject terminals 141, estimation is made based on the latitude and longitude information and facility information. The estimation unit 116 may use the environmental conditions 224 as the number of living persons 424.

The daily life activity start time 425 is the start time of the daily life activity 201 estimated based on the behavior data from the sample subject terminal 141.

The life activity end time 426 is the end time of the life activity 201 estimated based on the behavior data from the sample subject terminal 141. That is, the daily life activity start time 425 and the daily life activity end time 426 correspond to the environmental condition 225.

The latitude and longitude information 427 is acquired as behavior data from the sample subject terminal 141 and corresponds to the environmental condition 221.

Facility 428 is a category 501 acquired for facility information in the behavior data from sample subject terminal 141, and is designated by identification code 502. Facility 428 corresponds to environmental conditions 222.

The service information 429 is a category 501 acquired as service information in the behavior data from the sample target person terminal 141, and is designated by an identification code 502.

In this way, the estimating unit 116 calculates the means of living 423, the number of people living 424, the starting time 425 of living activities, the end time 426 of living activities, Latitude and longitude information 427, facility 428, and service information 429 are generated and registered in the QoL calculation DB 120 as action history data. Note that the estimation unit 116 may register the behavior data as is as behavior history data.

Returning to FIG. 1, the derivation QoLDB 130 is a database that holds data necessary for deriving a target QoL value. The derived QoLDB 130 will be specifically explained.

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

The upper layer data 601 defines the sample subject ID 312 of the sample subject 140 in row number 001. The upper layer data 601 may be the ID of a cluster, which is a plurality of sample subjects 140 having a common attribute, instead of the sample subject ID 312 of the sample subject 140.

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

The model 622 is an identification code that uniquely specifies a function for calculating the objective QoL value regarding the daily life activity 201 defined by the evaluation target 621. The correspondence between functions and identification codes is defined in the calculation method list 132.

Model parameters 623 are parameters input to the function specified by model 622. Since the degree of satisfaction and sufficiency felt by the corresponding life activity 201 differs depending on the sample subject 140, the model parameters 623 are set for each sample subject 140. The model 622 and model parameters 623 can be changed by the local government servicer terminal 161 or the sample target person terminal 141.

The calculation method list 132 defines a model 622 and a function definition 630 in row numbers. The function definition 630 defines a function for calculating the objective QoL value regarding the daily life activity 201 defined by the evaluation target 621. The correspondence between the evaluation target 621 and the function definition 630 can be changed arbitrarily from the local government servicer terminal 161.

FIG. 7 is an explanatory diagram showing an example of the referenceable information list 131. The referenceable information list 131 is data that defines the evaluation target 621, and includes a reference target information area 701 and a reference condition information area 702.

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

Male 710 is an identification code indicating whether a male is included in the participants in the daily life activity defined by evaluation target 621. If it is "000", men are not included, and if it is "001", men are included.

Female 711 is an identification code indicating whether a woman is included in the participants in the daily life activities defined by evaluation target 621. If it is "000", women are not included, and if it is "001", women are included.

The occupation 712 is an identification code indicating whether or not the occupation of the participant in the daily life activity defined by the evaluation target 621 is referenced. If the value of the occupation 712 is "000", the evaluation device 100 does not refer to the reference occupation information 713, and if it is "001", the evaluation device 100 identifies the occupation by referring to the reference occupation information 713.

The reference occupation information 713 defines a reference condition number 721 defined in the reference condition information area 702. For example, in the case of “005”, “company employee, self-employed” corresponding to “005”, which is the reference condition number 721 of row number 006 in the reference condition information area 702, is specified as the reference condition 723.

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

The reference time information 715 defines a 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”, the reference condition 723 is “2021.6.10. 13:30, 2021.6.10.15:30” is specified.

The latitude and longitude 716 is an identification code indicating whether or not the activity position of the daily life activity 201 defined in the evaluation target 621 is referenced. If the value of the latitude and longitude 716 is "000", the evaluation device 100 does not refer to the reference geographic information 717, and if it is "001", the evaluation device 100 refers to the reference geographic information 717 to identify the activity position of the daily life activity 201. .

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

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

The reference facility information 719 defines a reference condition number 721 defined in the reference condition information area 702. As the reference condition 723, text data such as the facility name, address, and facility outline specified in the reference condition information area 702 is specified.

