Keywords

1 Introduction

The structure of local communities in Japan has needed to change after the Tohoku Earthquake. Japan is the first country to have a super-aging society, first noted in 2007. According to the latest Annual Health, Labor and Welfare Report, on the other hand, the connections have been weak among members of the communities, but the number of people who want to help in the community has increased [2]. That is, local communities need to be vitalized for the regaining relationship.

This type of social situation has prompted the development of several approaches from the computer science field. For example, the Strategy Proposal of 2012, the Japan Science and Technology Agency includes the person-watching system for the elderly and smart city system are examples of these approaches [3]. Despite the need for these approaches in many communities, most communities cannot use them casually.

The research on “constructing” the system has been successful, but that on its “usage” is in the developing stage. Moreover, the introduction of the system does not always guarantee local activation, which always depends on the locals who will notice their problems and act to solve them. If residents can be aware of their invisible relationship that they are usually unconscious, and if they understand its importance, they could vitalize their community through sustaining and promoting it? That is the concept of resident-centered vitalization of a local community.

This research aims to realize the resident-centered community design by utilizing of information and communication technology (ICT). We defined “a media spot” as the place where communication is active in an area. As a place for creating and strengthening the relationship, we visualize media spot [1] and create an opportunity to regain the relationship within the community.

In recent years, SaaS (Software as a Service) type data visualization service has been prospering due to spread of cloud computing. On the other hand, there is no service for visualizing and analyzing location information and relationship integratedly. In this research, in order to visualize and analyze media spots, we developed a tool using a web interface that can visualize the location information and the relationship integratedly. We visualized location information and passing-each-other data from Bluetooth collected in the field experiment that we have been doing since 2013 using this system.

2 Resident-centered Vitalization of the Local Community

Ushino’s research (1982) on local resident-based regional development explained the importance of such concept and proposed a system called “Kande System” [4]. Ushino said that after the industrialization and urbanization in the 1950s, the village communities in the rural areas were divided by the agricultural policy and then re-integrated in the 1970s to create a new regional system. The importance of local resident-based regional development has already been a significant research topic since the 1980s.

Meanwhile, Yoshizumi’s case study (2013) analyzed the way for locals to develop regions sustainably and suggested the “Eco Card System” [5]. In this system, the locals are given a stamp card called “Eco Card” that promotes environmental activities, thereby creating a setup for the locals to be involved in the region. This system highlights the importance of visualizing or making the locals notice the problems for them to manage local resident-based regional development.

With the introduction of information communication technology (ICT), it is temporarily possible to solve the challenges of a local community. However, to vitalize a local community continuously, residents must solve them positively. For residents to solve the challenges of a local community by themselves, they must be conscious of these challenges. Thus, “resident-centered” development means that “residents themselves solve the challenges faced by their local community.” In this research, we aimed to establish a methodology that enables them to do so by visualization.

3 Overview of the Visualization and Analysis System

3.1 User Interface

Figure 1 shows a user interface that is actually visualized using the system. The upper left side of the screen is a map, the upper right side of the screen is the relationship (undirected graph) based on the passing-each-other data and the lower part of the screen is the query input part. We can input start time, interval to visualize, and send a query. Then, the result from the API is drawn on the upper part of the screen.

Fig. 1.
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User interface of the visualization and analysis system

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3.2 Architecture

This system consisted of a “database” in which raw data is stored, “Web API” for returning data based on data acquired from the database, and “Web front-end” for drawing data acquired from the API.

We used “MySQL,” which is one of the RDBMS. A table was built for each type of data in the database.

The Web API was built using “Django” which is one of the Web frameworks described using Python. Django, like a general Web framework, can easily build Web applications by following the design pattern. In this research, we used Python-based scientific computing library, therefore we used Python web framework that has a high affinity. In addition, we used the “Django REST framework” package specialized for API creation.

We used HTML5, CSS3, Vue.js to construct the Web front-end. Vue.js is a JavaScript framework that makes it easy for browsers to update screens dynamically. We adopted this mechanism because this system mainly focuses on updating screens on the browser. We used Google Maps JavaScript API and D3.js to draw data.

The flow of the system is shown in Fig. 2. First of all, we connect to the Web front-end using a Web browser and designate the data period etc. The Web front-end builds a query to send to the API and sends it to the API Endpoint. Then, the Web front-end draws using the data returned from the API.

