Advanced AI Video Analytics

Hypersensor is Flame's proprietary technology that transforms existing security cameras into high-performance analytics sensors through AI software. Unlike dedicated counting sensors (infrared, thermal, stereoscopic) that require specific hardware per counting point at 500-2,000 EUR per unit, Hypersensor works with standard IP cameras and people counter sensors that most establishments already have installed. The AI processes video streams to extract multiple metrics simultaneously: People Counting, flow analysis, dwell time and Zones analytics, all from a single camera. This drastically reduces deployment cost and enables scaling to hundreds of locations quickly, as demonstrated by a major fuel retailer's deployment across 1,000+ service stations and a network of physical spaces across multiple venues.

Hypersensor achieves over 99% accuracy in People Counting, matching or exceeding the best dedicated stereoscopic sensors and significantly outperforming infrared (85-90%) and thermal (80-90%) sensors. The key is the deep learning model trained with millions of real-world scenarios — from busy shopping malls to physical spaces to retail stores — adapting to each installation's specific conditions. Hypersensor handles complex scenarios that cause errors in conventional sensors: compact groups, people with large bags, baby strollers, wheelchairs and counterflows at narrow entrances. Accuracy is validated through quarterly field audits at client installations including leading retailers, shopping mall operators and organizations managing physical spaces.

Yes. Hypersensor includes a staff exclusion module that learns to identify typical employee movement patterns — restricted access zones, repetitive movements, prolonged presence in work areas — and automatically excludes them from visitor counts. This is not based on facial recognition or personal identification, but on behavioral pattern analysis by zone. Alternatively, exclusion zones (stockrooms, staff areas) can be defined where all movement is discounted. For organizations with variable or large teams — whether managing physical spaces, retail chains or shopping malls — combining zone-based and behavior-pattern exclusion provides the most reliable results.

Hypersensor scales without practical camera limits. The architecture is distributed: each camera is processed as an independent stream, allowing cameras to be added incrementally without affecting system performance. In production, Flame simultaneously manages thousands of camera streams across its client network. For an individual deployment, sizing adapts to needs: from 2-4 cameras in a small retail store to 100+ cameras in a large shopping mall, through a major fuel retailer's 1,000+ locations. Cloud processing scales automatically. For clients preferring local processing (edge computing), Flame provides processing devices that handle 8-16 cameras per unit, stackable as needed.