I-Corps: Translation Potential of Advanced Behavioral Analytics for Enterprise Security Solutions

Award ID: 2451977

This I-Corps project focuses on a sophisticated data analytics platform designed to enhance event recognition capabilities within security systems. With retail theft increasing in the United States, the economic ramifications are profound, affecting employment and forcing closures of retail establishments. Traditional security measures such as perimeter breach detection, facial recognition, and reliance on human oversight are increasingly inadequate due to high rates of false positives and the limited operational attention spans by human operators. By integrating advanced artificial intelligence technologies, this project aims to improve the accuracy and efficiency of behavioral pattern analysis in security applications, thereby addressing significant economic losses and enhancing public safety across various sectors. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of algorithms capable of interpreting complex human behaviors using new and emerging artificial intelligence technologies coupled with foundational machine learning techniques. These scientific advancements allow for a more nuanced understanding of security threats and a significant reduction in false positives. By accurately mapping human activities and interactions within monitored environments, this technology promises substantial improvements in security response times and decision-making processes, providing significant benefits to commercial entities by safeguarding assets and ensuring public safety. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ruth Shuman