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2020: What’s in store for video surveillance?

2020: What’s in store for video surveillance?

Enterprise SecurityEuropeSoftwareTop Stories

As cybercrime evolves and people are becoming more aware of threats to businesses, the importance of modernising security systems for protection purposes is clear. Kevin Waterhouse, Managing Director at VCA Technology, explains the physical security and video surveillance trends we should expect to see this year.

Video analytics and Artificial Intelligence are making their mark in a range of different industries and security is undoubtedly one of them. As businesses rely less and less on vigilance staff, video surveillance has become a crucial business tool for security teams, enabling them to not only analyse footage retrospectively to identify criminals, but also significantly improve protection through live monitoring.

With the labour shortage affecting UK Monitoring Centres and crime rates on the increase, businesses have no choice but to turn to technology to support their overstretched teams and effectively prevent security incidents. When coupled with AI and Deep Learning, video surveillance is able to deliver vital information, empowering companies to enhance security and make better business decisions.

Here are five key video surveillance trends we see emerging in 2020:

Surveillance cameras: more than just security

Video Analytics have become a standard requirement in many security applications. However, as technologies such as Deep Learning and AI become more mainstream, video analytics will help video surveillance stretch far beyond its original remit. As we move further into 2020, we will see an increasing number of companies utilising their surveillance cameras not just for security, but also through video analytics and the metadata they produce, to obtain intelligent insight which can be used as a core business tool. Video analytics enable cameras to be deployed in many different scenarios and will provide businesses with a much greater return on investment than ever before, across multiple applications such as investigating customer behaviour, counting footfall and better optimising space and resources.

False alarms in video surveillance will decline due to increased adoption of video analytics

One of the biggest challenges continually faced by businesses when it comes to security is the vast number of false alarms raised by surveillance systems, which is driving complacency in the industry and increasing risk – some monitoring stations can experience several thousand false alarms from the monitored CCTV systems each night. With crime rates on the rise, 2020 will therefore see businesses increasingly adopting video analytics within their current systems, enhanced with AI and Deep Learning, to exponentially improve accuracy and detection rates, significantly reducing false alarms, increasing capture rates and creating more secure environments.

Surveillance cameras will no longer be a mere insurance tick box exercise

The majority of businesses set up security cameras for either insurance purposes, as a mere tick box exercise, without deriving any real advantage or insight from the technology. While this equipment represents a cost, companies are happy to pay it in return for peace of mind – yet criminals know that by covering their faces and wearing bland clothing, the likelihood of CCTV images being able to identify them is remote. However, with the increasing adoption of video analytics, we expect to see more conversations surrounding gaining a bigger return on investment from security spend; while a traditional surveillance system represents little or no deterrent for criminals, as the footage it collects is hardly ever monitored in real time and is often just recording a crime rather than preventing it. Choosing a modern system with analytic capabilities drives operational efficiencies by creating real-time alerts, before the intruder has breached the perimeter. This enables security staff to take a proactive and preventative approach, thereby improving security.

AI and Machine Learning will complement the human workforce

For several years, there has been an array of headlines reporting that Machine Learning will replace humans but this couldn’t be further from the truth. Although Machine Learning has advanced at breakneck speed, AI still requires humans to work alongside it to make decisions on the data it generates. When it comes to video surveillance, human workers have a limited attention span and research suggests that they suffer from fatigue after only 18 minutes, leading to poor monitoring performance and anomalous events being missed. As operators gain confidence with AI-driven analytic systems, they can adopt a more proactive response by reacting to potential threats based on AI-generated alerts, thereby reducing fatigue and screen blindness.

Businesses will now be able to rely on the technology’s consistently impeccable performance. AI relieves the human workforce of long hours of tedious video monitoring, only requiring their intervention to determine how to handle an incident once this has been proactively identified. Working in parallel, AI and humans will help companies improve detection rates, reduce false alarms and secure business efficiencies. This year, we will see the perception of AI change from a threat to humans to a complementary force and irreplaceable ally, allowing companies to improve operational efficiency, enhance customer service and reduce crime rates.

Fast and accurate event search facilities will become essential

Tens of thousands of security installations in the UK have very limited post-event search capabilities and rely upon basic methods of fast-forward and rewind on their NVR/DVR, making the process time-consuming, ineffective and inaccurate. The addition of AI and Deep Learning to these systems will allow monitoring room operators to set specific search criteria based on the metadata collected by the system, and produce meaningful detailed reports in minutes, rather than hours or days. Forensic search, post-event analysis and string searches are very powerful tools leveraged in all aspects of security – whether the application is law enforcement, incident detection, or property protection. Accurate, speedy search facilities, aided by Deep Learning and AI, will become an essential requirement of most middle to high end security systems.

As crime rates increase and threats to businesses become increasingly complex, the importance of modernising security systems to enhance protection and obtain real business benefits grows. Organisations will find themselves re-evaluating their security strategy, hoping to gain greater advantage from their existing resources and looking for new threat detection tools to make their environments more secure.

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