Deployment of Wireless Mobile Detection and Surveillance for Data-Intensive Applications

Real-time information about traffic conditions is vital in construction, advanced traffic management systems, advanced traffic information systems, and other operational or design activities. Traditionally, at most permanent installations, such information is captured by in-pavement sensors and transmitted through land-based communications. However, temporary detection and surveillance are often needed as alternatives to the permanent sensor and camera systems at construction sites, during special events, or during communication or sensor failures. In such cases, temporary detection and surveillance must be reliable and low cost. Recent advances in wireless technologies have enabled development of portable detection and surveillance systems that can detect traffic, collect measurements, capture live video, and transmit this information wire-lessly back to the supervising station to facilitate rapid, inexpensive, and efficient deployment. However, to make widespread use practical, further improvements are needed in robustness, ease of use, functionality, and cost reduction. A low-cost, easily deployable detection and surveillance system is presented. The system integrates machine vision sensors for data collection, compressed digital video for surveillance, and wireless communications for information retrieval and remote control. It can be placed on existing or mobile structures and assembled with off-the-shelf components to serve department of transportation needs for both temporary traffic monitoring and planning and research data collection. Four of these advanced detection systems were deployed at a 1.7-mi site for wireless, continuous coverage, allowing detailed real-time data collection and surveillance. This data- and video-intensive deployment serves as a live laboratory for applications ranging from evaluation of new technologies (such as sensors, video, wireless communications) to testing of advanced traffic-simulation models or refinement of accident-prevention studies.