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

Returning to FIG. 1, the list generation unit 102 generates behavior history data of the QoL calculation DB 120 (QoL value 421 of daily life activity 201, daily life activity 422, means of daily living 423, number of people living 424, daily life activity The referenceable information list 131 is generated by referring to the start time 425, end time 426 of daily activities, latitude and longitude information 427, facilities 428, and service information 429). Thereby, the user of the local government servicer terminal 161 can create an appropriate referenceable information list 131.

The QoL calculation unit 103 refers to the QoL calculation DB 120 and the calculation method list 132, extracts the QoL value 421 of the daily life activity 201 corresponding to the evaluation target 621 from the QoL calculation DB 120, and determines the purpose according to the calculation method in the calculation method list 132. Calculate QoL value. The evaluation device 100 transmits the calculated target QoL value to the local government servicer terminal 161.

[QoL value]
Here, the QoL value will be specifically explained. The QoL values calculated by the evaluation device 100 include a QoL value 421 of the daily life activity 201 and a target QoL value. As described above, the QoL value 421 of the daily life activity 201 is an index value indicating how satisfied the sample subject 140 is with the daily life activity 201 that the sample subject 140 performed. That is, the QoL value 421 of the daily life activity 201 is the cluster-specific QoL value 302 acquired for the daily life activity 422 as an estimated value from the estimation unit 116, as described above.

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

The QoL calculation unit 103 calculates a target QoL value from the QoL value 421 of the daily life activity 201 estimated by the estimation unit 116. The purpose QoL value is, for example, a QoL value used to evaluate the effectiveness of a living activity 201 defined by an evaluation target 621 such as a specific policy, a specific public service, urban life with specific attributes such as people with disabilities, gender, and age group. It is.

Specifically, for example, the QoL calculation unit 103 extracts the QoL value 421 of the daily life activity 201 of the sample subject 140 that matches the purpose from the QoL calculation DB 120, and extracts the function definition 630 that matches the purpose from the calculation method list 132. The QoL value 421 of the extracted daily life activity 201 is substituted into the extracted function definition 630. Thereby, the QoL calculation unit 103 calculates the target QoL value.

[Example of calculation of objective QoL value regarding evaluation target 621]
Here, a first example of calculation of the objective QoL value regarding the evaluation target 621 will be explained. Here, the evaluation target 621 is assumed to be "XX life activities in the park" whose identification code is "000". In the case of "living activities in XX park", the QoL value 421 of the living activities 201 performed in XX park is required. Therefore, the latitude and longitude 716 of row number 002 in the reference target information area 701 is set to "001". Further, the reference condition number 721 referred to by the reference geographic information 717 of row number 002 is polygon data specified by four latitudes and longitudes (reference condition 723) that are the four vertices of a rectangle indicating the position of XX Park.

Based on the four latitudes and longitudes of XX Park specified by this reference condition 723, the QoL calculation unit 103 refers to the QoL calculation DB 120, and uses the same line number as the latitude and longitude information 427 included in the four latitudes and longitudes of XX Park. If the QoL value 421 of the activity 201 is the QoL value 421 that matches the purpose, and the availability status 420 is "OK", it is extracted from the lower layer data 402 of the sample subject 140.

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

In this case, the QoL calculation unit 103 uses the function definition 630 with the identification code "000" as the function definition 630 that matches the purpose, and calculates the weighted average value of the QoL values 421 of the extracted daily life activities 201 as "XX It is calculated as the objective QoL value related to "living activities in the park".

Note that model parameters 623 are set in the lower layer data 602 for each sample subject 140. In the example of FIG. 6, "3.00" is set as the model parameter 623 in the row number 002 of the identification code "000" of the evaluation target 621 whose sample subject ID 312 is "ID00001". Therefore, when applying the QoL value 421 of the daily life activity 201 of the sample subject 140 whose sample subject ID 312 is "ID00001" to the function definition 630 whose identification code is "000", the model parameter 623 is "3.00". ” is applied as the weight of the function definition 630.

A second calculation example of the objective QoL value regarding the evaluation target 621 will be explained. Here, the evaluation target 621 is "life activities of women participating in events planned at facility ZZ" with identification code "001". In the case of "lifestyle activities of women participating in events planned at facility ZZ", the QoL value 421 of the life activities 201 performed within facility ZZ is required. Therefore, the latitude and longitude 716 of row number 002 in the reference target information area 701 is set to "001". Further, the reference condition number 721 referred to by the reference geographic information 717 of row number 002 is polygon data specified by four latitudes and longitudes (reference condition 723) that are the four vertices of a rectangle indicating the position of the facility ZZ.

