Machine Learning: What Is It and How Does It Work?
Machine learning is a practice that makes computers faster, smarter and more self-efficient than ever before. With technology accelerating at a faster rate than we can keep up with, computers are constantly evolving and becoming more intelligent. Like the name implies, machine learning is when a computer learns patterns, characteristics, events and more without specifically being programmed to do so. This powerful way of operating reduces the need for human interaction once the computer is up and running.
The process of machine learning closely resembles how the human mind learns. For example, how a CCTV system with facial recognition learns faces is very similar to how a human learns faces. When a person meets someone for the first time, they look at their face and takes notes of the distinguishable characteristics they see. These may be the size of a person’s nose, their eyes, their haircut, etc. When the person sees them a few more times, they begin to recognize them more and more. If the person gets a haircut or wears glasses they will still be recognized because they have learned their face.
This process is similar to how CCTV systems use machine learning for facial recognition. When a camera first views a person, it will take approximately 3-5 seconds to recognize the face and unlock a door based on their biometrics. After that, each facial recognition will be quicker and quicker because the system is learning every time it recognizes the face. Because the system is constantly learning, it will still recognize a person even if they are wearing glasses one day or grow a beard another. This eliminates the need for users to login to the system and update a person’s credentials when they get a haircut or grow facial hair. The system will learn and perform this action automatically.
Machine learning also applies to video analytics that detect objects. The longer an object is exposed to a camera’s view the faster it will recognize that object because the system has had more time to learn. For example, if a CCTV camera is constantly monitoring a bus garage, the system has a lot of time to learn and recognize the buses. If an SUV parks where a bus usually sits, the CCTV system will recognize that as unusual because it has learned how the environment is normally set up.
Machine learning eliminates the possibility of human error. Humans make mistakes, but computers do not if they are programmed correctly. For this reason, machine learning takes the risk of user mistakes away from a high-security environment or situation.
Please contact us to learn more about machine learning and how it can be used to make systems more accurate and efficient.