基于IOT驾驶安全风险干预的处理方法、系统、设备及存储介质
By analyzing multi-source data and adjusting risk factor scores using additive algorithms, an intelligent logistics transportation safety management system is constructed. This solves the problem that traditional manual supervision is insufficient to cope with the rapidly increasing number of vehicles and drivers in large logistics companies, and achieves precise and timely safety risk prevention and control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN LEAPFROG NEW TECH CO LTD
- Filing Date
- 2026-05-14
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional logistics transportation safety management models rely on manual supervision and post-event handling, which are insufficient to cope with the rapidly growing number of vehicles and drivers in large logistics companies, and lack forward-looking and systematic risk prevention and control capabilities.
By acquiring multi-source heterogeneous data, including DSM camera data, ADAS sensor data, GPS data, transportation business system data, and environmental data, and combining historical behavior, time, frequency, and environmental factors, an additive algorithm is used to adjust the risk factor scores to generate a refined total driving safety risk score. Corresponding measures are then taken according to the risk level to build an intelligent safety prevention and control system.
It has improved the accuracy and timeliness of driving safety risk assessment, adapted to diverse business scenarios, provided data support for the standardization and closed-loop management of safety, and enhanced the refinement of safety management and the optimization of resource allocation.
Smart Images
Figure CN122198666B_ABST