In addition, the QoL value 421 of daily life activities 201 performed during the activity time period of "Daily life activities of women participating in events planned at facility ZZ" is also required. Therefore, the time 714 of row number 002 in the reference target information area 701 is set to "001". Further, the reference condition number 721 referred to by the reference time information 715 of row number 002 is, for example, the reference condition 723 indicating the time zone of row number 004 in the reference condition information area 702.

In addition, the QoL value 421 of the daily life activity 201 of the woman who is the target of participation in "the daily life activity of the woman participating in the event planned at the facility ZZ" is also required. Therefore, the female 711 in the row number 002 in the reference target information area 701 is set to "001", and the male 710 in the row number 002 in the reference target information area 701 is set to "000".

The QoL calculation unit 103 refers to the QoL calculation DB 120 using the four latitudes and longitudes and time zones of the facility ZZ specified by this reference condition 723, the time zone, and the identification code "001" indicating that the woman 711 is included. In the QoL calculation source data 400 where the gender of the demographic 411 is female, the latitude and longitude information 427 included in the four latitudes and longitudes of the facility ZZ and the QoL of the daily life activity 201 with the same line number as the time zone of the event planned at the facility ZZ If the value 421 is the QoL value 421 that matches the purpose and the usage availability status 420 is "OK", it is extracted from the lower layer data 402 of the sample subject 140.

Furthermore, the QoL calculation unit 103 specifies a function definition 630 from the calculation method list 132. Specifically, for example, in the model 622 in the lower data 602 of each sample subject 140, a function definition 630 that defines a weighted root mean square is set as the function definition 630 corresponding to the identification code "001" of the evaluation subject 621. It is assumed that an identifying identification code "001" is specified.

In this case, the QoL calculation unit 103 uses the function definition 630 with the identification code "001" as the function definition 630 that matches the purpose, and calculates the weighted root mean square value of the QoL values 421 of the extracted daily life activities 201 as " It is calculated as the objective QoL value regarding "life activities" of women participating in events planned at facility ZZ.

Note that model parameters 623 are set in the lower layer data 602 for each sample subject 140. In the example of FIG. 6, "3.00" is set as the model parameter 623 in the row number 002 of the identification code "000" of the evaluation target 621 whose sample subject ID 312 is "ID00001". Therefore, when applying the QoL value 421 of the daily life activity 201 of the sample subject 140 whose sample subject ID 312 is "ID00001" to the function definition 630 with the identification code "001", the model parameter 623 is "3.00". ” is applied as the weight of the function definition 630.

FIG. 8 is an explanatory diagram showing the correspondence between daily life activities 201 and activity environment 202 in chronological order of a certain sample subject 140. The daily life activities 201 are chronological daily life activities 201A1, 201B1, 201C, 201D1, 201E, 201B2, 201F, 201G, 201D2, 201B3, and 201A2 of a certain sample subject 140. The corresponding activity environment 802 indicates the activity environment in which each of the daily life activities 201 was performed. The width of each daily life activity 201 indicates a time interval.

For example, sleep 201A1 and meal 201B1 refer to daily life activities 201 performed in the activity environment 202A of the home in city B where the sample subject 140 resides. Similarly, childcare 201C also means daily life activities 201 performed in the activity environment 202A of the home in city B where the sample subject 140 resides.

Furthermore, movement 201D1 means a daily life activity 201 in city B where the sample subject 140 resides in an activity environment 202B called a car. In addition, the leisure time 201E means the daily life activities 201 that the sample subject 140 performed in the activity environment 202C called a cafe in the destination city A according to the activity environment 202B. Furthermore, the meal 201B2 means the daily life activity 201 that the sample subject 140 performed in the activity environment 202D of a restaurant in the city A.

Further, the work 201F means the daily life activity 201 performed by the sample subject 140 in the activity environment 202E, which is an office in city A. Exercise 201G means daily life activity 201 performed by sample subject 140 in activity environment 202F, which is a park in city A. Movement 201D2 means a daily life activity 201 in which the sample subject 140 is in a car in city B, an activity environment 202B. Eating 201B3 and sleeping 201A2 refer to daily life activities 201 performed in the activity environment 202A of the home in city B where the sample subject 140 resides.

