How accurate is AI Video Monitoring in detecting threats?

AI Video Monitoring is highly effective in detecting threats but is not infallible. Its accuracy depends on various factors, including environmental conditions, system setup, and AI model training. Here are some key insights from different AI-powered video monitoring solutions:

Accuracy of Threat Detection: AI Video Monitoring uses object detection and classification to differentiate between humans, vehicles, and other objects in real time. Evolon, our cloud-based AI algorithm provider, integrates advanced AI models that continuously learn and improve over time, increasing the accuracy of distinguishing genuine threats from non-threatening movements.

Challenges & Limitations: AI Video Monitoring is not always practical for accurate outdoor detection due to environmental factors like automobile light reflections, rain, snow, blowing leaves, and small animals. These conditions contribute to false positives and, in some cases, may lead to missed detections.

Use of AI Filtering: before escalating an event to a human operator, AI filters the video to determine if the scene contains a person or a vehicle. AI first determines whether an alarm is a “true positive” or “false positive.” If it is a true positive, the system sends the event to an operator for further action.

Continuous AI Training: AI models used in video analytics are continually trained and updated to adapt to new scenarios, improving accuracy over time. Cloud-based AI offers the advantage of real-time updates without the need for local software or firmware upgrades.

Best Practices for High Accuracy: To maximise accuracy, AI Video Monitoring systems should:

• Use high-resolution cameras with adequate lighting and a clear field of view.
• For proper recognition, ensure that objects to be detected are at least 10% of the camera’s field of view.
• Have a fixed high-speed internet connection to process video analytics efficiently.
• Risk of Missing True Positives: Despite its effectiveness, AI Video Monitoring can miss true positives, which means they may fail to detect an actual threat. This is one of the significant concerns with AI surveillance, and users should implement human verification and other security measures as a backup.

AI Video Monitoring is a powerful tool for enhanced security, reducing false alarms, and improving operational efficiency. While AI models have shown high accuracy rates, they are not foolproof. Environmental conditions, object detection limitations, and AI training quality all impact detection performance. Businesses should combine AI monitoring with human oversight and complementary security measures to maximise threat detection accuracy.