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 helps build the technical understanding for the reader.

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 avenues. He is a member of the ACM, IEEE, and actively involved with various working groups and committees of IEEE and ACM related to smart grid, energy informatics and smart cities.

Neeraj Kumar:

Prof. Neeraj Kumar (SMIEEE) (2019, 2020 highly-cited researcher from WoS) is working as a Full Professor in the Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology (Deemed to be University), Patiala (Pb.), India. He is also adjunct professor at Asia University, Taiwan, King Abdul Aziz University, Jeddah, Saudi Arabia. He has published more than 400 technical research papers (DBLP: https://dblp.org/pers/hd/k/Kumar_0001:Neeraj) in top-cited journals and conferences which are cited more than 14802 times from well-known researchers across the globe with current h-index of 65 (Google scholar: https://scholar.google.com/citations?hl=en&user=gL9gR-4AAAAJ). He is highly cited researcher in 2019, 2020 in the list released by Web of Science (WoS). He has guided many research scholars leading to Ph.D. and M.E./M.Tech. His research is supported by funding from various competitive agencies across the globe. His broad research areas are Green computing and Network management, IoT, Big Data Analytics, Deep learning and cyber-security. He has also edited/authored 10 books with International/National Publishers like IET, Springer, Elsevier, CRC. Security and Privacy of Electronic Healthcare Records: Concepts, paradigms and solutions (ISBN-13: 978-1-78561-898-7), Machine Learning for cognitive IoT, CRC Press, Blockchain, Big Data and Machine learning, CRC Press, Blockchain Technologies across industrial vertical, Elsevier, Multimedia Big Data Computing for IoT Applications: Concepts, Paradigms and Solutions (ISBN: 978-981-13-8759-3), Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019) (ISBN 978-981-15-3369-3). Probabilistic Data Structures for Blockchain based IoT Applications, CRC Press. One of the edited text-book entitled, "Multimedia Big Data Computing for IoT Applications: Concepts, Paradigms, and Solutions" published in Springer in 2019 is having 3.5 million downloads till 06 June 2020. It attracts attention of the researchers across the globe. (https://www.springer.com/in/book/9789811387586).

He is serving as editors of ACM Computing Survey, IEEE Transactions on Sustainable Computing, IEEE Systems Journal, IEEE Network Magazine, IEEE Communication Magazine, Elsevier Journal of Networks and Computer Applications, Elsevier Computer Communication, Wiley International Journal of Communication Systems. Also, he has organized various special issues of journals of repute from IEEE, Elsevier, Springer. He has been a workshop chair at IEEE Globecom 2018, IEEE Infocom 2020 (https://infocom2020.ieee-infocom.org/workshop-blockchain-secure-software-defined-networking-smart-communities) and IEEE ICC 2020 (https://icc2020.ieee-icc.org/workshop/ws-06-secsdn-secure-and-dependable-software-defined-networking-sustainable-smart) and track chair of Security and privacy of IEEE MSN 2020 (https://conference.cs.cityu.edu.hk/msn2020/cf-wkpaper.php). He is also TPC Chair and member for various International conferences such as IEEE MASS 2020, IEEE MSN2020. He has won the best papers award from IEEE Systems Journal and IEEE ICC 2018, Kansas-city in 2018. He won the best researcher award from parent organization every year from last eight consecutive years.

Gagangeet Singh Aujla:

Dr. Gagangeet Singh Aujla is an Assistant Professor of Computer Science at Durham University. Before this, he worked as a post-doctoral research associate at Newcastle University, a research associate at Thapar University (India), a visiting researcher at University of Klagenfurt (Austria) and on various academic positions for more than a decade. He received his PhD degree from the Thapar University (India), Master and Bachelor degrees from the Punjab Technical University (India). For his contributions to the area of scalable and sustainable computing, he was awarded the 2018 IEEE TCSC Outstanding PhD Dissertation Award of Excellence. The main theme of his research is energy-efficient, reconfigurable, resilient and intelligent surfaces (smart city, smart grid, IoT-Edge-Cloud systems, healthcare systems, transportation systems). To develop himself as a researcher, he worked on various research projects awarded by EPSRC, the Department of Science and Technology (India), and Austrian Federal Ministry of Education, Science and Research. This facilitated his collaboration with international researchers from the UK, US, Canada, Australia, China, Austria, Brazil, and India. Together, the group published several research papers in the fields of software-defined networking, energy-efficient cloud data centres, edge-cloud computing, blockchain, particularly focusing on the creation of reconfigurable, resilient and intelligent surfaces. He led his team organizing workshops (SecSDN and BlockSecSDN) in conjunction with different IEEE Communication Society conferences like IEEE Infocom, IEEE Globecom, IEEE ICC, and many more. Contributing to the research community, he is serving as Associate Editor for Ad-hoc Networks and Topic Editor for Sensors, a Guest Editor for IEEE Transaction on Industrial Informatics, IEEE Network, Neural Computing and Applications (Springer), Computer Communications (Elsevier), and Transactions on Emerging Telecommunications (Wiley).

1. Smart City: The Verticals of Energy Demand and Challenges. 2. Conventional Power Grid to Smart Grid. 3. Smart Grids: An Integrated Perspective. 4. Internet of Energy: Solution for Smart Cities. 5. IoE Applications for Smart Cities. 6. IoE Design Principles and Architecture. 7. Machine Learning Models for Smart Cities. 8. Machine Learning Models in Smart Cities - Data-Driven Perspective.9. Case Study - 1: Machine Learning Techniques for Monitoring of PV Panel. 10. Case Study - 2: Intelligent Control System for Smart Environment. 11. Pathway and Future of the IoE in Smart Cities.