The QoL value 421 of each lifestyle activity 201 is determined by the time the lifestyle activity 201 is performed, the degree of preference for the lifestyle activity 201, and the activity environment 202 in which the lifestyle activity 201 is performed. As shown in FIG. 8, the daily life of the sample subject 140 is made up of a combination of a plurality of daily life activities 201. Therefore, the evaluation device 100 can index the QoL value of the daily life activity 201 as a degree of satisfaction. Depending on how the QoL values 421 of the daily life activities 201 are combined, a desired QoL value from an arbitrary viewpoint can be defined. For example, if it is desired to derive the objective QoL value regarding city A, the evaluation device 100 will refer to the QoL values of daily life activities 201E, 201B2, 201F, and 201G performed in city A.

Furthermore, when it is desired to derive the purpose QoL value regarding the means of transportation, the evaluation device 100 refers to the QoL values of the daily life activities 201D1 and 201D2 indicating "movement." When evaluating a specific evaluation target 621 or a resident with a specific attribute (demographic 411 or psychographic 412), similarly to the above, the evaluation device 100 calculates the QoL value 421 of the corresponding daily activity 201 by using the QoL calculation DB 120. The target QoL value will be calculated by acquiring from The objective QoL value can be used, for example, as an index that contributes to the maintenance and management of urban management and infrastructure evaluation by the government and local governments.

[Example hardware configuration of evaluation device 100]
FIG. 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. A processor 901, a storage device 902, an input device 903, an output device 904, and a communication IF 905 are connected by a bus 906. Processor 901 controls evaluation device 100. Storage device 902 becomes a work area for processor 901. Furthermore, the storage device 902 is a non-temporary or temporary recording medium that stores various programs and data. Examples of the storage device 902 include ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), and flash memory. Input device 903 inputs data. Examples of the input device 903 include a keyboard, mouse, touch panel, numeric keypad, scanner, microphone, and sensor. Output device 904 outputs data. Examples of the output device 904 include a display, a printer, and a speaker. Communication IF 905 connects to network 170 and transmits and receives data.

Note that the sample target person terminal 141, the external site 150, and the local government servicer terminal 161 also have the same hardware configuration as in FIG. 9.

<Screen example of sample target terminal 141>
Next, screen examples of the sample subject terminal 141 will be explained using FIGS. 10 to 13.

FIG. 10 is an explanatory diagram showing example 1 of the screen of the sample target person terminal 141. The sample subject 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 investigation 1011 and an explanation of the purpose of the investigation 1012.

The sample subject 140 reads the subject of the survey 1011 and the explanation of the purpose of the survey 1012, and if they agree, presses the consent button 1002 to express their intention. By pressing the consent button 1002, the sample subject terminal 141 acquires question data from the evaluation device 100. The display content on the display 1000 then transitions from the consent acquisition screen 1001 to the first questionnaire screen.

FIG. 11 is an explanatory diagram showing a second screen example of the sample target person terminal 141. FIG. 11 shows a first questionnaire screen 1100 transitioned from the consent acquisition screen 1001. The first questionnaire screen 1100 displays first question details 1101 and a first selection button group 1102. The first selection button group 1102 is the daily life activity 201 included in the question data from the evaluation device 100.

The sample subject 140 presses any one of the first selection button group 1102. By pressing this button, the content displayed on the display 1000 changes from the first questionnaire screen 1100 to the second questionnaire screen.

FIG. 12 is an explanatory diagram showing a third screen example of the sample target person terminal 141. FIG. 12 shows a second questionnaire screen 1200 transitioned from the first questionnaire screen 1100. The second questionnaire screen 1200 displays second question details 1201 and a 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.

The sample subject 140 presses any one of the second selection button group 1202. Since there are a plurality of activity environments 202 (four in FIG. 2) as shown in FIG. 2, the second questionnaire screen 1200 regarding the next question is displayed until all questions regarding the activity environment 202 are completed. When any one of the second selection button group 1202 is pressed for the last activity environment 202, the content displayed on the display 1000 changes from the second questionnaire screen 1200 to the QoL survey screen.

FIG. 13 is an explanatory diagram showing example 4 of the screen of the sample target person terminal 141. FIG. 13 shows a QoL survey screen 1300 transitioned from the second questionnaire screen 1200. The QoL survey screen 1300 displays third question content 1301 and a third selection button group 1302. The third question content 1301 is a question 203 for confirming the QoL value 421 of the daily life activity 201. The third selection button group 1302 is a five-point answer option for the third question content 1301.

