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Artificial intelligence and machine learning are two, closely-related concepts, but with some distinguishing characteristics. Let’s take a look at what those distinctions are and how these technologies are being recognized in the security industry today.
The exact definition of artificial intelligence is hard to nail down, but it basically boils down to this: incorporating human knowledge into machines.
We use AI to teach computers how to do things that humans can currently do better. AI makes use of rules and algorithms in order to solve problems. Some examples of day-to-day technology that makes use of AI include:
Machine learning is a subset of artificial intelligence, and refers to a computer’s ability to not only process algorithms, but actually learn beyond its initial programming.
In machine learning, a computer works through a scenario, processes the data, and then searches for ways to improve based on what it learned. This involves an immense amount of data to reach the end goal of maximizing the performance of a task. Some examples of implemented machine learning technology include:
AI and machine learning aren’t just the future of the security industry, they are the here and now. As camera technology becomes more advanced, AI is implemented in a variety of ways: some of which are developed with user privacy in mind, and some which seem to disregard or even exploit consumers.
For both big corporations and the everyday user, there are a lot of perks to this advanced technology.
Some new security cameras come equipped with facial recognition technology: allowing users to filter through familiar faces and pay more attention to new ones. This technology also helps identify those who have been marked as a potential threat, and track them down.
As security cameras become more sophisticated, pet/animal detection is a useful feature. With this capability, users can be notified when a human comes to the door without having to worry about being alerted every time the neighborhood cat comes to sit on the porch throughout the day.
Some security cameras are starting to dive into the world of object tracking. Being able to recognize a firearm or zoom in and follow a face can be extremely useful capabilities—especially in the crime-fighting sector.
Another recent development in machine learning technology, as it refers to the security industry, is the ability to analyze a scene and distinguish the norm from the unusual. Advanced cameras can detect particular movements, like removing an object from its place: useful for businesses concerned with theft.
While all of these new AI capabilities and potential use cases are exciting, there is still a lot of progress that must be made before much of it is available to the everyday consumer. Last year, we wrote an article on the future of security video technology where we went over AI technology, post-incident video analysis, and real-time incident analysis. Check it out to learn more about where the industry is headed in regards to AI.
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