Scalable Time-Space Surveillance System

Surveillance systems record spatially and time-referenced sensor data, such as video imagery. With a growing need to monitor larger regions for longer intervals, there is a corresponding geometric growth in the size of the four-dimensional time-space surveillance recording. Tools that allow efficient exploration of this time-space are key to extracting value from the surveillance data. The critical problem is to preserve spatial context and causal time correlation while providing timely access to vast amounts of distributed data. We propose an innovative solution that extends 3-D map viewers such as Google Earth to add a 4th time dimension. These 3-D maps are a recent innovation of their own¿they access geospatial data on demand from a vast, distributed database. Our innovation adds on-demand time-history distributed surveillance imagery to 3-D maps, and enables the capability to ¿fly through¿ a seamless 4-D time-space world. The end user implementation is easy and intuitive to use¿a simple ¿time throttle¿ is added to the existing spatial navigation controls of the map viewer. The proposed scalable time-space surveillance technology will greatly improve the efficiency with which meaningful data from large distributed surveillance systems can be acquired, monitored, and reviewed. We thus enable more efficient use of limited resources, and quicker response in time-critical situations. The benefits to safety would have applications in homeland security, military and industrial facility monitoring, and home security systems.