How AI and security guards work together using video analytics

How AI and humans can work together is a longstanding debate. As society progresses technologically, there’s always the worry of robots taking over jobs.

Self-checkout tills, automated factory machines, and video analytics are all improving efficiency and productivity, but they can still work in tandem with humans, and in most cases, they need to. Video analytics in particular is one impressively intelligent piece of technology that security guards can utilise. How can video analytics help with certain security scenarios?

Video analytics tools

Before video analytics or even CCTV in general, if a child went missing in a shopping centre, we could only rely on humans. Take a crowded Saturday shopping centre, a complex one with a multitude of shops and eateries, you’d have to alert the security personnel, rely on a tannoy and search party, and hope for a lockdown to find a lost or kidnapped child. With video analytics, how would this scenario play out? It’s pretty mind-blowing.

As soon as security is alerted, they can work with the video analytics tools to instruct it precisely

With the same scenario, you now have the help of many different cameras, but then there’s the task of searching through all the CCTV resources and footage. That’s where complex search functions come in. As soon as security is alerted, they can work with the video analytics tools to instruct it precisely on what footage to narrow down, and there’s a lot of filters and functions to use.

Expected movement direction

For instance, they can tick a ‘human’ field, so the AI can track and filter out vehicles, objects etc., and then they can input height, clothing colours, time the child went missing, and last known location.

There’s a complex event to check too, under ‘child kidnap’. For a more accurate search, security guards can then add in a searching criterion by drawing the child’s expected movement direction using a visual query function. A unique function like this enables visual criteria-based searches rather than text-based ones. The tech will then narrow down to the images/videos showing the criteria they’ve inputted, showing the object/child that matches the data and filter input.

Detecting facial data

There are illegal demonstrations and troublesome interferences that police have to deal with

A white-list face recognition function is then used to track the child’s route which means the AI can detect facial data that has not been previously saved in the database, allowing it to track the route of a target entity, all in real time. Then, security guards can confirm the child’s route and current location. All up-to-date info can then be transferred to an onsite guard’s mobile phone for them to confirm the missing child’s movement route, face, and current location, helping to find them as quickly as possible.

Often, there are illegal demonstrations and troublesome interferences that police have to deal with. Video analytics and surveillance can not only capture these, but they can be used to predict when they may happen, providing a more efficient process in dealing with these types of situations and gathering resources.

Event processing functions

Picture a public square with a number of entries into the main area, and at each entry point or path, there is CCTV. Those in the control room can set two events for each camera: a grouping event and a path-passing event. These are pretty self-explanatory. A grouping event covers images of seeing people gathering in close proximity and a path-passing event will show when people are passing through or entering.

The video analytics tool can look out for large gatherings and increased footfall to alert security

By setting these two events, the video analytics tool can look out for large gatherings and increased footfall to alert security or whoever is monitoring to be cautious of protests, demonstrations or any commotion. Using complex event processing functions, over-detection of alarms can also be prevented, especially if there’s a busy day with many passing through.

Reducing false alarms

By combining the two events, that filters down the triggers for alarms for better accuracy to predict certain situations, like a demonstration. The AI can also be set to only trigger an alarm when the two events are happening simultaneously on all the cameras of each entry to reduce false alarms.

There are so many situations and events that video analytics can be programmed to monitor. You can tick fields to monitor any objects that have appeared, disappeared, or been abandoned. You can also check events like path-passing to monitor traffic, as well as loitering, fighting, grouping, a sudden scene change, smoke, flames, falling, unsafe crossing, traffic jams and car accidents etc.

Preventing unsafe situations

Complex events can include violations of one-way systems, blacklist-detected vehicles

Complex events can include violations of one-way systems, blacklist-detected vehicles, person and vehicle tracking, child kidnaps, waste collection, over-speed vehicles, and demonstration detections.

The use of video analytics expands our capabilities tremendously, working in real time to detect and help predict security-related situations. Together with security agents, guards and operatives, AI in CCTV means resources can be better prepared, and that the likelihood of preventing unsafe situations can be greatly improved.

It’s a winning team, as AI won’t always get it right but it’s there to be the advanced eyes we need to help keep businesses, premises and areas safer.