Machine Learning Automated People Counting
We created a machine learning-powered solution for automated people counting in public venues. The system uses computer vision and edge device hardware to count the number of people on-premise in real-time, while ensuring privacy compliance.
Custom convolutional neural networks for real-time people counting
Edge device hardware for local processing
Privacy-centric design ensuring no identifiable information is collected or shared
Challenge
Businesses and public venues needed a solution to track occupancy in real-time for compliance with safety regulations, especially during the pandemic, while maintaining user privacy.
Solution
We developed a machine learning-based solution that uses computer vision to count people in real-time. The data is processed locally on secured edge devices, ensuring no personal information is collected while providing accurate occupancy insights.
Results
Within three months of deployment, the system prevented 47 over-capacity incidents and provided valuable insights into traffic patterns, helping businesses optimize staffing and improve operational safety.
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