The development, deployment, and operation of specialized video security solutions have long been essential components of any successful commercial video security installation. However, the extensive and advanced use of core technologies like cameras, storage systems, and processing systems has led to a major expansion of defensive capabilities.
One of the most beneficial technological developments in recent years has been the introduction of AI software and machine learning algorithms. Stakeholders have been able to automate a number of vital surveillance tasks and add fresh and engaging ways to human teams.
One crucial area where you shouldn’t take any short cuts is video analytics. But how knowledgeable are you in this area? Video analytics is the process of viewing and analyzing recorded video information to transform real-time data into illuminating and practical knowledge.
This enables active video security systems to identify and observe a range of objects and stimuli associated with security issues without the assistance of people during operation. In order to notify staff to events that deserve their attention, video analytics systems, for instance, can automatically identify and observe vehicles, people of interest, illicit products, and strange objects.
By implementing video analytics security solutions, on-site staff no longer need to continuously observe CCTV feeds manually. By alerting security staff to events that require their attention and action, AI systems instead ensure that areas are adequately safeguarded.
Video analytics solutions rely on rule-based algorithms to identify whether stimuli in live surveillance footage pose a hazard. Software tools will pose and answer a series of questions in a “if/then” decision tree. For example, if an object is discovered that is the same size and shape as a weapon, staff will be alerted to respond.
CCTV analytics systems observe live video by breaking down individual frames and analyzing each image separately. Rule-based algorithms are recording any changes as intelligent metadata so that this video can be continually analyzed in the context of the previously set decision tree.
The recording and documenting of this data enables deep learning in video analytics and enhances threat detection capabilities. In order to direct the operation of surveillance systems, artificial intelligence (AI) algorithms can identify patterns in data over time.
To put it simply, video analytics cameras can identify and identify objects, patterns, and movement that are connected to normal, safe activities. As a result, the system can more quickly identify and address actual security issues.
Understanding How Video Analytics Surveillance Technology Work
