NSF-Funded Collaborative Research on Building an Intelligent, Uncertainty-Resilient Detection and Tracking Sensor Network


Detection, identification, and tracking of CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive) plumes can be accomplished by combining the modalities of sensor and cyber networks. The sensor network provides information about physical-space activities, e.g., locations and movements of the plume sources. The cyber network provides storage and computational resources to analyze and infer where the plume originated, the trajectory of its movement, and the prediction of its future movement. The challenges in realizing such a sensor cyber network include intelligent sensing (intelligent sensor selection and coverage) and the capability to deal with uncertainties (uncertainty in measurement as well as in modeling). This project proposes to leverage the convergence between the sensor and the cyber networks to achieve these goals. In particular, the plan is to carry out three synergistic research tasks: 1) network formation by sensor selection, placement, and coverage; 2) sensor tasking protocol with temporal/spatial uncertainty management; 3) protocols for reliable sensor-cyber communication supporting the above two tasks. The PIs will prototype the research results and integrate the prototypes for different components to build the sensor cyber network for plume detection, identification and tracking. They will also evaluate the sensor cyber network using various test scenarios in collaboration with Oak Ridge National Lab. If successful, the project will provide technology for building detection and tracking sensor networks that can give great protection to people and the environment against harmful plumes.

Awarded Partners

Florida International University
Louisiana State University & Agricultural and Mechanical College
Computer Science Department, Purdue University
University of Florida

Collaborative Partners

Indian Institute of Science
Oak Ridge National Laboratory
University of Hong Kong
Zhejiang University

For more information, visit the project web page at: http://nets.cis.fiu.edu/.