The extreme growth of data-intensive, latency-sensitive and mission-critical applications has led to the convergence between Generative Artificial Intelligence, edge computing and Internet of Things (IoT), and in doing so, redefining the design and applications of intelligent systems. At the network edge, vast amounts of data are generated, and traditional cloud centered artificial intelligence architectures are increasingly faced with the obstacles related to latency, bandwidth, energy consumption, privacy and reliability. As a result, such limitations have spurred a paradigm change in favour of edge intelligence, in which data processing, learning and generative inference is done close to the location where data is generated. This book provides a holistic and systematic coverage of Generative AI-enable edge computing for intelligent IoT systems with a significant focus on reliability, sustainability and real time decision making. It questions data, resource, and decentralised data/codes that enable data generative models to be deployed within resource-constrained edge environments.