How AI makes video security proactive

Most security measures are essentially reactive. An alarm is tripped or a sensor detects that a window’s been opened outside of business hours. Both of these may help even when an incident is fresh; but they can’t prevent it. Video surveillance has long been reactive too: A surveillance recording might show when a thief struck but could do little to stop him.

How does today’s video surveillance move from reactive to proactive? Here are five ways that AI has already helped make that shift:

Sending alerts based on designated triggers:

Did an unknown vehicle just pull up to the loading dock? Is there movement in a hospital ward after hours? AI-powered surveillance systems can digest the content of a video stream and send alerts or trigger alarms based on previously configured rules. 

Eliminating expensive false positives:

For businesses that use sensor-based intrusion detection systems that communicate with an alarm monitoring service or directly with local law enforcement, false alarms are more than just annoying — they’re expensive. False alarms, especially repeated ones, can trigger fees or fines costing thousands of dollars. AI can eliminate the vast majority of false alarms by preventing alarms based on wind motion, rain, or animals. That makes future triggered alarms more effective, and more trustworthy.

Identifying and focusing on relevant activity:

When an incident is known or suspected, looking back at recorded video is necessary, and speed may be critical and there’s little time for real-time review. Scrubbing through old-fashioned video surveillance footage is a tedious, manual task. One labor-saving aspect of AI-aided surveillance is that recorded video with no relevant activity can be automatically skipped over or discarded while periods of observed activity are highlighted for quicker review.  

Leveraging AI for vehicle management:

AI can use increasingly sophisticated rules to trigger real-time actions based on pre-configured data, such as allow / deny lists for vehicles. License plate recognition (LPR) can isolate and analyze vehicle plates to allow known employees or pre-arranged visitors access to your premises or a parking facility. Just as more importantly, it can trigger alerts or deny entry to vehicles that are either unknown or specified as unauthorized. 

Applying analytics for real-time knowledge:

Smart surveillance systems do more than record screens full of pixels. Instead, they also analyze both within video frames (“Is that a backpack?”) and between sections of video (“Is this the same car that was here last night?”). Custom rules can turn information gleaned from video analysis into actions or alerts. For instance, counting abilities can help you know that a hallway or other public area is dangerously overcrowded.

Surveillance is so much more than cameras

These five AI capabilities are just the start, though; when a surveillance system is built with software access in mind, authorized third parties can make industry or context-specific solutions using their own analytics too. You can already obtain analytics to spot and investigate retail fraud, perform sophisticated license plate analysis, watch for work-site safety practice violations, and more. 

An excellent way to familiarize yourself with how AI is bringing proactive security to the forefront is by looking through the technology partners using Eagle Eye Networks’ open API to deliver specialized software in coordination with Eagle Eye Cloud VMS.

Want to see what your video surveillance system can do?

Eagle Eye Networks

Since 2012, Eagle Eye Networks has provided smart cloud surveillance solutions, leveraging AI to drive natural language search, automation, and more. Eagle Eye’s camera-agnostic approach heightens security while saving money, time, and resources.