Explainable IoT Applications: A Demystification

Explainable IoT Application: A Demystification is an in-depth guide that examines the intersection of the Internet of Things (IoT) with AI and Machine Learning, focusing on the crucial need for transparency and interpretability in IoT systems. As IoT devices become more integrated into daily life, from smart homes to industrial automation, it is increasingly important to understand and trust the decisions they make. The book starts by covering the basics of IoT, highlighting its importance in modern technology and its wide-ranging applications in fields such as healthcare, transportation, and smart cities. It then delves into the concept of explainability, stressing the need to prevent IoT systems from being perceived as opaque, black-box operations. The authors explore various techniques and methods for achieving explainability, including rule-based systems and machine learning models, while also addressing the challenge of balancing explainability with performance. Through practical examples, the book shows how explainability can be successfully implemented in IoT applications, such as in smart healthcare systems.

Furthermore, the book addresses the significant challenges of securing IoT systems in an increasingly connected world. It examines the unique vulnerabilities that come with the widespread use of IoT devices, such as data breaches, cyberattacks, and privacy issues, and discusses the complexities of managing these risks. The authors emphasize the importance of implementing security strategies that strike a balance between fostering innovations and protecting user data. The book concludes with a comprehensive exploration of the challenges and opportunities in making IoT systems more transparent and interpretable, offering valuable insights for researchers, developers, and decision-makers aiming to create IoT applications that are both trustworthy and understandable.

Provides a comprehensive and accessible guide to the complex intersection of IoT and explainable AI Bridges the gap between the complexity of IoT systems and the accessibility of knowledge Presents an insightful exploration, real-world case studies, and expert perspectives

Auteur

Dr. Sachi Nandan Mohanty was recognized as Top 2% World Scientists Ranking by Stanford University and Elsevier for years 2022, and 2023. He received his PostDoc from Indian Institute of Technology Kanpur, India in the year 2019 and Ph.D. from Indian Institute of Technology Kharagpur, India in the year 2015, with MHRD scholarship from Govt of India. He has authored/edited Forty two books, published by IEEE-Wiley, Springer, Wiley, CRC Press, NOVA and DeGruyter. His research areas include Data mining, Big Data Analysis, Cognitive Science, Fuzzy Decision Making, Brain-Computer Interface, Cognition, and Computational Intelligence. Prof. S N Mohanty has received four Best Paper Awards during his Ph.D. from International Conference at Benjing, China, and the other at International Conference on Soft Computing Applications organized by IIT Rookee in the year 2013. He has awarded Best thesis award first prize by Computer Society of India in the year 2015. He has guided 9 PhD Scholar, twenty three Post graduate student. He has published 241 International Journals of International repute. He has received 4th time International Travel support from Government of India Department of Science and Technology, SERB Funding for International travel for presenting research paper and Keynote specker. He has awarded by many awards and fellowships during his career and to name a few are and has been elected as FELLOW of Institute of Engineers, IETE, Ambassador European Alliance Innovation (EAI), and Senior member of IEEE Computer Society Hyderabad chapter. He has been awarded by many awards and fellowship during his career and to name a few are Prof. Ganesh Mishra Memorial Award on 61st Annual Technical Session & 19th Prof. Bhubaneswar Behera Lecturer on 23-24th June 2020 from The Institution of Engineers (India) Odisha State Center, Bhubaneswar. He is a member of professional bodies like IETE, CSI, IE, IEEE (Hyderabad section). He also the reviewer of Journal of Robotics and Autonomous Systems (Elsevier), Computational and Structural Biotechnology Journal (Elsevier), Artificial Intelligence Review (Springer), Spatial Information Research (Springer). He is leading as General chair of 2 international conferences such as ICISML, AIHC and editor in chief of international journal EAI Transaction on Intelligent System and Machine learning Application. Dr. Mohanty has gone for academic assignment to New York, Atlanta, Orlondo, Georgia, Paris, Slovakia, Singapore, Abu Dhabi, Saraja, Dubai, Malaysia, Istanbul, Viena, and Germany for delivering Key note talk and chair the sessions in International conferences with travel support from Department of Science & Technology, Government of India, New Delhi, India.

Dr. Suneeta Satpathy (Senior member, IEEE) is currently working as an Associate Professor, Center For AI & ML, SOA University, Bhubaneswar, Odisha. She has received her Ph.D. from Utkal University, Bhubaneswar, Odisha, in the year 2015, with Directorate of Forensic Sciences, MHA scholarship from Govt of India. Her research interests include Computer Forensics, Cyber Security, Data Fusion, Data Mining, Big Data analysis, and Decision Mining. She has edited books in association with Springer and Wiley and CRC AAP, NOVA Publications. In addition to research, she has guided many post-graduate and graduate students. She has published papers in many International Journals and conferences in repute. Her professional activities include roles as editorial board member and/or reviewer of Journal of Engineering Science, Advancement of Computer Technology and Applications, Robotics and Autonomous Systems (Elsevier), computational and Structural Biotechnology Journal (Elsevier), Journal of Big Data(Springer) as well as Inder Science Journals. She is an active member of CSI, ISTE, OITS, IE, Nikhil Bh

Contenu

Essential Uses of IoT and Machine Learning.- IoT Pro-Interventions: Transforming Industries and Enhancing Quality of Life.- A Comprehensive Review of Machine Learning Approaches in IoT and Cyber Security for Information Systems Analysis.- Application of Machine learning in the Internet of Things.- Empowering Industries with IoT and Machine Learning Innovations.- A Framework for Sustainable Smart Healthcare Systems in Smart Cities.- Cloud Computing Applications in Digital Health: Challenges related to Privacy and Safety.- An IoT-Based Blockchain-Enabled Secure Storage for Healthcare Systems.- Block-Chain Technology in Smart Telemedicine using IOT.- Securing the Future of IoT-Based Smart Healthcare: Challenges, Innovations, and Best Practice.- Smart City: Challenges & Opportunities Detection and Identification of Autonomous Vehicles Using Sensor Synthesis.- AN IOT BASED REAL TIME TRAFFIC MONITORING SYSTEM.- Internet of Things enabled Technological devices empowering expertise in improve Smart City operations.- Enhancing Smart City Retail: An Innovative IoT Driven Smart Billing-Enabled Shopping Cart.- Smart City: Challenges and Issues.- IoT based Real-Time Ecological Monitoring System Deploying an Arduino Board and Cloud Computing.- IoT Based Monitoring Of Waste Management And Air Pollutants.- IOT based smart dustbin design and implementation for monitoring under uncertain environments.- Smart garbage monitoring system using IOT for commercial purpose.- IoT Based Smart Home Systems.- A Survey on Various Secure Access Control and Authentication in a Block Chain -Enable Cloud IoT.- Uncovering the Truth: A Machine Learning Approach to Detect Fake Product Reviews and analyze Sentiment.- Real Time Fall Detection monitoring on elderly using IoT and Deep Learning.- CNN's augmented with IoT for Traffic Optimization and Signal Regulation.- CVLSTMLW-CNN:A IoT-Enabled Hybrid CNN mod…