Intelligent Video Monitoring Platform

At the core of the AI video monitoring system lies real-time analysis of video streams to detect abnormal behaviors, potential safety hazards and other suspicious activities, and trigger alarms or other response actions accordingly.

1. Flame Recognition Description: Trained on large-scale flame datasets, the flame recognition algorithm works with cameras to identify open flames within the monitored area in real time. It sends out immediate alerts once fire risks are detected. Suitable for construction sites, shopping malls, supermarkets and other premises with fire hazards, the solution adapts to various complex indoor and outdoor environments.
2. Bin Overflow Recognition Description: Powered by AI analytics, the bin overflow recognition algorithm automatically detects whether waste bins are full or if garbage has spilled over. It also checks for piled waste around the bins. If overflow or scattered rubbish is identified, managers will be notified promptly for cleaning.
3. E-bike Detection in Elevator Cabins Description: Based on AI visual analytics, the e-bike detection algorithm automatically identifies electric bikes entering elevator cars, stairwells or corridors. An on-screen alarm will pop up once an e-bike is detected. This effectively prevents fire risks caused by e-bike charging and enables safe management of electric two-wheelers.
4. Human Fall Detection Description: Leveraging computer vision technology paired with on-site cameras, fall detection automatically identifies falls in scenarios including homes for the elderly, nursing homes, subway escalators and staircases, and activity zones for children and seniors. The recognition accuracy exceeds 90%. It enables timely rescue, improves manual supervision efficiency and safeguards human life.
5. Hard Hat Recognition Description: Trained with massive hard hat image datasets, the hard hat recognition algorithm, working with site cameras, automatically checks whether on-site workers wear safety helmets. The accuracy is over 90%, delivering high-efficiency supervision.