AISight: The World’s Only Behavioral Recognition™ System
AISight®, created by BRS Labs, is the ONLY video surveillance software that meets the needs of today’s ever-changing security environment.
Traditional video analytic software can only compare captured video activity to a list of preprogrammed objects and scenarios. It requires the costly setup of tripwires, zones of interest, and scene boundaries. Initial setup and subsequent maintenance is labor intensive and has demonstrated a poor return on investment.
BRS Labs’ AISight is advanced, intelligent software that uses Behavioral Recognition™ technology to learn—on its own—about the environment and objects it observes in each camera’s field of view. Since its learning is perpetual, AISight understands which activities commonly occur in any particular scene, bringing attention to objects or behaviors that are out of the ordinary through real-time alert notification. It begins autonomously learning about every environment it observes from the moment it is connected to a video network … AISight never requires the burdensome preprograming (or reprograming) necessary for legacy video analytic systems.
With eleven Registered Patents granted and more than fifty others pending, AISight is a unique, ground-breaking product whose capabilities surpass all other video analytic products. It provides accurate, real-time alerts to security personnel about real threats, while constantly learning to ignore the everyday behaviors that trigger the exponential number of false alarms in other products. Busy security personnel no longer need to waste valuable time with systems that continually cry wolf.
How AISight Works
AISight works with patented learning and analysis engines that enable the system to observe events, analyze them, and remember them similarly to how human brain makes and stores memories. When new events differ from AISight’s memories, it determines that a suspect event is occurring and alerts security personnel.
After the software has been started, it connects to the video network and begins to monitor the unique environment and activities for each individual camera. Each camera view is stored as a separate memory. Elements that are always present in the environment become part of the “background.” Objects that enter the field of view are analyzed based on their appearance, classification and interaction within its environment and other objects. AISight analyzes the structures, sizes, shapes, locations, velocities, accelerations, paths of objects and other characteristics of all objects within the scene and forms memories about them. It also records timestamps for these events and remembers during what times of day or days of the week events most frequently occur. Just like the “Long-term Memory” of the Human Brain, the more frequently certain objects and behaviors are observed, the stronger those memories become.
Whenever AISight observes objects and behaviors, it compares these events to its current memories. The less frequently it has observed an event in the past, the weaker its memory will be about the event and the more unusual it will deem the current activity. Unusual activity is immediately reported to security personnel to enable a proactive response to potential threats, but normal activity is ignored. And even when AISight has learned to ignore certain activities, it can still be told to alert security personnel of those activities regardless of how often they occur, if needed.
Just as frequent observation of objects and events reinforces AISight’s memories, memories that aren’t reinforced degrade. This means that AISight not only learns about commonly occurring activity but also “forgets” when that activity becomes less frequent, enabling it to alert on events that are no longer commonplace. Because of this unique ability to learn, remember, and forget, AISight’s ability to provide currently relevant, accurate alerts evolves alongside the environment. It adapts to moving vegetation, lighting changes, repositioning of furniture, weather patterns, and myriad of other environmental aspects that challenge video analytic systems.