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Using Artificial Intelligence (AI) for surveillance security
Published 27th January 2020

There is a fine line between wanting to feel ‘watched over’ and feeling ‘watched’ which is why advances in security technology, such as smart CCTV cameras integrated with AI, leave many people on the fence. However, in a country rife with crime such as South Africa, there has been an undoubtable increase in the need for video monitoring and protection which has organically led to advancements in the sphere of security and surveillance technology. It’s a case of still wanting our privacy but also realising the dire need for improved security measures.

Video surveillance cameras have played their role as electronic eyes of security operations for many years but have always required humans to regard and make sense of the footage. Subsequently, it also relies on human-based assessment and decisions before action can be taken. Considering a business environment, imagine how many hours of surveillance footage, streaming from multiple cameras, a human would have to process before putting their finger on the problem- ultimately leaving room for vulnerability and weak spots.

This is where the merging of AI and camera surveillance can offer beneficial properties such as smart security technology and analysis that is in Real Time and not prone to human error. How does it work? AI uses machine-based learning and algorithms to monitor and analyse images, videos and data from video surveillance. AI has the capacity to recognise humans, vehicles and objects and the software can learn normal behaviour patterns. So, if something is displaying out of pattern behaviour then it will get flagged as an anomaly. AI software has an impressive ability to store surveillance from hundreds of thousands of cameras using the cloud; another big up on the ability of humans to do the same!

AI add brains to the digital eyes of cameras and serves to maintain or restore public safety, assist police and ambulances and is used to clarify and enhance low-resolution imaging; the focus is on optimisation and improving all aspects of security with ‘proactive’ detection and prevention. Did you know that algorithms and deep-learning in AI can even detect threats before they happen by noticing the slightest change in otherwise normal behaviour, thus preventing potential attacks? This means that our cameras, control-room equipment and back-end infrastructure can now ‘learn’ about potential threats for themselves.

Two types of AI security currently exist;

  1. Rule-Based: this is where programmers will feed the system with pre-designed rules.
  2. Behavioural Analytics: a newer form of AI where behavioural analytics is self-learning software that auto studies, analyses and learns normal human behaviour.
    Some application benefits of AI include: detection of suspicious suspects identification of different types of vehicles (including make and model), protection of work or home perimeters where unfamiliar objects or humans will trigger an alert and business intelligence which uses people counting and heat mapping..

The need for AI in security technology in homes and businesses is increasing at a rapid rate. The key lies in the incorporation of AI into our daily safety operations. If you want to join the smart security surveillance movement or find out more information, please contact Broubart security who has iCentre Control Rooms with the ability to monitor, detect, reduce risk and offer clients smart solutions which will save on the bottom line when implementing

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