A large company responsible for the application of public health protocols was facing implementation challenges due to manual and semi-automated processes. Blackstraw deployed a real-time, AI-based health risk monitoring system across 600+ CCTV cameras within a single premise, delivering a 10x reduction in operational costs and reducing thermal screening time by 20x. The solution led to three published patents, creating a scalable and defensible foundation for large-scale health risk monitoring.
During large-scale public health monitoring initiatives, organizations encountered major challenges in enforcing safety protocols. These include social distancing, mask compliance, and temperature screening across large facilities. Manual monitoring was labor-intensive, inconsistent, and hard to scale. Point-based thermal checks led to bottlenecks and slowed response times. The client needed a real-time, automated solution that could continuously track various risk indicators across hundreds of live camera feeds, without adding to human oversight or operational complexity.
Real-Time Computer Vision Monitoring: Developed an AI-powered computer vision system capable of detecting social distancing violations, identifying face mask compliance, and performing thermal analysis simultaneously across multiple individuals.
Thermal Intelligence at Scale: Enabled non-intrusive thermal screening across live video feeds, eliminating reliance on manual or single-point temperature checks.
High-Throughput Video Inference: Optimized the solution for continuous, real-time inference across 600+ live CCTV camera feeds within a single deployment.
Production-Grade Deployment Architecture: Designed for centralized monitoring and uninterrupted operation across large physical environments.
Centralized, Automated Health Monitoring: Enabled continuous enforcement of health protocols without manual oversight.
Significant Cost and Time Efficiency: Achieved a 10x reduction in operational costs and a 20x reduction in thermal screening time.
Scalable Real-Time Deployment: Successfully scaled across 600+ cameras with consistent performance.
Defensible Intellectual Property: Created reusable IP, resulting in 3 published patents in computer vision–based health monitoring.
Enjoying this article? Share it with the World
