THE NEXT SECURITY BATTLEFIELD: PREPARING UNDER VEHICLE SURVEILLANCE SYSTEMS FOR AI ANOMALY DETECTION

Vehicles have commonly been used as weapons for conducting anything from simple crimes to acts of terrorism. 

Enter the Under Vehicle Inspection Systems (UVIS). They addressed and mitigated the risk associated with multiple threat scenarios, interacted with related technologies such as License Plate Readers (LPR), Access Control/Gate Systems, CCTV, VMS, and Command Control (C2) systems. 

However, the Achilles heel of UVIS systems is that they are inherently dependent on an ordered and timed sequence of events. The order is always a process defined by an embedded sequence dependent on timing. Understanding these concerns, Comm Port Technologies, a developer of technology-based security solutions, introduced its Comm Port Area Scan (CPAS) under-vehicle surveillance and inspection system (UVIS) to meet the growing need for securing premises by checking vehicles at points of entry. CPAS UVIS is a complete inspection system consisting of an area scan camera, monitor, industrial PC, license plate reader camera, driver image camera, LED lighting, and associated hardware and software modules.

Comm-Port Technologies solved the majority of these interdependencies years ago with their Adaptable Matrix Software (AMS) concept. AMS is an advanced software/hardware technology that allows for independent and dependent programmable signal timing variations (inputs and outputs) within a UVIS system's sequential information capture processes. 

Today, in the security market space, there is a growing trend towards connecting the UVIS with Artificial Intelligence (AI)/Machine Learning (ML) and anomaly detection algorithms at security checkpoints, critical infrastructure security gates, port-of-entry facilities, and other high-security facilities. By utilizing AI/ML, under-vehicle inspectors can more efficiently identify hidden threats and safety hazards. 

An advanced UVIS with integrated AI/ML can generate high-resolution imaging captures of the undercarriage while the vehicle traverses over the scanning lane. 

Using AI/ML for detecting anomalies in a UVIS will lead to a significant advancement in practical inspection processes, as AI/ML will provide a faster and more efficient way to inspect vehicles and be capable of detecting many threats that human inspectors typically overlook. As edge-device-based AI continues to improve, and as sensor fusion and improvements to unsupervised anomaly detection mature, AI-enabled UVIS will become a common asset for both securing perimeters and fleet operations. 

CommPort’s new CPAS-AI provides the integrated software to create accurate and coherent anomaly datasets that create quicker response times and analysis reports for the security staff and decision makers for quicker entry point approval.