This represents a fundamental change in mindset when designing, deploying, and managing physical security systems across virtually every conceivable application. AI is driving this trend with new, faster, and more complex algorithms that provide more proactive and pre-emptive automated solutions. Nowhere is this more evident than in the field of video analytics.
Advanced video analytics delivers a much higher level of contextual analysis of events, providing organizations of all sizes and market classifications with information to better understand their ecosystems, business practices, and policies. They do so by defining distinct event rules, matching events to those rules, and finding anomalies where known rules are violated. This provides security professionals with a powerful solution to help automatically identify potential threats, providing higher levels of details and context that improve overall situational awareness on an entirely new level.
Applying Real Intelligence
Modern video analytics can potentially make technologies smarter in the same way they make humans smarter. Take a central monitoring station with hundreds of camera feeds monitored manually, which typically just displays those camera feeds that operators need to focus on at that moment in time. With new video analytics, system operators can be automatically prompted when an event is detected, enabling intelligent monitoring. This empowers a video management system to present the events that truly matter to the operators.
Today’s new generation of video surveillance cameras, embedded with analytics on the market allows users to more efficiently and cost-efficiently apply advanced video analytics specifically where required. For example, if a system-wide analytics solution has a rule defined to detect instances of “line crossing” or “loitering,” the very act of loitering or crossing an imaginary threshold may not necessarily constitute a security threat in every camera location, which can trigger numerous nuisance alarms. With the ability to correlate analytics on a camera-by-camera basis, users can now identify an individual loitering near an ATM or get too close to a production line as a potential threat or event of interest. This specific rule contextualized by location helps system operators better prioritize and manage security and various operational events with the added benefit of automated alerts.
This extends the practical applications beyond traditional physical security to an extensive range of business intelligence applications such as process management, pedestrian and vehicular trafficking, human resources, occupancy control/monitoring, compliance, and so much more.
AI Embedded Cameras Are Game Changers
New AI-embedded cameras bring intelligence to the edge with deep-learning video analytics for unprecedented accuracy and speed during live events and for post-event forensic searches. Purpose-built for professional commercial and industrial applications, these intelligent cameras are a force multiplier, strategically reducing false alarms and enabling a rapid response to intrusion, line crossing, and loitering events. Available in numerous configurations with different resolutions and feature sets, the new generation of AI-embedded cameras allows system designers and users to deploy precise combinations of imaging performance and features they need for their specific applications.
Looking Forward
AI-driven video analytics at the edge are just a small piece of a greater puzzle on the enterprise level. Metadata combined from AI-embedded cameras with data from access control systems, IoT devices, and various other types of sensors can provide even greater insight to achieve even higher levels of contextual awareness for security and business intelligence applications. This enables organizations to manage and deploy personnel to perform mission-critical tasks with greater efficiency – a true win-win across every level of operations.
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