Hesai Promotes 3D Lidar as Privacy-First Physical AI Infrastructure for Stationary Applications
Hesai argues that 3D lidar, unlike cameras, provides accurate spatial perception without capturing identifiable images, making it ideal for privacy-sensitive stationary AI deployments.
What Happened
Stationary applications for physical AI, such as intrusion detection and traffic management, require continuous spatial perception. Camera-based systems capture identifiable information and are prone to false alarms from lighting changes, limiting their reliability and privacy compliance.
- Lidar captures only shape and position, not images; cameras capture identifiable information.
- Lidar is unaffected by ambient lighting; cameras struggle with changes and shadows.
- Lidar provides highly accurate distance measurements; cameras have limited measurement accuracy.
Hesai offers a full portfolio of 3D lidar sensors—including the OT series for long-range 360° coverage, JT/XT for mid-range, and FT series for short-range—to serve a range of stationary applications. The company has partnered with firms like Beonic, Embotech, and Outsight in real-world deployments.
Why this matters
As physical AI expands into public spaces, lidar offers a way to monitor environments without compromising privacy, addressing a key limitation of camera-based systems.
Terms in This Story
- Lidar
- Light Detection and Ranging; a remote sensing technology that uses laser pulses to measure distances to objects.
- Physical AI
- Artificial intelligence systems that perceive and interact with the physical world, often using sensors like lidar or cameras.
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