A major U.S. city deployed Expanso to process video from 15,000 cameras at the edge, enabling ML-powered indexing, real-time analysis, and long-term archival.
Major U.S. City
Public Sector - Smart Cities
Edge Video Analytics & Public Safety
Expanso
The city faced significant challenges in managing and analyzing video data from its extensive surveillance network. Heavy reliance on human operators created bottlenecks, while limited storage capacity meant video footage was automatically purged after just seven days.
The city combined off-the-shelf hardware with Expanso to index edge video footage using machine learning and archive it locally. This approach reduced bandwidth consumption while maintaining data privacy by keeping sensitive footage on-premise.
Machine learning models run directly on edge devices to automatically index and categorize video content.
Indexed footage archived locally, reducing cloud bandwidth while enabling long-term retention.
Seamless integration with existing search infrastructure for rapid incident investigation.
The implementation delivered transformative capabilities for public safety and operational efficiency, enabling the city to derive real-time insights from its camera network while dramatically reducing costs.
See how Expanso can help your city or organization process video and IoT data at the edge, delivering real-time insights while reducing costs and maintaining data privacy.