As shown in FIG. 2, there are multiple third question contents 1301 (26 in FIG. 2). A QoL survey screen 1300 is displayed. When any one of the third selection button group 1302 is pressed regarding the question 203 (Q26) for confirming the QoL value 421 of the last daily life activity 201, the sample subject terminal 141 displays the sample subject ID 312 of the sample subject 140. Answer data including the options selected so far is transmitted to the evaluation device 100.

<Database generation process>
FIG. 14 is a sequence diagram illustrating an example of database generation processing by the database generation unit 115. The sample subject terminal 141 receives a notification that the sample subject has become a subject of the survey from the terminal 1301 of the research project entity such as the government or local government, or the research agency 1300 commissioned by the research project entity (step S1400). As a result, the sample subject terminal 141 displays a consent acquisition screen 901 for the survey and data provision, and when the consent button 902 is pressed, a request to register the sample subject ID 312 of the sample subject 140 and a survey trigger are sent. (Step S1401).

Upon receiving the request to register the sample subject ID 312 of the sample subject 140 and the survey trigger, the question generation unit 114 generates question data and transmits it to the sample subject terminal 141 (step S1402).

The sample subject terminal 141 generates response data based on the selection of the sample subject 140, as shown in FIGS. 10 to 13, and transmits it to the database generation unit 115 (step S1403).

The database generation unit 115 receives the response data from the sample target terminal 141 and the data from the map server 151 and the weather server 152, executes clustering, and creates the cluster-specific QoL management table 300 and the affiliated cluster management table 310. An entry is generated (step S1404).

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

<Calculation process of objective QoL value>
FIG. 15 is a sequence diagram illustrating an example of a procedure for calculating a target QoL value. Through the operation of the local government servicer 160 that has received a request from the research agency 1300, the local government servicer terminal 161 selects the sample subject ID 312 to be investigated (hereinafter referred to as the survey sample subject ID 312), and selects the selected sample subject to investigate. The user ID 312 is transmitted to the evaluation device 100 (step S1501). The survey target sample subject ID 312 to be transmitted may be the sample subject ID 312 of the sample subject 140 selected at random, or may be the sample subject ID 312 of the sample subject 140 belonging to a specific cluster.

Upon receiving the research sample subject ID 312, the estimating unit 116 estimates the QoL value 421 of the daily life activity 201 (step S1502). Specifically, for example, the evaluation device 100 transmits a sampling trigger to the sample subject terminal 141 having the survey subject sample subject ID 312 for each of the survey subject sample subject IDs 312, and from the sample subject terminal 141, Get current detection data.

The estimation unit 116 also acquires meteorological data corresponding to the time of the detected data from the weather server 152, acquires facility information corresponding to the latitude and longitude at the time of the detected data from the map server 151, and provides services from a public site (not shown). Get information. In this way, the estimation unit 116 acquires behavior data.

The estimation unit 116 uses the acquired behavior data to refer to the database 112 and estimates the QoL value 421 of the daily life activity 201 for the sample subject 140 of the survey sample subject ID 312. Then, the estimating unit 116 includes a usage availability status 420, estimated QoL value 421 of daily life activity 201, daily life activity 422, means of daily living 423, number of people living 424, daily life activity start time 425, daily life activity end time 426, latitude and longitude information 427 , facility 428, and service information 429 are stored in the QoL calculation DB 120 as action history data (step S1503).

When the local government servicer terminal 161 receives the completion notification of data storage in step S1503 for all survey target sample subject IDs 312 transmitted in step S1501, it transmits the analysis viewpoint to the evaluation device 100 as an analysis start signal (step S1504). . The analysis viewpoint includes, for example, the identification code of the evaluation target 621, attribute information (demographic 411 and psychographic 412), facility information, and service information. For example, when the local government servicer 160 wants to analyze "life activities in XX park" and obtain its objective QoL value, the local government servicer 160 sets the identification code "000" of the evaluation target 621 to the local government servicer terminal 161, and transmits its identification code “000” to the evaluation device 100.

