Studies in Computational Intelligence

Amodu, Oluwatosin Ahmed; Mahmood, Raja Azlina Raja; Althumali, Huda; Bukar, Umar Ali; Abdullah, Nor Fadzilah; Jarray, Chedia

This book offers a structured exploration of how Markov Decision Processes (MDPs) and Deep Reinforcement Learning (DRL) can be used to model and optimize UAV-assisted Internet of Things (IoT) networks, with a focus on minimizing the Age of Information (AoI) during data collection. Adopting a tutorial-style approach, it bridges theoretical models and practical algorithms for real-time decision-making in tasks like UAV trajectory planning, sensor transmission scheduling, and energy-efficient data gathering. Applications span precision agriculture, environmental monitoring, smart cities, and emergency response, showcasing the adaptability of DRL in UAV-based IoT systems. Designed as a foundational reference, it is ideal for researchers and engineers aiming to deepen their understanding of adaptive UAV planning across diverse IoT applications.  

Details

Published by: Springer

Publication Date: 2025-10-08

Format: Hardcover

ISBN-13: 9783031970108

DOI: 10.1007/978-3-031-97011-5

Dimensions: 235cm x155cm

Pages: 142