Acadian Monitoring

STST has partnered with Acadian for their industry leading monitoring services since our beginning. Having a reliable monitoring service is critical in making the most of a camera intensive installation; without someone watching out for activity on your video feeds, the usefulness of the system is diminished. Acadian monitors several analytics from different video manufacturers. They also monitor motion-based triggers in cases where the camera is focused on a limited area with an analytics box drawn around the area of interest. 90 percent of what they monitor are external cameras using video analytics.
Traditional analytics are triggered using something called pixel modification formulas, while newer systems are starting to make use of machine learning driven formulas. In video analytics, most companies will make use of basically the same set of rules for triggering events and avoiding false alarms, even if they give them different names and trademarks for branding purposes. Below we will take a look at these rule sets.
Person and Vehicle Detection
This rule is used to alert on a person or vehicle when they have entered a zone specified to disallow their presence. This is the most common rule. Adjustments can be made for area size and time limits for the presence of the person or vehicle.
Group Gathering
As the name implies, this rule alerts the monitoring center when a group of people above a certain number have gathered in the specified area. This rule is often applied in high activity residential areas and in low income housing projects.
The typical amount of time set for event generation in the case of loitering is 30 seconds. Often employed by businesses with sidewalks facing their front, this analytic is able to limit false alarms from innocent people walking by but is still capable of triggering an event in the case of a breaking and entering attempt. This rule is not recommended if the front facing doors are glass.
Acadian also monitors thermal cameras. Thermal imaging is recommended in environments with low lighting or foliage that obscures a normal camera’s view.
Moving into the next decade, analytics will continue to be a critical part of the security and access control environment. Should machine learning advance as many project, these algorithms should be expected to become increasingly more robust and powerful, leading to the near elimination of false alarms and an almost human presence for all cameras and access control devices with analytics enabled. The total effects of machine learning are still somewhat speculative, but assuming any growth in the field, the possibilities may even exceed our current imagination.


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