There are two types of APIs, one that returns location information based on a query and one that returns an undirected graph showing the relationship. The API that returns location information calls data from the database, converts it to JSON format, and returns it to the client. The API that returns the undirected graph calls the data of the passing-each-other data from Bluetooth from the database, converts it to the undirected graph, and then returns the data to the client in the JSON format. For conversion to an undirected graph, we used Python’s network analysis library “NetworkX”.

Fig. 2.
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Flow diagram of the system focused on server and client

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4 Experiment Method

4.1 Overview of Field Experiment

We acquired residents’ activity data with smartphones lent to them in the Makishima area in Uji City, Kyoto, Japan, in cooperation with members of the non-profit corporation Makishima Kizuna-no-Kai. Activity data means “location information,” “send and receive emails,” “telephones reception and transmission” and “passing-each-other data from Bluetooth [6].” In this paper, we analyzed “location information” and “passing-each-other data from Bluetooth” using the system.

4.2 Experimental Area and Cooperators’ Attribute

This field experiment has been conducted in the Makishima area in Uji City, Kyoto, Japan.

Uji City is located in the south of Kyoto on the south side of Kyoto City. The population of Uji City as of April 1, 2016, is about 190,000 and 15,000 (about 8%) of them live in the Makishima area. Uji City has attracted lots of attention as a residential area near Kyoto, Osaka, and Kobe since the early 1960’s. As a result, residential land was developed in Uji City and the population remarkably increased. The Makshima area is one of the development areas in Uji City, and there is a densely populated area such as a housing complex. Blocks of the development area in the early 1960’s are aging, but the population of the whole Makishima area is slightly increasing.

The experimental cooperators live in the Makishima area. They are members of the non-profit corporation Makishima Kizuna-no-Kai. Table 1 shows the attributes of the experimental cooperators. A lot of experimental cooperators are over 65 years old. The reason is that people who retired at mandatory age mainly join the regional development.

Table 1. Attributes of field experiment
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Table 2 shows the periods of the field experiment. We instructed the experimental cooperators to use the lent smartphone at all times for the duration of the experiment. However, from the perspective of informed consent, we instructed that the experimental cooperators can switch off the smartphone when he/she does not want to inform his/her location information.

Table 2. Periods of field experiment
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4.3 Experimental Installation

Table 3 shows the specification of smartphones that are used in the field experiment. Smartphones used in the first period were discredited mostly due to sluggish actions and small screen. Accordingly, we lent them stylus pens for the improvement of usability. This way partly resolves that discredit.

Following the suggestion of the first period, smartphones using the second and third periods was chosen as quick action and big screen. Some of the experimental cooperators have his/her smartphone due to the spread of smartphones compared to the first period. That discredit is significantly resolved by these external factors also.

Table 3. Specification of smartphones
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Fig. 3.
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A result of visualization by the system for analysis

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5 Results of the Analysis and Discussion

Figure 3 shows a certain period using the system. When we watched only location information, we could know that the meeting was held at the facilities near the plotted place, but we could not know which people were actually present. However, the structure of the undirected graph shows who was present at the meeting. On the other hand, it was very difficult to estimate the type of event with only the graph structure, but it was made possible to some extent by combining with the location information.

Fig. 4.
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A result of visualization that we can observe many edges and nodes

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Fig. 5.
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A result of visualizing a holiday

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Figures 4 and 5 show the days when the meeting was held and the holidays.

Several problems also surfaced when analyzing with the system.

First, it is known that there is a limit to the number of location information that can be drawn at one time, and the action becomes slow when rendering the raw data because the location information is dynamically rendered by the client. As a countermeasure, it is possible to summarize markers, to thin out location information, etc. However, we considered methods that do not lose meaning from a set of location information.

Next, the system visualizes location information and relationship at a certain time. That is, users should visualize data sequentially and analyze results of visualizing it. In other words, users must continue to visualize while incrementing time counter until they find interesting results of visualizing. Such work is very inefficient, therefore it is necessary to assist analysis such as visualizing a change of centrality in a certain period in advance and so on.

6 Conclusion

This research aims to realize the resident-centered community design by utilizing of information and communication technology (ICT) and to create an opportunity to regain relationship within the community by visualizing media spot. In order to visualize and analyze the location information and the relationship integratedly, we developed a system using the Web interface.

As a result of visualization using the system, it became easy to guess the type of meeting and attendees, which can help analysis. On the other hand, it turned out that there is room for improvement in drawing speed and analysis efficiency. We would like to improve the system in the future so that we could get more interesting analysis results.