Learning Techniques for the Internet of Things

Dr. Praveen Kumar Donta (Senior Member IEEE & Professional Member ACM), currently working as Postdoctoral researcher at Distributed Systems Group, TU Wien (Vienna University of Technology), Vienna, Austria. He is received his PhD. from Indian Institute of Technology (Indian School of Mines), Dhanbad in the field of Machine learning-based algorithms for wireless sensor networks in the year of 2021. From July 2019 to Jan 2020, he is a visiting Ph.D. fellow at Mobile \& Cloud Lab, Institute of Computer Science, University of Tartu, Estonia, under the Dora plus grant provided by the Archimedes Foundation, Estonia. He received his Master in Technology and Bachelor in Technology from the Department of Computer Science and Engineering at JNTUA, Ananthapur, with Distinction in 2014 and 2012. Currently, he is a Technical Editor and Guest Editor for Computer Communications, Elsevier, Editorial Board member for International Journal of Digital Transformation, Inderscience, Transactions on Emerging Telecommunications Technologies (ETT), Wiley. HE also serving as Early Career Editorial Board in Measurement and Measurement: Sensors, Elsevier journals. He served as IEEE Computer Society Young Professional Representative for Kolkata section. His current research includes Learning-driven Distributed Computing Continuum Systems, Edge Intelligence, and Causal Inference for Edge.Dr. Abhishek Hazra currently works as an assistant professor in the Department of Computer Science and Engineering, Indian Institute of Information Technology Sri City, Chittoor, Andhra Pradesh, India. He was a Post-doctoral Research Fellow at the Communications \& Networks Lab, Department of Electrical and Computer Engineering, National University of Singapore. He has completed his PhD at the Indian Institute of Technology (Indian School of Mines) Dhanbad, India. He received his M.Tech in Computer Science and Engineering from the National Institutes of Technology Manipur, India,and his B.Tech  from the National Institutes of Technology Agartala, India. He currently serves as an Editor/Guest Editor for Physical Communication, Computer Communications, Contemporary Mathematics, IET Networks, SN Computer Science, Measurement: Sensors. He is also a conference general chair for IEEE PICom 2023. His research area of interest includes IoT, Fog/Edge Computing, Machine Learning, and Industry 5.0.Dr. Lauri Loven (IEEE Senior Member) D.Sc. (Tech), is a senior member of IEEE and the coordinator of the Distributed Intelligence strategic research area in the 6G Flagship research program, at the Center for Ubiquitous Computing (UBICOMP), University of Oulu, in Finland. He received his D.Sc. at the university of Oulu in 2021, was with the Distributed Systems Group, TU Wien in 2022, and visited the Integrated Systems Laboratory at the ETH Zürich in 2023. His current research concentrates on edge intelligence, and on the orchestration of resourcesas well as distributed learning and decision-making in the computing continuum. He has co-authored 2 patents and ca. 50 research articles.

• Chapter. 1. Edge Computing for IoT.- Chapter. 2. Federated Learning Systems: Mathematical modelling and Internet of Things.- Chapter. 3. Federated Learning for Internet of Things.- Chapter. 4. Machine Learning Techniques for Industrial Internet of Things.- Chapter. 5. Exploring IoT Communication Technologies and Data-Driven Solutions.- Chapter. 6. Towards Large-Scale IoT Deployments in Smart Cities: Requirements and Challenges.- Chapter. 7. Digital Twin and IoT for Smart City Monitoring.- Chapter. 8. Multiobjective and Constrained Reinforcement Learning for IoT.- Chapter. 9. Intelligence Inference on IoT Devices.- Chapter. 10. Applications of Deep Learning models in diverse streams of IoT.- Chapter. 11. Quantum Key Distribution in Internet of Things.- Chapter. 12. Quantum Internet of Things for Smart Healthcare.- Chapter. 13. Enhancing Security in Intelligent Transport Systems: A Blockchain-Based Approach for IoT Data Management.- Index.