Artificial Intelligence offers an array of benefits to businesses, such as powering video surveillance systems which can help to minimise false alarms during a time when business leaders are dealing with more pressing matters. Kevin Waterhouse, Managing Director at VCA, explores how AI can be applied to security operations and ultimately, enhance business performance.
Artificial Intelligence (AI) can bring enormous benefits to many areas of our lives. From high-profile consumer applications such as voice-activated assistants like Alexa and Siri, to Amazon’s transactional AI which streamlines the commerce experience. AI can also make a difference in the security industry, but much confusion remains as to how the technology can be applied to this sector. One of the misconceptions about AI adoption in electronic security is that the tool is usually associated with facial recognition, as this is the area which dominates media headlines.
However, in order to fully understand how AI can help the electronic security sector, it’s important to become familiar with the different aspects of the tool and how they differ. As it stands, the term ‘AI’ is often used to cover concepts such as Machine Learning (ML) and Deep Learning (DL). These terms are often used interchangeably; however, they refer to different algorithms. ML, for example, is a branch of AI which utilises the concept that systems can learn from data, identifying patterns and improving processes or making decisions, with little to no human intervention. Whereas DL is a sub-category of AI that uses algorithms inspired by the structure and function of the brain, called artificial neural networks.
But how does this apply to security and, specifically, video surveillance?
AI has the potential to bolster core functions of security, most prominently CCTV and video surveillance. CCTV is by no means a new technology – but, when combined with analytics-based AI, it can bring new improvements to the security function of a business.
When analytics are incorporated within video surveillance, CCTV is transformed from a passive tool that simply records events, to an active one which can help teams quickly identify suspicious events. That being said, analytics-powered detection has been known to erroneously pick up on natural events and mistake them for potential threats. These false alarms are one of the biggest challenges faced by security professionals when it comes to analytics in video surveillance – they unnecessarily call upon staff members’ attention when they could be working on more pressing matters, causing the waste of time and resources. So how can these systems’ accuracy be improved? That’s where AI comes in.
Deep Learning, a subset of AI, can be deployed to ‘teach’ the system how to distinguish humans and vehicles from, for instance, a wind-blown tree branch – thus differentiating between a false alarm and a real threat. By calibrating the system to identify different moving objects, the machine can assess which events to flag to security teams, who can then determine how to address them. This way, only events that can truly pose a threat to the business create an alert, and staff members’ time and efforts can be focused on real security issues.
A timely help
The COVID-19 outbreak has undoubtedly had a considerable impact on the current business landscape across sectors, and security is no exception. With more than a fifth of the world’s population under lockdown, many buildings are left empty while employees work remotely. It’s clear that security risks are heightened. To make matters more complicated, as workers are furloughed or encouraged to stay at home to facilitate social distancing regulations, security teams are depleted and business premises have become even easier targets for those looking to exploit these vulnerabilities. It’s never been more urgent to enhance video surveillance systems. Firstly, analytics-powered surveillance solutions can take over the onerous job of constantly scanning live footage to spot unusual behaviour and alert the few remaining staff of potential intruders. With short-staffed security teams, the help of analytics-based threat detection that triggers an alert and determines when action is required is simply invaluable.
Furthermore, an overstretched workforce can’t afford to waste time on unimportant issues, that’s why companies require surveillance systems that identify threats with precision, minimising false alarms. In a situation where only a limited number of security staff are allowed at the premises, filtering out unnecessary alerts means resources are optimised and businesses safeguarded, without putting employees at risk.
As security threats change and businesses adjust to a new norm, video surveillance must evolve accordingly – and what better way to power this evolution than with a disruptive technology like AI? If businesses look beyond the flashy facade, real advantage can be obtained by enhancing video management systems with AI elements, and now – with the world facing an unprecedented crisis and companies battling new challenges – is the time to take the leap.