Cybermatics: Cyber–physical–social–thinking hyperspace based science and technology

Ning, Huansheng; Liu, Hong; Ma, Jun; Yang, Laurence T.; Huang, Runhe

doi:10.1016/j.future.2015.07.012

Cited by 131 publications

(51 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Bizopoulos and Koutsouris [31] advocated the creation of complex theoretical models not only in view of its structure and function but also in the refinement for application. According to the 5C architectural model [32,33], the CPS could provide conceptual guidance for the development of interactive clothing. The technical process of interactive clothing design and development, that is, the technical relevance of interactive clothing and CPS were revealed in the cyber-physical-clothing systems (CPCS) model ( Figure 1).…”

Section: Creating the Cpcs Modelmentioning

confidence: 99%

Integrating Interactive Clothing and Cyber-Physical Systems: A Humanistic Design Perspective

Wang

Fang

Nagai

et al. 2019

Sensors

View full text Add to dashboard Cite

This study is aimed at bridging the gap from a transdisciplinary perspective between cyber-physical systems (CPS) architecture in the field of information science and emotional design in the field of humanistic science for interactive fashion innovation. Information related to a familiar feeling in the process of interactive clothing design is used to explain how the transformation could be realized from data. By creating the cyber-physical-clothing systems (CPCS), the architecture model in the hyper world and takes the development process of an interactive parent-child clothing as a case study for analyzing the transformation from the physical signal input to the social symbol recognition output. The experimental results, which from the perspective of clothing art design rather than information discipline, show that interactive parent-child clothing is not only suitable for the rehabilitation of autistic children but also recognized by most parents. The reasonable embedding of sensing technology can greatly enhance the added value of clothing products. This study provides a fruitful practical application reference for designers who are engaged in the field of art and design but not familiar with the relevant information technology. Furthermore, the application principle and the technical process of CPCS for further interactive clothing design is explained.

show abstract

Section: Creating the Cpcs Modelmentioning

confidence: 99%

Integrating Interactive Clothing and Cyber-Physical Systems: A Humanistic Design Perspective

Wang

Fang

Nagai

et al. 2019

Sensors

View full text Add to dashboard Cite

show abstract

“…However, this assumption is known in many cases to not be true and different maintenance policies may apply better to each individual asset. A novel approach to deal with multi unit systems is the Social Internet of Things [7], which provides a paradigm for objects to connect with each other and exploit asset individualities to improve global performance [19].…”

Section: Introductionmentioning

confidence: 99%

Collaborative prognostics in Social Asset Networks

Palau

Liang

Lütgehetmann³

et al. 2019

Future Generation Computer Systems

View full text Add to dashboard Cite

With the spread of Internet of Things (IoT) technologies, assets have acquired communication, processing and sensing capabilities. In response, the field of Asset Management has moved from fleet-wide failure models to individualised asset prognostics. Individualised models are seldom truly distributed, and often fail to capitalise the processing power of the asset fleet. This leads to hardly scalable machine learning centralised models that often must find a compromise between accuracy and computational power. In order to overcome this, we present a novel theoretical approach to collaborative prognostics within the Social Internet of Things. We introduce the concept of Social Asset Networks, defined as networks of cooperating assets with sensing, communicating and computing capabilities. In the proposed approach, the information obtained from the medium by means of sensors is synthesised into a Health Indicator, which determines the state of the asset. The Health Indicator of each asset evolves according to an equation determined by a triplet of parameters. Assets are given the form of the equation but they ignore their parametric values. To obtain these values, assets use the equation in order to perform a non-linear least squares fit of their Health Indicator data. Using these estimated parameters, they are interconnected to a subset of collaborating assets by means of a similarity metric. We show how by simply interchanging their estimates, networked assets are able to precisely determine their Health Indicator dynamics and reduce maintenance costs. This is done in real time, with no centralised library, and without the need for extensive historical data. We compare Social Asset Networks with the typical self-learning and fleet-wide approaches, and show that Social Asset Networks have a faster convergence and lower cost. This study serves as a conceptual proof for the potential of collaborative prognostics for solving maintenance problems, and can be used to justify the implementation of such a system in a real industrial fleet.

show abstract

“…The emanating overlap between IoT and Social technologies has been pointed out in recent literature, with researchers (e.g., Zhang, Jin, & El Baz, 2015) predicting such integration will help evolve innovative sensing and computing capabilities. The extension of social relationships to share contextual data that permit better coordination between humans and smart devices (Ortiz, Hussein, Park, Han, & Crespi, 2014) shapes the development of Social IoT, a form of cyber-physical social system (Ali, 2015;Ning et al, 2016). While some researchers are addressing the complexities (e.g., Asl, Iera, Atzori, & Morabito, 2013) to realize such technology integration, others are analyzing challenges likely to arise thereof (e.g., STOA, 2016).…”

Section: Introductionmentioning

confidence: 99%

Emerging synergies between Internet of Things and social technologies

Mendhurwar

Mishra

2018

Journal of Global Information Technology Management

View full text Add to dashboard Cite

This essay discusses the phenomena of amalgamation of two prominent technologies: Internet of Things (IoT) and Social technologies. IoT devices are primarily used for connectivity between physical objects while Social technologies are responsible for collaboration and social interaction. The domain of Social Internet of Things (SIoTs) points toward social interactions of IoT devices. This phenomenon will further enhance the collaboration capabilities of IoTs to deliver huge amounts of human-computer interactions with very limited interventions from humans. Thus, high degrees of human-computer interfaces can be created among physical objects by enabling them with human-like capabilities and social interactions. In this context, we discuss relevant research developments, contextually analyze the drivers and challenges of SIoTs, and describe some interesting business use cases along with suitable recommendations going forward.

show abstract

Cybermatics: Cyber–physical–social–thinking hyperspace based science and technology

Cited by 131 publications

References 65 publications

Integrating Interactive Clothing and Cyber-Physical Systems: A Humanistic Design Perspective

Integrating Interactive Clothing and Cyber-Physical Systems: A Humanistic Design Perspective

Collaborative prognostics in Social Asset Networks

Emerging synergies between Internet of Things and social technologies

Contact Info

Product

Resources

About