We turned to three credible sources, Dell Technologies, tryo-labs, and Video Analytics, to endeavor to provide a concise yet comprehensive response to this question.
Traditional video surveillance systems typically provide two essential services: (a) the means to record activity in a given area, such as an ATM lobby, if there may be a need to review it later, or (b) allowing a security officer or security operations center (SOC) operator to watch live video feeds hoping to observe and respond to suspicious activity.
Video analytics software emerged from the extraordinary advances in video storage capabilities, combined with increasing hours of video footage and the limits of human capabilities. The primary objectives of the software are to automatically recognize sequential and spatial events in the video. Surveillance analytic software allows operators to receive real-time notifications of the events and actions that users pre-configure. The software monitors video feeds, alerting users to activity at a specific camera where something critical is happening. This process allows users to make the best use of the surveillance system – saving time and effort.
Video analytics can be an essential tool when monitoring for:
- Loitering and suspicious behavior
- Facial recognition and capture
- License plate recognition
- Alarm systems
- Gunshot detection
- Fire and smoke detection
Financial institutions can benefit from these enhanced video surveillance systems in several additional ways by proactively detecting suspicious behavior whenever predefined physical actions occur, in specific spaces including:
- Monitoring access to sensitive areas, vault openings, and night deposit activity.
- Safeguarding surveillance cameras with active tampering alarms.
- Detecting cash harvesting or the installation of skimming devices and other suspicious behaviors at ATMs.
The technology is available in various formats – because the software can reside on video cameras, network video recorders (NVR), on servers that are generally located in the monitoring station, or as third-party software. Video content analysis can be done in “real-time” by configuring the system to trigger alerts for specific events and incidents unfolding at the moment – or in “post-processing,” to analyze historical data to mine insights that can detect trends and patterns.