This book uncovers and presents various real-life applications in the areas of transportation, smart cities, manufacturing, agriculture, disaster management, finance, health care and in other areas by using cutting-edge advanced Machine Learning (ML) techniques such as Deep Learning and Explainable AI (XAI) models using IoT sensor data. The book provides various examples of analyzing large amounts of data, detecting patterns, and making predictions in real-time applications and detailed case studies with practical solutions using various state-of-the-art machine learning and IoT sensor data and all these aspects will benefit the stakeholders. The book is useful for academics, researchers, upper-undergraduate, master and Ph.D. students, engineers and practitioners in sensor/IoT and AI/ML technologies, methods, applications, and related areas, and it also offers valuable insights by suggesting future research directions and providing recommendations within the fields of AI and IoT.

Highlights case studies and innovative applications that leverage sensing technologies within the realm of IoT Serves as a platform for researchers and practitioners to exchange knowledge in AI, ML, IoT, and sensing technologies Discusses the challenges and issues encountered in the real-time implementation of IoT and AI/ML technologies

Inhalt

Sensors ML and AI for Real World Applications.- Flying IoT Sensor Fusion Performance Analysis for UAV Applications in Indoor Spaces.- Machine Learning Empowered IoT Devices Analysis of Indoor and Outdoor Temperature and Health Risks.- Identification of IoT devices through Machine Learning and hardware fingerprints based on clock skew.