A Framework for Fusion of Human Sensor and Physical Sensor Data

• Published in: IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2014-09, Vol.44 (9), p.1248-1261
• Main Authors: Pei-Hsuan Tsai, Ying-Jun Lin, Yi-Zong Ou, Chu, Edward T-H, Liu, Jane W. S.
• Format: Article
• Language: English
• Subjects: Alarm systems; Applied sciences; Cameras; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Crowdsourcing; Cybernetics; Data mining; Decision theory. Utility theory; Decisions; Disasters; Emergency warning programs; Estimation; Exact sciences and technology; Human; multiple sensor fusion; Operational research and scientific management; Operational research. Management science; Sensors; Software; statistical detection and estimation; Support systems; Surveillance; Temperature measurement
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2014.2309090

Many disaster warning and response systems can improve their surveillance coverage of the threatened area by supplementing in situ and remote physical sensor data with crowdsourced human sensor data captured and sent by people in the area. This paper presents fusion methods which enable a crowdsourcing enhanced system to use human sensor data and physical sensor data synergistically to improve its sensor coverage and the quality of its decisions. The methods are built on results of classical statistical detection and estimation theory and use value fusion and decision fusion of human sensor data and physical sensor data in a coherent way. They are the building blocks of a central fusion unit in a crowdsourcing support system for disaster surveillance and early warning applications.