Internet of Energy for Smart Cities Machine Learning Models and Techniques
Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book:
- Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions.
- Points to the solutions provided by machine learning to optimize the grids within a smart city set-up.
- Discusses relevant IoE design principles and architecture.
- Helps to automate various services in smart cities for energy management.
- Includes case studies to show the effectiveness of the discussed schemes.
Anish Jindal:
Dr. Anish Jindal is working as a Lecturer (Assistant Professor) in the School of Computer Science and Electronic Engineering (CSEE), University of Essex since Mar 2020. Prior to this, he worked as a senior research associate at the School of Computing & Communications, Lancaster University, UK from Oct. 2018 to Mar. 2020. He completed his Ph.D., M.Engg. and B. Tech. degrees in computer science engineering in 2018, 2014, and 2012, respectively. He is the recipient of the Outstanding Ph.D. Dissertation Award, 2019 from the IEEE Technical Committee on Scalable Computing (TCSC) and conferred with the IEEE Communication Society's Outstanding Young Researcher Award for Europe, Middle East, and Africa (EMEA) Region, 2019. He has also been a visiting researcher to OFFIS - Institute for Information Technology, Germany in 2019. His research interests are in the areas of smart cities, data analytics, artificial intelligence, cyber-physical systems, wireless networks, and security. Some of his research findings are published in top-cited journals such as IEEE Transactions on Industrial Informatics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Vehicular Technology, IEEE Communication Magazine, IEEE Network, Future Generation Computer Systems, and Computer Networks. In addition to it, his research works have also been presented in various conferences of repute such as IEEE ICC, IEEE Globecom, IEEE WiMob, IEEE PES General Meeting, ACM MobiHoc, etc. He has served as General co-chair, TPC co-chair, TPC member, Publicity chair and Session chair of various reputed conferences and workshops including IEEE ICC, IEEE WoWMoM, IEEE INFOCOM and IEEE GLOBECOM. He is also the guest editor of various journals including Software: Practice and Experience (Wiley), Neural Computing & Applications (Springer), Computer Communications (Elsevier), and Computers (MDPI). He has also delivered many invited talks and lectures in various international av
Date de parution : 07-2021
15.6x23.4 cm
Thèmes d’Internet of Energy for Smart Cities :
Mots-clés :
Low Power Wide Area Network; Smart Grid; DC Microgrid; Data Management; Phasor Measurement Units; Machine Learning; Remote Telemetry Units; Power Grid; Distributed Energy Resources; Energy Efficiency; Smart Cities; Energy Demand; Fog Computing; EV; Energy System; TCP; Power Consumption; LTE; Smart Energy Systems; Energy Resources; IoT Device; IoT Application; Intelligent Electronic Devices; Ml Model; Smart Metering; Energy Storage System; Transactive Energy; SCADA System; IoT Sensor; Energy Sustainability