Projects
Algorithm Based Object Recognition and Tracking (ABORAT) (RULETC)
Protecting Protecting the United States’ critical assets and vital infrastructures is at the forefront of most security professionals’ minds. Many organizations, however, face budget shortfalls, which equates to reductions in security spending. Advanced technologies have been developed in many areas which can enhance existing resources without having to hire additional personnel. One example of these emerging technologies is Algorithm Based Object Recognition and Tracking (ABORAT) software, which monitors video, identifies potential threat events, and alerts security personnel as the event is happening. A significant problem with existing ABORAT systems is that very few companies have expanded into this area causing a lack of competition in the market, which increases the cost of both the software and the specialized hardware required to operate the system. These high costs make the system prohibitive for many public safety and security professionals.
In order to reduce the cost, while increasing the effectiveness of ABORAT systems, the JSC and SecuraCorp embeded an ABORAT software package into a low-cost, multi-camera video server to increase the resolution and enhance both the performance and capability of the system. This embedded system underwent functionality testing within a laboratory setting, which will be followed by usability, scenario-based evaluation. The successful testing provided an affordable and more reliable and efficient ABORAT system that could be implemented by those in both the public and private sectors to safeguard the facilities they protect and the people they serve. The ABORAT project was funded by the U.S. Department of Homeland Security.
Visit Securacorp.com or the University of Lincoln for additional project information. Or, contact Ryan Baggett at 859.622.8261 or at Ryan.Baggett@eku.edu.
The ABORAT Project Team:
