This unique text/reference provides a broad overview of both the technical challenges in sensor network development, and the real-world applications of distributed sensing.

Important aspects of distributed computing in large-scale networked sensor systems are analyzed in the context of human behavior understanding, including such topics as systems design tools and techniques, in-network signals, and information processing. Additionally, the book examines a varied range of application scenarios, covering surveillance, indexing and retrieval, patient care, industrial safety, social and ambient intelligence, and sports analysis.

Topics and features: contains valuable contributions from an international selection of leading experts in the field; presents a high-level introduction to the aims and motivations underpinning distributed sensing; describes decision-making algorithms in the presence of complex sensor networks; provides a detailed analysis of the design, implementation, and development of a distributed network of homogeneous or heterogeneous sensors; reviews the application of distributed sensing to human behavior understanding and autonomous intelligent vehicles; includes a helpful glossary and a list of acronyms.

This authoritative collection offers practical insights of great benefit to graduate students, researchers, and practitioners from such diverse communities as computer vision, networked embedded sensing, and artificial intelligence.