Hui Liu - Smart Device Recognition: Ubiquitous Electric Internet of Things

Jointly published with Science Press

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The development of modern society poses new and high challenges to the regulation capability, intelligence, and digitization of the electric grid. Building the Ubiquitous Electric Internet of Things (UEIOT) is an effective way to solve technical problems of the electric grid and break through the bottleneck. It makes the electric users, grid companies, electric generation companies, suppliers, and their equipment all connected. Then, the shared data is generated for service users, electric grids, electric generation, suppliers, government, and society. It creates greater opportunities for the development of more market players.

Due to the rapid development of the UEIOT, the non-intrusive device recognition methods which obtain various device information by analyzing indoor level gathered signal have become the focus in the electric energy saving. Besides, smart device identification is the core of the technology and equipment. Using data science to realize non-intrusive smart device identification is of great significance for energy conservation and the development of mechanical and electrical control technology. It is significant to build the application framework of various data identification technologies in non-intrusive device recognition.

The book introduces a series of state-of-the-art device identification methods, which can provide ideas for doctoral students and researchers and encourage further research. In the book, various methods of intelligent device identification are introduced in detail, including machine learning, deep learning, intelligent clustering, optimization model, integrated learning, single-label and multi-label identification models, etc. Besides, a large number of experimental simulations are carried out. In addition, the book also illustrates some traditional device recognition solutions in Chap. for comparison, which are based on physical methods or template matching method. Not limited to the application in the field of energy conservation, the book also analyzes the potential application of intelligent device identification in mechanical and electrical system optimizations, environmental pollution detection, and so on. In general, the book provides an important reference for the development of data science and technology in non-intrusive device recognition and would promote the application of intelligent device identification methods in industry.

The studies in the book are supported by National Natural Science Foundation of China, National Key R&D Program of China, the Innovation Drive of Central South University of China. The publication of the book is funded by the graduate textbook project of Central South University of China. In the process of writing the book, Rui Yang, Chengqing Yu, Shuqin Dong, Chao Chen, Jiakang Wang, Zijie Cao, Yucheng Yin, Zeyu Liu, and other team members have done a lot of experimental verification and other work; the authors would like to express heartfelt appreciations.