A computer vision-based system was implemented to automate the process of detecting parking occupancy in the mall and predicting the future availability of slots by using the existing CCTV feeds. Live dashboards, predictive analytics, and automatic alerts enhanced the traffic movement, minimized visitor waiting times, and updated the overall parking activities.
Real-time AI safety monitoring software, “NVIDIA Jetson Nano,” was implemented by edge-based inference to automate safety gear compliance, detect helmets and gloves, and minimize on-floor hazards.
We helped restaurant staff track seat occupancy and customer movements to automate their operational workflow by building an AI-based system integrated with computer vision.
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