1. Adopt dynamic hierarchical and distributed data collection
2. Adaptive to business changes, flexible switching of data collection and collation rules
3. It can be compatible with different data sensing sources and select the most reasonable candidate data based on machine learning experience
4. Streamlined program assembly line to further improve data perception efficiency and save resource consumption

1. The four factors of "people, vehicles, road and environment" in the driving process are integrated, making the whole driving process completely transparent
2. The picture and video alarm mechanism triggered based on abnormal rules can comprehensively improve the efficiency and level of supervision and truly transform "passive" management into "active" management.
3. It can identify more than 90% of dangerous driving behaviors and effectively support a variety of business scenarios, such as vehicle danger state early warning, driving behavior analysis and assessment.

1. Sensitive induction, small footprint, low energy consumption, simple requirements for site wiring
2. Visual display of real-time parking space occupancy
3. The equipment conforms to outdoor standards, and has strong maintainability and expansibility

1.In-site intrusion alarm based on machine learning
2. Black light imaging technology meets 24 hours full color screen monitoring
3. Smart behavior analysis based on optical/thermodynamic attributes (Trans-boundary invasion, regional invasion, entering/leaving area), with alarm accuracy >96% and automatic filtering of birds and other small objects, reducing false alarm rate