Visual AI is the ability to automatically process a sequence of images to detect, track, identify, and analyze the behavior of objects and subjects within video. In today's rapidly evolving security landscape, visual AI transforms how organizations protect their assets, personnel, and information. By leveraging deep neural networks, machine learning, large language foundational models, and real-time video analytics, visual AI addresses some of the most pressing challenges faced by physical security teams, such as monitoring fatigue, false alarms, and reactive incident response.

This article explores how visual AI unlocks three superpowers to enhance physical security and operational efficiency.

Superpower 1: Enhanced Detection and Response Capabilities

Visual AI revolutionizes security operations by enabling real-time video feed analysis to detect anomalies and potential threats. Unlike many of today's video security systems, which rely heavily on human monitoring, visual AI systems reduce the margin of error and workload on security personnel by enabling cameras to understand when specific activity and behavior occur.

For instance, consider a large retail chain that implemented visual AI to monitor its stores. The system could detect unusual behaviors such as loitering near high-value items when a known shoplifter is on-premises and when unauthorized individuals access restricted areas. The system can trigger automated responses such as lockdowns, audible sirens, or direct notifications to local law enforcement when such activities are identified. This immediate detection and response capability significantly reduces the time it takes to address security incidents, thereby preventing potential losses and enhancing overall safety.

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Visual AI can handle the heavy lifting of monitoring by streamlining the detection and response process. Consequently, this allows physical security teams to move away from mundane tasks and focus on projects that can positively impact an organization.

Superpower 2: Improved Accuracy and Reduced False Alarms

One significant advantage of visual AI is its ability to improve detection accuracy for relevant events and reduce false alarms. Traditional video security systems often struggle to distinguish between genuine threats and benign activities, leading to numerous false alerts that can overwhelm security personnel and desensitize them to real dangers.

Machine learning models in visual AI systems learn from vast amounts of data to differentiate between normal and suspicious activities. Some systems even continuously learn based on your environment. According to a recent customer study, implementing a visual AI system reduced false alarms by up to 90% in a metropolitan area's public surveillance network, mainly because continuous learning allows these systems to adapt and improve over time, becoming more accurate as they are exposed to new data and scenarios.

For example, in a healthcare facility, visual AI can learn to ignore the routine movements of staff and patients while focusing on unusual behaviors, such as unauthorized access to medical supplies, or when a threat, such as a person holding a gun, is on-premises. This helps security teams focus on events that matter, improving incident response and saving time and resources.

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Superpower 3: Achieving Enterprise Scalability While Remaining Cost-effective

Visual AI systems offer unparalleled scalability, allowing organizations to expand their security coverage without significantly increasing personnel or costs. Organizations can enhance their monitoring capabilities by integrating AI with existing security camera infrastructure without investing in additional security cameras or DVR/NVR hardware. Additionally, best-in-class visual AI systems feature hybrid-cloud architecture that delivers the AI computation power directly to the camera network for optimal performance and efficiency.

For instance, a multinational corporation with offices worldwide can deploy visual AI across all its locations, ensuring consistent and comprehensive security coverage. The system's ability to simultaneously analyze video feeds from multiple sites and share data across the organization provides centralized management of global security operations. Furthermore, visual AI enables organizations to do more with less. Instead of hiring additional security personnel to monitor each location, the AI system provides centralized management, continuous surveillance, and real-time alerts, freeing up resources for other critical functions.

Conclusion

The world of physical security is rapidly advancing towards AI-based solutions. Visual AI’s ability to analyze video feeds in real-time and trigger automated responses ensures swift action against potential threats, reducing reliance on human monitoring and minimizing errors. This capability enhances overall safety and allows security teams to focus on higher-impact tasks. Moreover, the improved accuracy and reduced false alarms from continuous learning models enable security personnel to prioritize genuine threats effectively. The scalability of visual AI also allows organizations to expand their visibility across multiple locations without significant cost increases.

By effectively leveraging visual AI systems, organizations not only enhance security and safety but also empower their security teams with new tools to perform their duties more efficiently and effectively than ever before. Embracing visual AI transforms the security landscape, providing robust, scalable, and intelligent solutions to meet the evolving challenges of modern security.