Video analytics, powered by AI and machine learning, is becoming increasingly more important in the security industry. Over the last decade, end users have started to actively demand intelligent, scalable and cost-effective security solutions. The trend has accelerated even more with the increased security concerns relating to Covid-19.
But what is video analytics exactly and what is the buzz all about? And more importantly, how does it improve security?
Artificial intelligence, Machine Learning and Deep Learning – Where do video analytics fit in?
You’ll have heard terms like artificial intelligence, machine learning and deep learning being used in relation to video analytics. However, there is a lot of confusion around what they actually mean, and how they are applied in the context of analyzing video. These terms are frequently used as synonyms, but they’re not the same thing. Artificial intelligence (AI) is intelligence performed by machines, whereas machine learning (ML) is the science of making machines learn based on their experience. Deep learning (DL) is a technique for implementing machine learning.
In other words, AI is a simulation of human intelligence, in which programmers create step-by-step rules for machines to follow. On the other hand, ML is effectively a subset of AI that allows the machines to literally learn from their mistakes.
So, where in all this do video analytics fit in? Video analytics use deep learning methods to detect, identify and classify objects in cameras’ field of view. In other words, video analytics is AI based on deep learning techniques, and is therefore a form of AI and ML.
Brief history of the evolution of video analytics – fast forward 60 years
The 1960s saw the rise of CCTV and increase in its adoption. However, as the amount of CCTV cameras grew, so did certain issues surrounding monitoring. Research showed that the more cameras an operator monitors, the less efficient they become at their task. This led to development of video content analysis, which we now refer to as video analytics.
The first generation of video analytics was very simple. It mostly relied on motion detection, resulting in a lot of false alarms. As time progressed, video analytics have been greatly refined.
For example, some of the most recent developments in video analytics include object detection and text recognition. The main benefit of these recent updates is saving operators’ time by enabling them to monitor several cameras simultaneously, as well as helping capture events in full.
Finally, modern video analytics use deep learning techniques, meaning cameras effectively learn what motion can be disregarded. For example, Videoloft is training a neural network to learn what a spider web looks like and therefore will hopefully be able to stop spider webs causing motion alerts. In turn, they can be tailored to specific customer needs and are far more reliable than ever before.
The role of video analytics in the security industry
Video analytics have not only improved the users’ experience when searching for historic important events, but have also enabled reliable real-time alerting. Furthermore, analytics also allow the user to more effectively analyze situations that could be dangerous, and help spot potential weaknesses in security.
In summary, modern video analytics allow for real-time insight and monitoring. Moreover, because modern video analytics are based on AI and deep learning, they enable integrators to tailor security solutions to their customers. As a result, using video analytics can improve the efficiency and functionality of security systems.
Videoloft – video analytics applications
The main downside of implementing video analytics is the fact it is usually expensive. Not only is the initial cost high, as AI powered cameras are very expensive, but it also very often comes with an expensive VMS subscription. However, with Videoloft video analytics feature all you need to enable object detection, is a Videoloft Cloud Adapter. It also allows smart and easy search. Such advanced filtering helps users find the footage they want to view quicker than ever. It opens up an ability to analyze footage like never before.
Object detection with Videoloft’s video analytics
Not sure if something important happened, and you have lots of motion alerts to go through? With video analytics you can search your footage by object.
Let’s say you have CCTV on your business site, you have 15 motion alerts from overnight but you only really care if a person came onto your property. You can now search for ‘person’ and quickly find the clips where a person has been on your site.
Videoloft technology can pick up on hundreds of different types of objects, such as people, vehicles, machinery, clothing, safety equipment and wildlife. Worried it won’t be able to recognise objects during the night? Think again. Videoloft can detect hundreds of object types, even when visibility is limited.
Where we see our technology going – smart alerts
Videoloft’s next generation of analytics will be even more powerful. The Videoloft engineers are busy developing new features which further utilise analytics. Object detection and text recognition tools will be able to give you increased functionality, such as smart alerts. You might be monitoring a construction site and want to be notified if someone isn’t wearing proper safety equipment. You might have a remote property which has been targeted by trespassers out of working hours and want to be notified if a person is detected at night. The possibilities are endless!
Upgrade a basic CCTV system to an intelligent one
Purchasing AI powered cameras and the VMS subscription that goes with them can cost thousands. However, with the affordable Videoloft Cloud Adapter you can transform even the most basic CCTV systems into an intelligent one that can detect hundreds of objects and text. Videoloft’s video analytics makes intelligent CCTV accessible to anyone.
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