Sinopsis
In recent years, mobile technology and the internet of objects have been used in mobile networks to meet new technical demands. Emerging needs have centered on data storage, computation, and low latency management in potentially smart cities, transport, smart grids, and a wide number of sustainable environments. Federated learning's contributions include an effective framework to improve network security in heterogeneous industrial internet of things (IIoT) environments. Demystifying Federated Learning for Blockchain and Industrial Internet of Things rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. It provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication. Covering topics such as smart agriculture, object identification, and educational big data, this premier reference source is an essential resource for computer scientists, programmers, government officials, business leaders and managers, students and faculty of higher education, researchers, and academicians.
Acerca de los autores
Sandeep Kautish is working as Professor & Dean-Academics with LBEF Campus, Kathmandu Nepal running in academic collaboration with Asia Pacific University of Technology & Innovation Malaysia. He is an academician by choice and backed with 17+ Years of work experience in academics including over 06 years in academic administration in various institutions of India and abroad. He has meritorious academic records throughout his academic career. He earned his bachelors, masters and doctorate degree in Computer Science on Intelligent Systems in Social Networks. He holds PG Diploma in Management also. His areas of research interest are Business Analytics, Machine Learning, Data Mining, and Information Systems. He has 40+ publications in his account and his research works has been published in reputed journals with high impact factor and SCI/SCIE/Scopus/WoS indexing. His research papers can be found at Computer Standards & Interfaces (SCI, Elsevier), Journal of Ambient Intelligence and Humanized Computing (SCIE, Springer). Also, he has authored/edited more than 07 books with reputed publishers i.e. Springer, Elsevier, Scrivener Wiley, De Gruyter, and IGI Global. He has been invited as Keynote Speaker at VIT Vellore (QS ranking with 801-1000) in 2019 for an International Virtual Conference. He filed one patent in the field of Solar Energy equipment using Artificial Intelligence in 2019. He is an editorial member/reviewer of various reputed SCI/SCIE journals i.e. Computer Communications (Elsevier), ACM Transactions on Internet Technology, Cluster Computing (Springer), Neural Computing and Applications (Springer), Journal of Intelligent Manufacturing (Springer), Multimedia Tools & Applications (Springer), Computational Intelligence (Wiley), Australasian Journal of Information Systems (AJIS, International Journal of Decision Support System Technology (IGI Global USA), International Journal of Image Mining (Inderscience). He has supervised one PhD in Computer Science as a co-supervisor at Bharathiar University Coimbatore. Presently two doctoral scholars are pursuing their PhD under his supervision in different application areas of Machine Learning. He is a recognized academician as Session Chair/PhD thesis examiner at various international universities of reputes i.e. University of Kufa, University of Babylon, Polytechnic University of the Philippines (PUP), University of Madras, Anna University Chennai, Savitribai Phule Pune University, M.S. University, Tirunelveli, and various other Technical Universities. (Google Scholar - www.sandeepkautish.com.)
Gaurav Dhiman is an Assistant Professor within the Department of Computer Science, Government Bikram College of Commerce, Patiala. The editor’s current research interests include bio-inspired and evolutionary-based metaheuristic techniques for solving single-, multi-, and many-objective large-scale complex problems.
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