The Convergence of AI, IoT, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications
Will be published approx. on 1. September 2026
Book
Hardback
248 pages
978-1-83724-243-6 (ISBN)
Description
AI and data-driven methods, particularly machine and deep learning models, have revolutionized image processing tasks such as object detection and segmentation, as well as inverse sensing tasks such as atmospheric condition monitoring. These models enable highly accurate predictions from large, labelled datasets. However, one of the key challenges with current AI systems is their opacity. While they deliver precise results, they often fail to provide clear insights into the underlying mechanisms driving these predictions. The lack of interpretability, especially in the context of sensing data, complicates the understanding of how internal features are represented and utilized. This issue is particularly pronounced in smart environment applications, where artificial intelligence techniques are increasingly employed, yet their internal workings remain largely opaque.
In this edited book, the contributors explore the potential of machine intelligence, deep learning and sensing technologies, with a focus on their integration and applications. They present new methods, cutting-edge technologies and practical solutions to real-world challenges. The goal is to help readers better grasp the concepts necessary for designing and deploying the next generation of smarter and more sustainable systems and environments.
The Convergence of AI, IoT, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications is a useful reference for researchers, engineers and scientists in academia and industry, as well as advanced students in the fields of data science and security, AI and networking, communication engineering, smart sensing, remote sensing and automation. It will also be of interest to system designers and developers of AI and sensing technologies for smart environment applications.
In this edited book, the contributors explore the potential of machine intelligence, deep learning and sensing technologies, with a focus on their integration and applications. They present new methods, cutting-edge technologies and practical solutions to real-world challenges. The goal is to help readers better grasp the concepts necessary for designing and deploying the next generation of smarter and more sustainable systems and environments.
The Convergence of AI, IoT, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications is a useful reference for researchers, engineers and scientists in academia and industry, as well as advanced students in the fields of data science and security, AI and networking, communication engineering, smart sensing, remote sensing and automation. It will also be of interest to system designers and developers of AI and sensing technologies for smart environment applications.
More details
Series
Language
English
Place of publication
Stevenage
United Kingdom
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-83724-243-6 (9781837242436)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Chaker Abdelaziz Kerrache is a full professor in the Department of Computer Science at the University of Amar Telidji Laghouat, Algeria. His research areas cover the fields of security, trust and risk management, secure multi-hop wireless communications, unmanned aerial vehicles (UAVs), named data networking (NDN), and the mobile internet. He is an associate editor of Computer Communications, and Frontiers in Space Technologies, and a TPC member for several international conferences including Infocom, Globecom, ICC, and CCNC.
Mohamed Lahby is an associate professor and Director of the Laboratory of Applied Mathematics and Computer Sciences at the Ecole Normale Superieure (ENS), Hassan II University of Casablanca, Morocco. His research interests include wireless communication and network, mobility management, QoS/QoE, Internet of things, smart cities, optimization, machine learning and generative AI. He has published 60+ papers and edited 10+ books. He is a senior member of IEEE.
Al-Sakib Khan Pathan is a professor in the CSE Department at the United International University (UIU), Bangladesh. His research focuses on computer networks and security, wireless network routing, e-services technologies, Internet and web applications and multidisciplinary issues. He serves as a chair and board member for international IEEE and ACM conferences, He is editor-in-chief of the International Journal of Computers and Applications and the Journal of Cyber Security Technology. He is a senior member of the IEEE.
Yassine Maleh is an associate professor of cybersecurity and IT governance at Sultan Moulay Slimane University, Morocco. He is the founding chair of the IEEE Consultant Network Morocco and founding president of the African Research Center of Information Technology & Cybersecurity. He is a former CISO at the National Port Agency. He has published 200+ papers in international journals and at conferences and workshops), edited 40 books, and authored 5 books.
Mohamed Lahby is an associate professor and Director of the Laboratory of Applied Mathematics and Computer Sciences at the Ecole Normale Superieure (ENS), Hassan II University of Casablanca, Morocco. His research interests include wireless communication and network, mobility management, QoS/QoE, Internet of things, smart cities, optimization, machine learning and generative AI. He has published 60+ papers and edited 10+ books. He is a senior member of IEEE.
Al-Sakib Khan Pathan is a professor in the CSE Department at the United International University (UIU), Bangladesh. His research focuses on computer networks and security, wireless network routing, e-services technologies, Internet and web applications and multidisciplinary issues. He serves as a chair and board member for international IEEE and ACM conferences, He is editor-in-chief of the International Journal of Computers and Applications and the Journal of Cyber Security Technology. He is a senior member of the IEEE.
Yassine Maleh is an associate professor of cybersecurity and IT governance at Sultan Moulay Slimane University, Morocco. He is the founding chair of the IEEE Consultant Network Morocco and founding president of the African Research Center of Information Technology & Cybersecurity. He is a former CISO at the National Port Agency. He has published 200+ papers in international journals and at conferences and workshops), edited 40 books, and authored 5 books.
Editor
Full ProfessorUniversity of Amar Telidji Laghouat, Department of Computer Science, Algeria
Associate Professor and DirectorEcole Normale Superieure (ENS), Hassan II University of Casablanca, Laboratory of Applied Mathematics and Computer Sciences, Morocco
ProfessorUnited International University (UIU), CSE Department, Bangladesh
Associate ProfessorSultan Moulay Slimane University, Morocco
Content
Introduction to the book
Chapter 1: Adversarial Machine Learning Attacks in IoT Networks
Chapter 2: Advanced Security Mechanisms for Heterogeneous Sensing Data in IoT Ecosystems
Chapter 3: AI-Enabled Sensing, Security, and Explainability for Smart Urban, Industrial, and Environmental Applications
Chapter 4: AI-Powered Environmental Risk Assessment Leveraging Multi Sensor Fusion
Chapter 5: Synthetic Data Strategies for Indoor Human Activity Recognition: Analytical Models and Sensor-Based Measurement Campaigns
Chapter 6: Intelligent Resource Allocation for 6G-Enabled IoT Sensing Networks in Smart Cities
Chapter 7: Trustworthy Resource Allocation in AI-Driven 6G Sensing Networks
Chapter 8: AI-Enabled WiFi and RFID Sensing for Smart Environments: Enhancing Trust, Privacy, and Spatial Resolution
Chapter 9: Adversarial Machine Learning Countermeasures in IoT Networks
Chapter 10: AI and Blockchain Applications in IoT Security Systems: Fundamentals, Challenges and Opportunities
Chapter 11: Conclusion
Chapter 1: Adversarial Machine Learning Attacks in IoT Networks
Chapter 2: Advanced Security Mechanisms for Heterogeneous Sensing Data in IoT Ecosystems
Chapter 3: AI-Enabled Sensing, Security, and Explainability for Smart Urban, Industrial, and Environmental Applications
Chapter 4: AI-Powered Environmental Risk Assessment Leveraging Multi Sensor Fusion
Chapter 5: Synthetic Data Strategies for Indoor Human Activity Recognition: Analytical Models and Sensor-Based Measurement Campaigns
Chapter 6: Intelligent Resource Allocation for 6G-Enabled IoT Sensing Networks in Smart Cities
Chapter 7: Trustworthy Resource Allocation in AI-Driven 6G Sensing Networks
Chapter 8: AI-Enabled WiFi and RFID Sensing for Smart Environments: Enhancing Trust, Privacy, and Spatial Resolution
Chapter 9: Adversarial Machine Learning Countermeasures in IoT Networks
Chapter 10: AI and Blockchain Applications in IoT Security Systems: Fundamentals, Challenges and Opportunities
Chapter 11: Conclusion