Upon receiving the analysis viewpoint, the evaluation device 100 acquires the function definition 630 corresponding to the identification code of the evaluation target 621 from the local government servicer terminal 161 from the derivation QoLDB 130 (step S1505), and outputs it to the QoL calculation unit 103. Further, as described in [Example of calculation of objective QoL value regarding evaluation target 621], the QoL calculation unit 103 acquires the QoL value 421 of the corresponding daily life activity 201 and the model parameter 623 of the evaluation target 621, and the QoL calculation unit 103 (step S1506).

The QoL calculation unit 103 calculates a target QoL value by substituting the QoL value 421 of the daily life activity 201 and the model parameter 623 of the evaluation target 621 into the function definition 630, and transmits it to the local government servicer terminal 161 (step S1507). This completes the target QoL value calculation process.

<Utilization example>
Next, an example of application of the evaluation system 10 according to the present embodiment to infrastructure will be described. Here, we will explain park management as an example of infrastructure.

FIG. 16 is an explanatory diagram showing an example of utilization for park management. Examples of effectiveness evaluation indicators in conventional park management include green coverage, park area, and number of parks. These values basically remain unchanged once the park is designed. In conventional city planning, by constructing parks to increase the amount of greenery, the amount of greenery increases compared to before the park construction, but after the park construction, the amount of greenery does not increase. In addition, although the park was maintained, it did not lead to an increase in the number of users.

Therefore, the evaluation system 10 according to this embodiment is applied to park management, and by analyzing factors that prevent people from using the park and hidden needs, soft measures can be considered and the considered measures can be implemented.

Specifically, for example, the evaluation device 100 collects data from the sample subject terminal 141 and external site 150 of the sample subject 140 who uses the park, and calculates the QoL value of the sample subject 140's life activities 201 in the park. 421 is calculated. Then, the evaluation device 100 calculates the objective QoL value using the greening of the park used by the sample subject 140 as the evaluation target 621.

For example, if it is found that the objective QoL value related to greening is low even though the amount of greenery has increased due to park maintenance, the policy designer obtains the QoL value of the daily activities 201 of people who spend time in the park. As a result, for example, the QoL value of the daily life activity 201 for the sample subject 140 whose daily life activity is "childcare" is different from the QoL value of the daily life activity 201 for the sample subject 140 whose daily life activity is park use other than "childcare". Suppose it is lower than the value. This means that greening was not supported by the sample subjects 140 who are raising children.

Therefore, in order to improve the use of sample subjects 140 who are raising children, it is assumed that the policy designer has considered and held an event in which benchers and children can participate. As a result, the QoL value of the daily life activity 201 of the sample subject 140 whose daily life activity 201 is "raising children" increased compared to before the bench was installed or before the event was held. When the evaluation device 100 calculated the objective QoL value related to bench installation and the QoL value related to event holding, it was found that the objective QoL value was higher than the objective QoL value related to greening. In this way, the evaluation device 100 can make policy designers aware of the necessity of measures to enhance the effects of park maintenance, and can evaluate the effects of the measures in real time. As a result, operations and improvements that increase the value of park facilities, which were previously impossible, will become possible.

Another example is the scenario of a self-driving bus. Conventional performance evaluation indicators were efficiency of movement and reduction of travel time. The measures actually improved these indicators and confirmed their effectiveness, but there are many elderly residents in the target area, and when evaluating the QoL value 421 of 201 daily activities, it was found that the conversation on the self-driving bus was Based on the quantity, the longer the ride time, the higher the QoL value 421 of the daily life activity 201 in which the self-driving bus was used as a means of daily living 423. The QoL value was higher than that of 421, indicating that the self-driving bus also functions as a social gathering place.

As a result, the number of users of self-driving buses further increased, and the number of users of self-driving buses increased even further. The QoL score (421) of daily life activities (201) for using driving buses as a means of living also improved. Furthermore, in the daily life activities defined by evaluation target 621, when a self-driving bus was used as a means of daily living, the purpose QoL value also increased compared to before the improvement.

In this scenario, by utilizing the evaluation system 10 of this embodiment, it is possible to discover needs and user appeal values that could not be seen using conventional effectiveness evaluation indicators, and improve residents' QoL without making large infrastructure investments. This is an example of an improvement that was achieved.

In this way, the evaluation system 10 according to this embodiment can be expected to have similar effects in all infrastructure operations, administrations, and city management of local governments. Moreover, since the QoL value 421 and the objective QoL value of the daily life activity 201 can be calculated immediately at the necessary timing, it is possible to significantly improve the cycle of city management.

