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Artificial Intelligence & Machine Learning in Security

Artifical Intelligence and Machine Learnig in SecurityOne of the fastest growing areas in the field of security technology is artificial intelligence (AI) and machine learning. This idea, once thought to be the stuff of science fiction, is developing at a rapid pace and has already begun to transform industries like agriculture, aviation and energy management. Integrating machine learning and AI into security technology is the logical next step into making sure that your business is protected, and it’s closer than we once thought.

Some AI capabilities that would prove extremely useful in security applications are:

Machine Vision – The technology and methods used to provide image-based analysis for such applications as automatic inspection, process control, and robot guidance.

Anomaly Detection – The identification of items, events or observations which do not conform to an expected pattern or other items in a dataset.

Natural Language – This type of processing allows users to communicate with a computer in their own words. Without this, AI can only understand the base meaning of language and answer rudimentary questions. The discourse would lack any semblance of context.

With these elements in mind, it’s easy to imagine AI monitoring security footage with machine vision, spotting something out of the ordinary with anomaly detection, and being able to communicate the issue with natural language. These processes in tandem will make security a much more efficient process.  We see this today in the advancing field of video analytics in CCTV surveillance systems.

What is Machine Learning?

One of the ways that AI is developing at such a quick pace is with machine leaning, a subfield of computer science that allows computers the ability to learn without being explicitly programmed. The fastest growth seen in machine learning has been in neural-network (neural-net) processing, and while most of us probably first heard of neural-net processing in James Cameron’s Terminator 2: Judgement Day, the real thing is far less treacherous. In fact, this type of process is helpful not only to security technologies, but our every day lives. Neurel-net processing is a paradigm inspired by a biological process, in this case, the human brain. In this video, Yufeng Guo explains rather plainly what machine learning is, and how we’ve been using it for years without necessarily realizing it.

Machine Learning & AI in Security System Applications

Machine learning occurs in video where data is produced far more quickly than data sources in typical electronic security systems, and the Internet of Things (IoT) – the collection of physical objects, vehicles etc. with network connectivity – which dramatically increases the amount of data available to security systems. For electronic security systems machines are able to absorb an extensive amount of data, and learn through context how things should be operating. Machine learning with a neural-net processor is a far more efficient process than traditional methods, involving stringent parameters limiting machines to understand something as a rule without context or malleability.

Artificial intelligence and machine learning are exciting technologies that are only going to get more advanced. As they progress, we’ll start to see the benefits they have to offer in the field of security technology more clearly. With the implementation of machine vision and anomaly detection, security systems are about to get even more sophisticated, which is something to be very excited about.

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