The Role of Kansei/Affective Engineering and Its Expected in Aging Society

Shiizuka, Hisao; Hashizume, Ayako

doi:10.1007/978-3-642-22194-1_33

Cited by 3 publications

(5 citation statements)

References 3 publications

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“…Even though the methods have only been mentioned one time by the 43 case studies, they have been adapted and applied by different fields for years. Several publications are interesting works that may help readers have a better idea about the Kano model published by Zhao et al ( 2020 ) and Shahin et al ( 2013 ), Kansei engineering reviewed by Shiizuka and Hashizume ( 2011 ) and Coronado et al ( 2020 ), BPMN studied by Ko et al ( 2009 ) and Chinosi and Trombetta ( 2012 ).…”

Section: Literature Characterization Of Human-centred Design In Industry 40mentioning

confidence: 99%

Human-centred design in industry 4.0: case study review and opportunities for future research

2021

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The transition to industry 4.0 has impacted factories, but it also affects the entire value chain. In this sense, human-centred factors play a core role in transitioning to sustainable manufacturing processes and consumption. The awareness of human roles in Industry 4.0 is increasing, as evidenced by active work in developing methods, exploring influencing factors, and proving the effectiveness of design oriented to humans. However, numerous studies have been brought into existence but then disconnected from other studies. As a consequence, these studies in industry and research alike are not regularly adopted, and the network of studies is seemingly broad and expands without forming a coherent structure. This study is a unique attempt to bridge the gap through the literature characteristics and lessons learnt derived from a collection of case studies regarding human-centred design (HCD) in the context of Industry 4.0. This objective is achieved by a well-rounded systematic literature review whose special unit of analysis is given to the case studies, delivering contributions in three ways: (1) providing an insight into how the literature has evolved through the cross-disciplinary lens; (2) identifying what research themes associated with design methods are emerging in the field; (3) and setting the research agenda in the context of HCD in Industry 4.0, taking into account the lessons learnt, as uncovered by the in-depth review of case studies.

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Section: Literature Characterization Of Human-centred Design In Industry 40mentioning

confidence: 99%

Human-centred design in industry 4.0: case study review and opportunities for future research

2021

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“…A typical motivation of these academic projects is to overcome the technological performance reached by competitors. This approach denoted as machine-centered design is generally the main focus of academic and technological communities in the initial years of research and development of novel technological devices [24,25]. In many projects performing machine-centered research, the use and installation of complex and academic-oriented software frameworks and Linux-based OS are often considered trivial and preferred tasks.…”

Section: Motivationsmentioning

confidence: 99%

“…The inclusion of end users in research activities must also take into account the resources, capabilities, needs, and desires of humans by providing usable, portable, accessible, secure and aesthetic products [27,28]. This approach often denoted as human-centered design is an essential step to reach maturity and economical success when developing technological products for the general user [24,29,30]. A recent human-centered trend in HRI research in to bring robotic research activities, often done in laboratories, to "in the wild" (i.e., natural and every-day settings) and unstructured scenarios [1,23].…”

Section: Motivationsmentioning

confidence: 99%

“…While NEP can be used for academic-oriented applications such as shown in this article, the main focus of NEP is to support human-centered design tasks, where non-roboticist are included in the design processes of robots. Human-centered approaches are intrinsically multidisciplinary tasks whose main focus is the development of accessible, desirable, intuitive, friendly and usable products able to satisfy human needs and expectations [24,29]. In fact, most researchers in the robotics community mostly focus on machine-centered approaches being novelty and performance the main design objectives.…”

Section: What Is Nep?mentioning

confidence: 99%

“…In fact, most researchers in the robotics community mostly focus on machine-centered approaches being novelty and performance the main design objectives. As described in [24,25], mature technologies nowadays adopted by the general public have historically switched their design approaches from machine-centered to human-centered. An example of a human-centered task presented in this article is End-User Development [28].…”

Section: What Is Nep?mentioning

confidence: 99%

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Towards IoT-Aided Human–Robot Interaction Using NEP and ROS: A Platform-Independent, Accessible and Distributed Approach

Coronado

Venture

2020

Sensors

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This article presents the novel Python, C# and JavaScript libraries of Node Primitives (NEP), a high-level, open, distributed, and component-based framework designed to enable easy development of cross-platform software architectures. NEP is built on top of low-level, high-performance and robust sockets libraries (ZeroMQ and Nanomsg) and robot middlewares (ROS 1 and ROS 2). This enables platform-independent development of Human–Robot Interaction (HRI) software architectures. We show minimal code examples for enabling Publish/Subscribe communication between Internet of Things (IoT) and Robotics modules. Two user cases performed outside laboratories are briefly described in order to prove the technological feasibility of NEP for developing real-world applications. The first user case briefly shows the potential of using NEP for enabling the creation of End-User Development (EUD) interfaces for IoT-aided Human–Robot Interaction. The second user case briefly describes a software architecture integrating state-of-art sensory devices, deep learning perceptual modules, and a ROS -based humanoid robot to enable IoT-aided HRI in a public space. Finally, a comparative study showed better latency results of NEP over a popular state-of-art tool (ROS using rosbridge) for connecting different nodes executed in local-host and local area network (LAN).

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