A Framework for Fusion of Human Sensor and Physical Sensor Data

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 crowdsourc...

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Bibliographic Details
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
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Summary: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.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2014.2309090