**3. Problem solving by connective AI**

#### **3.1 Description of connective AI**

To address issues in the variety in living function, intervention needs, data fragmentation, and variety in privacy exposure, we believe in the importance of an approach referred to as "connective AI" that allows individual lives to be connected with each other and efficacy to be scaled to effectiveness by computerizing places of living in accordance with the private policy of individual facilities and connecting them with each other through a network. We believe that connective AI is essential to building a living function-resilient society.

While our lives and living environments have individuality and are different from each other, there are many similar phenomena and environments. Skillful processing of information should make it possible to share information and convert it into knowledge. As pointed out by Herbert Simon, a physical phenomenon is essentially nonlinear when viewed hierarchically. We can develop a science based on the assumption that a physical phenomenon in the target layer can be modeled by associating it with feature quantities in the sublayers.

#### **3.2 Smart living lab coevolving with connective AI**

As **Figure 2** shows, to work with connective AI in concrete terms, we at the National Institute of Advanced Industrial Science and Technology (AIST) have developed a smart living lab in cooperation with children's hospitals, rehabilitation hospitals, intensive care homes for the elderly, and private homes. The term "smart living lab" here means (1) a place where we identify needs in field settings with user participation and adaptively explore whether new proposals to meet the needs are acceptable to the users in these "living labs" and (2) a place where we collect data, using AI and sensors, on activities of daily living of users (including children as non-main users) with a variety in living function (a smart field).

A system that allows daily life data fragmented in these places to be shared is essential to understanding the variety in living function. We need a new approach for information processing (AI for reality) to clarify real conditions. A system to

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**technology**

**Figure 2.**

*Smart living lab developed by AIST.*

*Living Function-Resilient Society in the Centenarian Era: Living Safety Technology Based…*

link the verification of efficacy at the laboratory level to verification of effectiveness in facilities and communities is essential to developing solutions to support daily life. There is a strong need for a direction (reality for AI) for support technology to be put in place. We need to develop a living ecosystem suitable for individuals by combining stakeholders involved and social resources. We need to understand a field system as a complex system from a system science perspective and develop solutions that scale to different field settings. The next section describes connective AI technology being developed at AIST to build a living function-resilient society

and smart living lab activities using the technology.

**integrated manner (issue identification)**

causes the severity of injury to increase.

**4. Attempt to demonstrate safety in daily life using AI and IoT** 

**4.1 Raising awareness using data scattered across multiple organizations in an** 

A recent text mining technique allows us to process quantities of data that are too big for humans to process. It has the potential for social function, which can be referred to as awareness (issue identification). Using data on medical treatment costs and situations resulting in injury from the Japan Sport Council, we at AIST are developing a technique that automatically analyzes situations that may result in severe injury. This technique identifies phrases unique to situations resulting in severe injury from free descriptive text, based on the assumption that treatment costs increase with increasing severity of injury. It is called "severity cliff analysis [6]." As shown in **Figure 3**, when similar situations are plotted in descending order of treatment costs, a cliff appears where the treatment costs change sharply. The technique allows us to identify the inflection point of the cliff and analyze what

*DOI: http://dx.doi.org/10.5772/intechopen.85422*

*Living Function-Resilient Society in the Centenarian Era: Living Safety Technology Based… DOI: http://dx.doi.org/10.5772/intechopen.85422*

**Figure 2.** *Smart living lab developed by AIST.*

*Internet of Things (IoT) for Automated and Smart Applications*

in daily life.

**2.4 Variety in privacy exposure**

**3. Problem solving by connective AI**

to building a living function-resilient society.

associating it with feature quantities in the sublayers.

**3.2 Smart living lab coevolving with connective AI**

non-main users) with a variety in living function (a smart field).

**3.1 Description of connective AI**

abuse of the elderly.

integrated manner and thereby to evaluate the variety in living function among children and elderly people, identify issues associated with the variety, and evaluate potential solutions. More importantly, we need a method of detecting their changes

system for implementing the collective impact model based on the data.

In addition to data fragmentation, services as solutions are fragmented. A collective impact model has been proposed to achieve effectiveness by collectively using stakeholders and social resources with a common purpose [5]. There is a need for a

The definition of personal information has been changing. Besides that, there are a variety of ideas about privacy exposure. This means that there is a "one-sizefits-all" issue also in privacy policy; we need a system and technology to control information according to the variety of ideas of individuals and facilities about privacy, instead of developing a privacy policy common to all people and facilities. For example, there are facilities that are positive about installing cameras to prevent

To address issues in the variety in living function, intervention needs, data fragmentation, and variety in privacy exposure, we believe in the importance of an approach referred to as "connective AI" that allows individual lives to be connected with each other and efficacy to be scaled to effectiveness by computerizing places of living in accordance with the private policy of individual facilities and connecting them with each other through a network. We believe that connective AI is essential

While our lives and living environments have individuality and are different from each other, there are many similar phenomena and environments. Skillful processing of information should make it possible to share information and convert it into knowledge. As pointed out by Herbert Simon, a physical phenomenon is essentially nonlinear when viewed hierarchically. We can develop a science based on the assumption that a physical phenomenon in the target layer can be modeled by

As **Figure 2** shows, to work with connective AI in concrete terms, we at the National Institute of Advanced Industrial Science and Technology (AIST) have developed a smart living lab in cooperation with children's hospitals, rehabilitation hospitals, intensive care homes for the elderly, and private homes. The term "smart living lab" here means (1) a place where we identify needs in field settings with user participation and adaptively explore whether new proposals to meet the needs are acceptable to the users in these "living labs" and (2) a place where we collect data, using AI and sensors, on activities of daily living of users (including children as

A system that allows daily life data fragmented in these places to be shared is essential to understanding the variety in living function. We need a new approach for information processing (AI for reality) to clarify real conditions. A system to

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link the verification of efficacy at the laboratory level to verification of effectiveness in facilities and communities is essential to developing solutions to support daily life. There is a strong need for a direction (reality for AI) for support technology to be put in place. We need to develop a living ecosystem suitable for individuals by combining stakeholders involved and social resources. We need to understand a field system as a complex system from a system science perspective and develop solutions that scale to different field settings. The next section describes connective AI technology being developed at AIST to build a living function-resilient society and smart living lab activities using the technology.
