A Framework for Fusion of Symbiotic Human Sensor and Physical Sensor Data

Past experiences tell us that a disaster warning and response system can improve its surveillance coverage of the threatened area and situation awareness by supplementing in-situ and remote sensor data with human sensor data captured and sent by people in the area. This paper is concerned with fusion and processing methods with which the system can make use of human sensor data and physical sensor data synergistically to speed up the decision process and improve the quality of its decision. We formulate the problem in a statistical detection and estimation framework. Within this framework, value fusion and decision fusion of human sensor data and physical sensor data can be treated in a coherent way.