Video surveillance systems play an important role in public safety systems by allowing the monitoring of larger areas with fewer personnel. The goal of this proposal is to integrate advances in wireless networking and computer vision research to improve public surveillance systems. Existing camera-based surveillance systems typically rely on statically installed cameras to capture videos streams, which are then manually reviewed by law enforcement personnel. This is not only a relatively slow process, but also sometimes ineffective, since static cameras generally cannot be dynamically positioned to capture ad hoc events like flash mobs, street parties, and so on. Furthermore, most of the video cameras used in surveillance systems may not perform well in environments such as during the night, during inclement weather, and so on, due to poor lighting conditions. Our project proposes a surveillance system that uses 3D cameras affixed to moving vehicles, such as police squad cars. High speed wireless broadband networks are used to transmit the collected data for real time video processing and QoS adjustment. 3D cameras, unlike their 2D counterparts, perform far better under poor light environments. While individual components like wireless broadband networks and 3D video cameras already exist, the combination of these technologies to address a practical problem still requires addressing challenging problems. Local campus police department has agreed to provide domain expertise and facilitate testing of our prototype system.