Social distancing detection algorithm

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The Social Distancing Detection Algorithm by Providence Healthcare is an advanced solution designed to monitor and enforce social distancing protocols in various environments, such as hospitals, offices, and public spaces. By leveraging computer vision and machine learning technologies, this algorithm analyzes real-time video feeds to detect and alert individuals who are not maintaining the recommended physical distance, thereby helping to reduce the spread of contagious diseases like COVID-19. Key Features and Functionality: - Real-Time Monitoring: Utilizes live video streams to continuously observe and assess the physical distances between individuals. - Automated Detection: Employs advanced object detection models, such as YOLO (You Only Look Once, to accurately identify people within the camera's field of view. - Distance Calculation: Measures the space between detected individuals using depth sensors and perspective mapping techniques to ensure precise distance assessments. - Immediate Feedback: Provides instant visual or auditory alerts when social distancing guidelines are violated, enabling prompt corrective actions. - Scalability: Designed to integrate seamlessly with existing surveillance systems, allowing for deployment across multiple locations without significant infrastructure changes. Primary Value and User Benefits: The Social Distancing Detection Algorithm addresses the critical need for maintaining safe interpersonal distances in shared spaces, a key measure in preventing the transmission of infectious diseases. By automating the monitoring process, it reduces the reliance on manual supervision, thereby enhancing efficiency and ensuring consistent compliance with health guidelines. Organizations can leverage this technology to create safer environments for employees, customers, and visitors, ultimately contributing to public health efforts and minimizing potential outbreaks.

PPE detection algorithm (Facemask)

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Video-based AI that detects degree of COVID-19 facemask policy compliance. Analyzes statistical patterns at scale. See also separate Room Occupancy & Social Distance compliance detection module. Created by Providence Health Care, working with multidisciplinary teams from the University of British Columbia, including the Dept. of Computing Science & Computer Vision Lab. Our mission is to improve patient outcomes, particularly the most vulnerable in our Long-Term Care and Acute Care settings.