• 10 times Compression: : Offers near-lossless encoding for static cameras, preserving quality and saving bandwidth/storage by 90%.
• Ultra-Efficient Bandwidth Usage: Utilizes perceptual video compression and multi-view encoding to dramatically reduce bandwidth consumption.
• AI-Powered Perceptual Compression: Prioritizes key areas (faces, vehicles, license plates) while optimizing bitrate by compressing non-key areas.
• Multi-Format Support: Works with H.264/H.265, fits into main systems.
• Privacy Protection: Auto-blurring of sensitive data (faces, license plates) for GDPR/compliance.
• Safety Alerts: Flame/smoke detection, intrusion alarms, unmanned post monitoring.
• Behavior Analysis: Loitering detection, PPE (helmet/mask) compliance, restricted zone alerts.
• Multi-Format Deployment: Supports SDK integration, Edge AI hardware, and cloud/on-premise servers for diverse scenarios.
• Full Protocol Compatibility: Works with mainstream codecs, streaming protocols, and professional interfaces for seamless integration.
• Remote OTA Updates: Edge devices support over-the-air updates for easy maintenance.
• Challenge: Satellite bandwidth constraints hinder real-time video transmission.
• Solution: AI perceptual compression enables stable 100Kbps streaming, overcoming bandwidth limitations.
• Challenge: Starlink’s 8Mbps bandwidth struggles with multi-camera feeds.
• Solution: AI compression enables multi-stream transmission with smart detection.
• Challenge: High storage costs and bandwidth restrict camera coverage.
• Solution: AI compression reduces storage needs and supports more cameras within the same bandwidth.
• Challenge: Manual patrols and video lag reduce monitorin
• Solution: AI-enhanced analysis minimizes latency and automates inspections.
• Challenge: Manual monitoring misses critical equipment/personnel incidents.
• Solution: AI instantly detects failures and safety violations.
• Challenge: Public surveillance video consumes excessive storage.
• Solution: AI compression cuts storage needs by 90% without losing critical data.