The 2021 International Conference on Smart Technologies and Systems for Internet of Things

This book contains papers presented at the 2021 International Conference on Smart Technologies and Systems for Internet of Things, held on November 2627, 2021, in Shanghai, China. It covers topics like distributed processing for sensor data in CPS networks, approximate reasoning and pattern recognition for CPS networks, distributed processing in mobile networking, data analytics for social media sensor data integration, data platforms for efficient integration with CPS networks, virtualized and cloud-oriented resources for data processing for CPS networks, machine learning algorithms for CPS networks, data security and privacy in CPS networks, sensor fusion algorithms, sensor signal processing, data acquisition and preprocessing technology, intelligent computing, data mining methods and algorithms, big data system solutions and tools platform, intelligent control and intelligent management, and operational situation awareness utilizing big data-driven intelligence. It caters to postgraduate students, researchers, and practitioners specializing and working in related areas.

Consists of papers presented at STS-IOT 2021 Highlights the recent advances made in the area IoT Serves as a reference resource for researchers and practitioners in academia and industry

Auteur
Dr. Ishfaq Ahmad is Professor of Computer Science and Engineering and Director of the Center for Advanced Computing Systems at the University of Texas at Arlington (UTA) *which he joined in 2002. He earned his Ph.D. in Computer Science and his M.S. in Computer Engineering from Syracuse University, New York, USA, in 1992 and 1987, respectively; and his B.S. in Electrical Engineering from the University of Engineering and Technology, Lahore, Pakistan, in 1985. His early education was from Central Model High School, and Government College, Lahore. Prior to joining UTA, he was Associate Professor in the Computer Science Department at the Hong Kong University of Science and Technology. He has authored 260-plus publications that include books, papers in peer-reviewed journals, and conference proceedings, related to software for supercomputing systems, parallel optimization algorithms, digital video compression and analysis, assistive technologies, and sustainable computing. Professor Ahmad has received numerous international research awards, including five best research paper awards at leading conferences and top-tier journals. Dr. Ahmad's research, with career-wide funding exceeding $13 million, is sponsored by government agencies and several companies. His research work, according to the Google Scholar, is widely cited with over 20,000 authors in computer science referencing his research papers. Also, according to Google Scholar, he is ranked among the world's best researchers in several research areas of computer science and engineering. Aside from being the founding editor-in-chief of the Journal, *Sustainable Computing: Informatics and Systems, he has served as an editor of six others journals, chaired over 20 conferences, and delivered more than 150 talks. A senior visiting scientist at the U.S. Air Force Research Laboratory *in Rome, New York, and a visiting lecturer at NASA's *Johnson Space Center, Houston, Texas, he also holds honorary professorships at several universities around the world. He is also the editor-in-chief of Springer's new Journal Discover Internet-of-Things, with an editorial board of researchers from around the world. He is honored as a distinguished life fellow, in The Institute of Doctors, Engineers, & Scientists (IDES) of India. Dr. Ahmad is also a fellow of the IEEE, the largest professional organization in the world-the fellow grade is the highest of the IEEE and is conferred based on extraordinary achievements in electrical engineering and computer science.

Jun Ye received his B.S. degree in Applied Mathematics at Chongqing University; M.S. degree in Cryptography at Guilin University of Electronic Technology; Ph.D. in Xidian University. He is a high-level talent of Hainan Province, and he is working at School of Computer Science and Cyberspace Security of Hainan University. His current research interests include computer science and information security. He has authored or co-authored more than 20 high-level publications, and he is also a reviewer of many well-known journals. He is one of the high-level talents of Hainan Province and got the "First prize" of science and technology progress prize of Hainan Province in 2019.

Weidong Liu is an associate professor in College of Computer Science, Inner Mongolia University, China. He got the Ph.D. degree from the School of Computing Engineering and Science, Shanghai University, Shanghai. His current research interests include intelligent information processing, data mining, and machine learning. He has authored or co-authored more than 20 publications indexed by SCI and EI.

Contenu
Signal Processing of Ground Penetrating Radar Based on MED Technology.- Application Analysis of Information Security Technology in Credit Card System.- A Job Recommendation System Based on Student and Category Similarity Computation.- Correct Modeling of SH 50ETF Option Implied Volatility Based on Neural Network.- International Trade Strategy of SMEs Based on Blockchain Technology.- Information Collection Analysis and Processing of Digital Substation Based on Artificial Intelligence.- Computer Network Monitoring and Analysis Method Based on Petri Net.- Fuzzy Control Method Based on Dynamic Self-Optimization.- Application of Data Encryption Technology in Computer Software Testing.- New Rural Intelligent Pension Model Based on Big Data Technology.- Application of Dual-Loop Control Algorithm Simulation Technology in Power Regulation of New Energy Grid.- Mine Safety Monitoring and Early Warning System Based on 5G Network Technology.- The Influence of Fintech on the Performance of Commercial Bank Based on Big Data Analysis.- Research and Design of Soft Switch Technology in New Energy Vehicle Wireless Charging System.- High Dimensional Data Visualization Analysis Based on Unsupervised Laplacian Score. <p