A COIN-inspired synthetic dataset for qualitative evaluation of hard and soft fusion systems

Traditional data fusion systems focus on processing of physical (“hard”) sensor data to achieve an understanding of an observed environment. The rapid dissemination of mobile phones allows humans to act both as a sensor platform and as an observer (a “soft” sensor). Currently, the methods for fusing hard and soft data are still at their infancy. Regardless of the specific techniques utilized to fuse hard and soft data, a key challenge involves how to obtain a calibrated data set involving both hard and soft data. This paper describes a new data set being developed at the Pennsylvania State University aimed at addressing this challenge. The data set is inspired by a Counter Insurgency (COIN) scenario in Bagdad. The data currently includes nearly 600 messages (“soft” data). The construction of synthetic complimentary hard data (e.g., simulated physical sensor data) is currently underway. The COIN scenario covers a four month period: 1 January 2010-May 2010, centered in Baghdad, Iraq.