Multi-Agent Augmented Computer Vision Technologies to Support Human Monitoring of Secure Computing Facilities

Abstract

Humans are poorly equipped to perform repetitive tasks without adversely affecting the efficiency with which they are performing the task. One such task is the monitoring of CCTV footage to prevent the theft of, or tampering with, computing equipment. This paper introduces an approach towards security monitoring that uses a Computer Vision augmented with Speeded-Up Robust Features (SURF) as the catalyst to provide event-driven object detection to assist in securing an environment. A multi-agent artificial intelligence is used to improve the processing of event detection during the execution of these computer vision algorithms. The scenario of a secure computer environment is used to demonstrate the problems with current approaches and present an alternative to human monitoring using Computer Vision. The paper demonstrates that some of the physical aspects of information security can be improved through the use of SURF algorithms.