Most video surveillance systems can be upgraded with Artificial Intelligence (AI) based analytics to achieve significant gains in efficiency and responsiveness. AI video analytics use computer vision and deep learning to transform surveillance footage into searchable, structured data that detects objects, classifies attributes, tracks behavior, and enables intelligent search.
Traditional video review requires manual playback. AI-based systems allow for object-based filtering (person, vehicle, color), time compression (video synopsis), behavior detection (loitering, intrusion), metadata indexing, and smart alerts.
Milestone reports that in a recent study conducted by Forrester (independent research group) that AI-based video analytics produced an average of 30-60% faster handling of evidence in searching across multiple cameras and exporting footage. Hours of footage can be reviewed in minutes. Our own experiences show that with the proper setup, it is easy to zero in on specific information under investigation.
Value Goes Beyond Traditional Security and Law Enforcement
Upgrading Video Management Systems (VMS) with AI-based analytics is a great way to support security operations in government, education, manufacturing, and critical infrastructure with high volumes of video review. However, the analytics can be used effectively in environments where cameras are used for purposes beyond security such as retail customer flow, queue management, loss prevention, traffic flow optimization, workplace productivity and safety compliance monitoring.
Implementation Considerations
Most solutions integrate with existing CCTV and VMS system, adding analytics without replacing infrastructure. Implementation costs including software, hardware, storage, integration, and training vary by size and scope. A typical small implementation will run between $10,000 and $30,000, medium implementations between $30,000 and $200,000 and large-scale greater than $200,000.
Setup and initial training / fine tuning are often cited as key concerns; however, in our experience this has proven not to be a significant concern. Accuracy of results depends on camera quality and environmental conditions. The implementation process often includes server and software installation, checking cameras and changing configurations if needed, and creating virtual pathways of adjacent cameras. Generally, the most difficult part of the installation is working the firewall issues in integrating the server, Video Management System (VMS), network, clients and web interfaces. It is important to have the right multi-disciplined team members involved upfront for a smooth integration across the IT environment.
Privacy and legality concerns can be key issues impacting an AI analytics in video surveillance. The analytics turn passive video into searchable structured data containing what can be considered as personally identifiable information (PII) such as facial features, gender, and daily patterns. Most video analytic platforms have built in governance tools to deal with privacy issues.
Video Analytics Platforms
There are a number of leading AI video analytics platforms including BriefCam, Milestone Systems, Genetec, and Avigilon. TSG Security is happy to advise on the differences in these platforms and which options may be best for your needs.
Conclusion
AI video analytics transforms surveillance into a powerful operational and analytical tool, delivering measurable efficiency and business value.