<City management cycle>
FIG. 17 is a conceptual diagram showing a city management cycle realized by the evaluation system 10. Conventional urban planning has mainly been a long-term process of five to 10 years, from master plan planning to implementation, evaluation, and updating, requiring a lot of effort and time at each stage. As a result, the adaptation of measures was limited to optimizing the conventional system, and it was not sufficiently reflected in the impact on residents and their sense of satisfaction and fulfillment with their lives.

When the evaluation system 10 is applied, the acquisition of data for calculating the QoL value 421 of the daily life activity 201, the calculation of the QoL value 421 of the daily life activity 201, and the purpose QoL are performed immediately. This makes it possible to provide short-term feedback of several months or less, making it possible to promote effective urban planning that responds to on-site issues. Furthermore, with regard to intangible improvements in public services and flexible operation of infrastructure, it becomes possible to evaluate the effects in a short period and accumulate evaluation results, and new value can be continuously added to existing infrastructure and measures after implementation. It becomes possible to realize the cycle in a short period and with certainty.

<Relationship between administrative services and measures for the elderly and expected outcomes>
FIG. 18 is an explanatory diagram showing an example of the relationship between administrative services and measures for the elderly and expected results. Through concrete activities (measures) and their direct results, there is a causal relationship between initial (short-term), medium-term, and long-term outcomes. In the city management cycle shown in Figure 17, the effect of improving QoL values 421 of daily life activities 201 and purpose QoL values, which are the direct results of residents' actual experiences, is measured in short cycles for each measure, immediately after the measures are implemented. It is possible to evaluate the By using evaluation results and causal relationships, it becomes possible to select and weed out measures that will lead to long-term results, such as a master plan, immediately after implementing the measures. This makes it possible to reduce the number of cases of policy failure to the utmost from the viewpoint of

As described above, according to the present embodiment, it is possible to automatically acquire the QoL value and the target QoL value of daily life activities with a small implementation load and immediate implementation results. This will enable policy designers to implement effective measures in a timely manner. In addition, it is possible to immediately measure whether the measures taken are effective or not, making it easier to change policy directions.

Note that the present invention is not limited to the embodiments described above, and includes various modifications and equivalent configurations within the scope of the appended claims. For example, the embodiments described above have been described in detail to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to having all the configurations described. Further, a part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Furthermore, the configuration of another embodiment may be added to the configuration of one embodiment. Furthermore, other configurations may be added, deleted, or replaced with some of the configurations of each embodiment.

Further, each of the above-mentioned configurations, functions, processing units, processing means, etc. may be realized in part or in whole by hardware, for example by designing an integrated circuit, and a processor realizes each function. It may also be realized by software by interpreting and executing a program.

Information such as programs, tables, and files that realize each function is stored in storage devices such as memory, hard disks, and SSDs (Solid State Drives), or on IC (Integrated Circuit) cards, SD cards, and DVDs (Digital Versatile Discs). It can be stored on a medium.

Furthermore, the control lines and information lines shown are those considered necessary for explanation, and do not necessarily show all the control lines and information lines necessary for implementation. In reality, almost all configurations can be considered interconnected.

10 Evaluation system 100 Evaluation device 101 Generation unit 102 List generation unit 103 QoL calculation unit 114 Question generation unit 115 Database generation unit 116 Estimation unit 120 QoL calculation DB
130 Derivation QoLDB
140 Sample target person 141 Sample target person terminal 160 Local government servicer 161 Local government servicer terminal 201 Daily life activities 202 Activity environment 203 Questions

Claims (10)

