Smart Device Recognition
Autor Hui Liu, Chengming Yu, Haiping Wuen Limba Engleză Hardback – 13 dec 2020
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Specificații
ISBN-13: 9789813349247
ISBN-10: 9813349247
Pagini: 312
Ilustrații: XV, 294 p. 168 illus., 107 illus. in color.
Dimensiuni: 160 x 241 x 23 mm
Greutate: 0.58 kg
Ediția:1st ed. 2021
Editura: Springer
Locul publicării:Singapore, Singapore
ISBN-10: 9813349247
Pagini: 312
Ilustrații: XV, 294 p. 168 illus., 107 illus. in color.
Dimensiuni: 160 x 241 x 23 mm
Greutate: 0.58 kg
Ediția:1st ed. 2021
Editura: Springer
Locul publicării:Singapore, Singapore
Cuprins
Introduction.- Smart non-intrusive device recognition based on physical methods.- Smart non-intrusive device recognition based on intelligent single-label classification methods.-Smart non-intrusive device recognition based on intelligent multi-label classification methods
Notă biografică
Hui Liu is Professor of Artificial Intelligence and Smart Cities, Central South University, China; Vice Dean, Faculty of Traffic and Transportation Engineering, Central South University, China. He has double Ph.D. degrees from China and Germany (Ph.D. in Traffic & Transportation Engineering from Central South University of China in 2011/Ph.D. in Automation Engineering from Rostock University of Germany in 2013). He obtained his habilitation degree (professorship degree) on Automation Engineering from University of Rostock, Germany, in 2016. He had been employed as the BMBF Junior Group Leader of Ministry of Education & Research of Germany at CELISCA (Center for Life Science Automation), University of Rostock, Germany, since 01/2015 until 12/2016. He authorized 40 China invention patents in the field of data science, air quality monitoring and time series modeling, as the first inventor. He won many reputable research awards, including the second prize for Natural Science Research by Ministry of Education of China in 2017, the first prize for National Scientific and Technological Progress Award of China in 2018, the first prize for Scientific and Technology Award of China Railway Society in 2018, etc. He also received Elsevier Applied Energy Most Highly Cited Research Paper Award (20 papers globally selected in 2015), national outstanding doctoral thesis nomination awards of China, Hunan outstanding doctoral thesis of China, Baosteel Education Award, Mao Yisheng Railway Award and other personal honours.
Ms. Fang Cheng is now pursuing Ph.D. at Central South University, Changsha, China. Her research interests include machine learning for predictive health management.
Yanfei Li is Associate Professor, Shennong Chair Professor, College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha, China. Prof. Li published 2 monographs, 45 SCI/EI papers, including 27 JCR Q1 journal papers, 2 ESI 1% highly-cited papers, and authorized 10 China national invention patents as the first inventor as well. She leaded several important research projects, including China National Key Research and Development Project, Human Natural Science Foundation Project. She won the second prize of the Natural Science Award of Ministry of Education in 2017, the first prize of the Hunan New Energy Science and Technology Progress Award in 2020, the Logistics Technology Innovation Award of China Federation of Logistics and Purchasing in 2021 and the Transportation and Logistics Innovation Award of China Highway and Transportation Society in 2020.
Textul de pe ultima copertă
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.
Caracteristici
Provides a detailed introduction to and analysis of various advanced technologies for smart device recognition Evaluates state-of-the-art smart device recognition technologies on the basis of experimental cases Presents the potential applications of smart device recognition technologies in industry