AI Occupancy-Tracking Platform enables Social Distancing
An AI Neural Network platform uses radio CSI (Channel State Information) to provide reliable people detection for COVID restriction compliance in Buildings, Smart Cities and Transportation.
Occupancy tracking is becoming crucial in many people-centric applications, such as Social Distance regulatory compliance, Crowd Control, Building & Energy Management, Smart Cities and Transportation.
Crowd behaviours are usually unpredictable, which pose many challenges for crowd counting and estimation. Other challenges may include object occlusions and real-time processing requirement.
Classical solutions can be broadly categorized as “image-based” and “non-image-based” methods. An image-based counting model estimates the crowd density by analyzing the human characteristics in high-resolution images in the pixel, texture,or object level, often achieving a superb detection accuracy. However, sensitivity to scenario brightness, high computational costs, and privacy concerns are limiting factors that could confine the applicability of such image-based methods.
Bluewind presents here a “non-image-based” solution: an AI-based software platform designed to compute the number of people in indoor environment, providing real-time and accurate estimation of the crowd size.