An evaluation device comprising a processor that executes a program, and a storage device that stores the program,
A first satisfaction level for each group to which the sample subject belongs, which is defined for each activity pattern of daily life activities performed by the sample subject, is stored for each of the daily life activities, and the sample subject and the sample subject belong to the group. accessible to a first database associated with the population;
The processor includes:
When the behavior data is acquired from the sample target terminal capable of detecting behavior data indicating the sample target's behavior, an estimation process of estimating the daily life activity and the activity pattern of the sample target based on the behavior data. and,
In the first database, from among the first satisfaction levels for each of the activity patterns of the group to which the sample subject belongs in the daily life activities estimated by the estimation process, the satisfaction level estimated by the estimation process is a registration process of extracting the first satisfaction level of the activity pattern and registering it in a second database;
an acquisition process for acquiring an evaluation target defined by a specific daily life activity;
The first satisfaction level for the specific life activity that corresponds to the evaluation target acquired by the acquisition process from among the first satisfaction levels for each of the life activities stored for each sample target in the second database. an extraction process to extract the
a calculation process of calculating a second satisfaction level regarding the evaluation target based on the first satisfaction level of the specific life activity extracted by the extraction process;
an output process that outputs the second satisfaction level calculated by the calculation process;
An evaluation device characterized by performing the following. The evaluation device according to claim 1,
The processor includes:
Generating questions regarding the daily life activities and transmitting them to the terminal; as a result of transmitting the questions to the terminal, acquiring the first satisfaction level for each of the activity patterns of the daily life activities from the terminal; , executing a generation process of generating the first database by associating the sample target with the group to which it belongs based on the first satisfaction level for each activity pattern;
An evaluation device characterized by: The evaluation device according to claim 2,
In the generation process, the processor generates the group by clustering the sample targets based on the first satisfaction level for each activity pattern according to the daily life activity.
An evaluation device characterized by: The evaluation device according to claim 2,
The question includes a plurality of life activities that the sample subject can select from.
An evaluation device characterized by: The evaluation device according to claim 4,
The question includes a plurality of daily life activities from which the sample subject can select, and a plurality of activity environments from which the sample subject can select for the daily life activities selected from the plurality of daily 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 evaluation device according to claim 4,
The questions include questions to confirm the first satisfaction level,
An evaluation device characterized by: The evaluation device according to claim 6,
The above-mentioned questions are questions based on the World Health Organization's QoL evaluation method,
An evaluation device characterized by: The evaluation device according to claim 1,
A plurality of calculation methods for calculating the second satisfaction level are selectably defined,
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: An evaluation method using an evaluation device including a processor that executes a program, and a storage device that stores the program,
A first satisfaction level for each group to which the sample subject belongs, which is defined for each activity pattern of daily life activities performed by the sample subject, is stored for each of the daily life activities, and the sample subject and the sample subject belong to the group. accessible to a first database associated with the population;
The processor includes:
When the behavior data is acquired from the sample target terminal capable of detecting behavior data indicating the sample target's behavior, an estimation process of estimating the daily life activity and the activity pattern of the sample target based on the behavior data. and,
In the first database, from among the first satisfaction levels for each of the activity patterns of the group to which the sample subject belongs in the daily life activities estimated by the estimation process, the satisfaction level estimated by the estimation process is a registration process of extracting the first satisfaction level of the activity pattern and registering it in a second database;
an acquisition process for acquiring an evaluation target defined by a specific daily life activity;
The first satisfaction level for the specific life activity that corresponds to the evaluation target acquired by the acquisition process from among the first satisfaction levels for each of the life activities stored for each sample target in the second database. an extraction process to extract the
a calculation process of calculating a second satisfaction level regarding the evaluation target based on the first satisfaction level of the specific life activity extracted by the extraction process;
an output process that outputs the second satisfaction level calculated by the calculation process;
An evaluation method characterized by carrying out. A first satisfaction level for each group to which the sample subject belongs, which is defined for each activity pattern of daily life activities performed by the sample subject, is stored for each of the daily life activities, and the sample subject and the sample subject belong to the group. An evaluation system in which an evaluation device capable of accessing a first database associated with the group and a terminal capable of detecting behavioral data indicating the behavior of the sample target can communicate,
The terminal is
executing a process of acquiring the behavior data and transmitting it to the evaluation device;
The evaluation device includes:
an estimation process of estimating the daily life activity and the activity pattern of the sample target based on the behavioral data when the behavioral data is acquired from the terminal;
In the first database, from among the first satisfaction levels for each of the activity patterns of the group to which the sample subject belongs in the daily life activities estimated by the estimation process, the satisfaction level estimated by the estimation process is a registration process of extracting the first satisfaction level of the activity pattern and registering it in a second database;
an acquisition process for acquiring an evaluation target defined by a specific daily life activity;
The first satisfaction level for the specific life activity that corresponds to the evaluation target acquired by the acquisition process from among the first satisfaction levels for each of the life activities stored for each sample target in the second database. an extraction process to extract the
a calculation process of calculating a second satisfaction level regarding the evaluation target based on the first satisfaction level of the specific life activity extracted by the extraction process;
an output process that outputs the second satisfaction level calculated by the calculation process;
An evaluation system characterized by carrying out.

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