Artificial intelligence, or AI, is more common than you may think. Technology such as automatic incident detection or license plate recognition systems, facial recognition, and perimeter protection use some kind of artificial intelligence. Today, artificial intelligence has more applications in the field of security, which makes it an important factor for companies researching commercial security camera systems for their businesses. In this article, we’ll cover some of the best use cases for AI-based video surveillance systems.
How does artificial intelligence work? AI technology collects data points, and uses them to identify trends and trigger actions. The availability of huge amounts of data (big data), especially in image, video, and text, provides the raw material to train complex models of neural networks, better known as deep learning or machine learning.
Recent technological advances have allowed us to have great computing capabilities at affordable prices. The development of different options to implement machine learning at the hardware level, as well as different approaches on how to build the most appropriate architecture for each artificial intelligence application, such as GPU, TPU, NPU, or FPGA., has led to the availability of powerful tools to train complex models of neural networks.
The application of this technology to video surveillance processing, as well as to access control technology, has allowed companies to implement powerful algorithms to analyze facial features, and effectively identify individuals based on those features. Similar to the FaceID used in smartphones, facial recognition in video surveillance and access control can be used to authenticate a user, or identify a potential security risk. AI facial recognition technology has been used frequently during COVID-19 to detect if people are wearing masks or face coverings, and to help provide touchless experiences in offices and commercial buildings.
Incident and behavior detection
Deep learning systems also provide us with a reliable solution for the detection of incidents and anomalies in behavior. This type of deep learning is based on a peculiar and realistic mathematical method of tracking 3D moving objects, drastically reducing false alarms and simplifying the calibration of the desired algorithms.
With the use of artificial intelligence and deep learning, the software is able to identify the types of objects that move through the scene, reducing the typical problems of a standard system such as occlusions that hinder the analysis process.
In addition, problems caused by low lighting and bad weather conditions can easily be overcomed with the use of thermal cameras. Some video surveillance technology can even connect to existing CCTV cameras to enable AI detection and analysis without having to install new business security cameras. Also, AI allows much more flexibility in the location of the camera thanks to the software’s ability to distinguish objects, even if they are very close to each other.
With deep learning and AI, the extraction of visual characteristics is no longer defined manually and cameras actually “learn” more over time, becoming more accurate and reliable the longer they’re in use.