Smart Device Recognition (eBook)

Ubiquitous Electric Internet of Things
Artikelnummer: 978-981-3349-25-4
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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The book is the first international reference on the field of smart device recognition and Ubiquitous Electric Internet of Things (UEIOT). It presents a range of state-of-the-art key methods and applications for smart device recognition. In future smart environments, obtaining energy consumption information for identifying every device is an effective approach to guarantee the energy efficiency of smart industrial systems. Such as, the Ubiquitous Electric Internet of Things (UEIOT) technology represents one of the most effective measures for electricity and energy management and has attracted considerable attention from scientists and engineers around the world. The realization of smart device recognition in the UEIOT framework has become the core and basis of UEIOT's success. The device smart recognition can help governments and managers to distribute energy and power better, and help device manufacturers to improve their products regarding smart energy conservation. Accordingly, in the future smart industry, implementing smart device recognition is desired and very important. In the book, several methods, strategies, and experiments for achieving smart device recognition are presented in details. As the first monograph in the field of smart device recognition, the book can provide beneficial reference for students, engineers, scientists, and managers in the fields of power, energy, electromechanical devices, smart cities, artificial intelligence, etc.

 


The book is the first international reference on the field of smart device recognition and Ubiquitous Electric Internet of Things (UEIOT). It presents a range of state-of-the-art key methods and applications for smart device recognition. In future smart environments, obtaining energy consumption information for identifying every device is an effective approach to guarantee the energy efficiency of smart industrial systems. Such as, the Ubiquitous Electric Internet of Things (UEIOT) technology represents one of the most effective measures for electricity and energy management and has attracted considerable attention from scientists and engineers around the world. The realization of smart device recognition in the UEIOT framework has become the core and basis of UEIOT's success. The device smart recognition can help governments and managers to distribute energy and power better, and help device manufacturers to improve their products regarding smart energy conservation. Accordingly, in the future smart industry, implementing smart device recognition is desired and very important. In the book, several methods, strategies, and experiments for achieving smart device recognition are presented in details. As the first monograph in the field of smart device recognition, the book can provide beneficial reference for students, engineers, scientists, and managers in the fields of power, energy, electromechanical devices, smart cities, artificial intelligence, etc.

 


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VerlagSpringer Nature Singapore
EinbandPDF
Erscheinungsjahr2020
Seitenangabe294 S.
AusgabekennzeichenEnglisch
AbbildungenXV, 294 p. 168 illus., 107 illus. in color.
Masse14'903 KB
PlattformPDF
ReiheEngineering; Engineering
AutorLiu, Hui / Yu, Chengming / Wu, Haiping

Alle Bände der Reihe "Engineering; Engineering (R0)"

Über den Autor Hui Liu

Dr. Hui Liu is a Full Professor in the field of Artificial Intelligence, Smart Cities and Smart Energy at Central South University (CSU), China. Prof. Liu is the director of Institute of Artificial Intelligence and Robotics at CSU. He received double Ph.D degrees from Central South University (China) in 2011 and University of Rostock (Germany) in 2013, respectively. He received habilitation degree from University of Rostock in 2016. He was appointed as the BMBF junior group leader by the Ministry of Education and Research of Germany at University of Rostock since January, 2015 until December 2016. Dr. Yanfei Li is an Associate Professor in the field of Artificial Intelligence, Smart Agriculture and Smart Energy at Hunan Agricultural University (HAU), China. Prof. Li is the director of Institute of Artificial Intelligence at HAU. She received Ph.D degree from University of Rostock (Germany) in 2014 then worked as a postdoctoral fellow at University of Rostock in 2015. Dr. Zhu Duan is an assistant researcher in the field of Data Science at Central South University. Dr. Duan focuses on the research of time series prediction. He was selected as the Postdoctoral Fellowship Program of CPSF and Xiaohe Science and Technology Talent of Hunan Province in China.

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