Grant: Collaborative Research and Development Grants

Surveillance systems collect data and information about different aspects of objects (used in the sense of actors) and events in a given Volume Of Interest (VOI) and fuse them in order to provide a complete picture of the situation of interest. Most surveillance systems operate in an open-loop mode, i.e., they try to maximize the information gathered from the environment regardless of its value to the task/mission. Although these systems are able to handle a large number of objects and events, few have the ability to accurately and robustly discriminate the critical ones. A low Discrimination Power (DP) can result in a loss of opportunities for action, poor reliability, and, in some cases, inaccurate and undesirable effects, such as collateral damages, caused by taken actions. This project proposes a closed-loop approach to surveillance that optimally combines the sensing and the data/information fusion processes using a Pervasive Multi-Modal Surveillance System. The proposed approach aims at maximizing DP over critical objects/events by selectively collecting and fusing information based on high-level information about the task/mission. The results of this research and development project will advance the state of knowledge of this discipline by providing enabling technologies that will make surveillance systems reliable, adaptive and pervasive. The project involves collaboration of researchers, experts in their fields, from academic and industrial institutions pooling their talents to target this important research area. The developed methods and technology is of strategic importance to our industrial partners who specialize in real-time surveillance systems and intelligent decision support systems. The project fits very well into their plan for product development, growth and marketing strategy.