What You Need to Know about Video Analytics

CCTV cameras are a basic component of most security systems to help security teams identify potential threats. In larger and more complicated installations, however, it might be more difficult to ensure that all active cameras and surveillance feeds are appropriately monitored.

Thanks to the development of intelligent technologies like AI and Machine Learning, modern surveillance systems may be programmed to automatically notice unexpected stimuli and security matters, allowing teams to focus on developing essential matters and events.

This is the core concept of video analytics. After all, it can independently analyze and extract insights from video data to aid in decision-making and enhance the efficacy of security measures.

Video analytics surveillance systems make reviewing and analyzing security footage easier and more productive. The ability to automatically categorize footage captured by several cameras over several days by matters of interest allows security personnel to identify and respond properly to suspicious conduct both in real-time and during investigations.

How, therefore, can video analytics yield such remarkable results? Video analytics systems process video inputs using algorithms developed to recognize certain stimuli. Photos in sequence are reviewed by specialized software programs that have been programmed to seek for particular object or events that could point to a security problem.

Simply put, video analytics generates insights into these events by using rule-based algorithms to detect anomalous deviations in a sequence of photographs. For instance, if a camera catches an object moving inside its field of view, video analytics will ask questions to assist define the object and evaluate whether its existence requires further action.

Video analytics cameras ensure that key areas are constantly observed by using a variety of video analytics algorithms designed to search for specific stimuli. Among the most widely used analytics are facial recognition, motion detection, crows’ detection, object tracking, people counting, and Automatic License Plate Recognition (ALPR).

To meet different use cases in different industries, several types and combinations of video analytics solutions can be developed. To meet specific industry requirements, security teams, professionals, and business owners can either invest in creating custom solutions or use off-the-shelf products to tackle common security and organizational management needs.

Real-time video analytics, which provides experts with instant insights into crucial organizational, infrastructural, and security activities, can be extremely beneficial to businesses in the majority of important sectors.