Nowadays, surveillance cameras are installed almost everywhere. On a typical day in a major city, one may encounter hundreds of Closed-Circuit Television (CCTV) cameras. This massive deployment generates a vast amount of video data that security and monitoring personnel must review on a daily basis. Manually processing such a volume is nearly impractical.
Some systems have the capability to alert security personnel to potential threats based on what is captured by the cameras. These systems can read vehicle license plates and recognize certain faces. Others leverage specialized algorithms to detect suspicious activities, such as loitering near restricted access points or identifying unattended baggage.
Among these technologies, Briefcam stands out by integrating Machine Learning (ML) and Artificial Intelligence (AI) to enable video investigators to review hours of footage in just minutes and quickly identify persons or objects of interest.
One of Briefcam’s most prominent features is its ability to condense hours of video into just a few minutes, perform quantitative video analytics to extract actionable data such as facial features, color attributes, and vehicles, thereby facilitating investigations and decision-making, and to immediately respond to critical environmental changes.
1. Understanding the Architecture of a Video Analytics Solution
Component Connectivity Mechanism:
| Video Synopsis (VS) server | Handles user access interface, authorization, stream processing, and video storage. |
| Research Server (RS): | Performs data analysis and reports |
| Processing Server (PS): | Dedicated video processing server equipped with multiple GPU cards for decoding, data extraction, object detection, and classification. |
Provides both real-time online analytics and offline video search and analysis.
- Summarizes long video footage into short clips by simultaneously displaying multiple objects captured at different times.
- Enables search for objects (humans or vehicles) based on basic attributes (e.g., gender, color, behavior) using data from both Video Management Systems (VMS) and independent video files.
- Object Filtering Features: Filter by color, gender, direction of movement, zone/region, and vehicle type.
- Face Recognition Capabilities
Support for Analysis and Alerts:
- Real-time analytics
- Scheduled analytics based on predefined time intervals
Users can define monitoring rules, and the system analyzes real-time video sources to trigger alerts when events match those rules, such as:
- Virtual fences
- Intrusion detection
- Crowd detection
- Loitering detection
- Motion detection
- Directional movement detection
The system’s distributed architecture supports flexible scalability according to operational needs. Additional functional servers with performance matching the vendor’s sizing documentation can be seamlessly integrated.
Minimum 24-month support and warranty period.
2. Technical specifications
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Indicative price: 3000 $/channel
“Please contact us directly for consultation and a more accurate quotation.”
