A vehicle accident detection, warning method and system

By employing a multimodal perception and cloud-based collaborative vehicle accident detection method, real-time collection and fusion of multi-source sensor data, combined with a risk assessment model and a dual backup storage mechanism, the shortcomings of existing technologies in detection and response are addressed, achieving efficient and safe vehicle accident detection and early warning.

CN122432878APending Publication Date: 2026-07-21GUANGZHOU HUAGONG MOTOR VEHICLE INSPECTION TECH +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
GUANGZHOU HUAGONG MOTOR VEHICLE INSPECTION TECH
Filing Date
2026-04-29
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing vehicle accident detection technologies have shortcomings in terms of detection dimensions, response mechanisms, data storage, and alarm communication. They are unable to accurately identify complex accident scenarios, have insufficient data security, and offer only one alarm method, failing to quickly transmit information to emergency response units near the accident scene.

Method used

A vehicle accident detection method employing multimodal perception and cloud collaboration is adopted. It collects and fuses multi-source sensor data in real time, combines it with a pre-trained risk assessment model, and realizes accident type identification, severity level assessment and graded response. Data security and rapid response are ensured through dual backup of local storage and cloud, ZigBee short-range broadcast and GSM remote communication mechanisms.

Benefits of technology

It improves the accuracy of accident detection, reduces the false alarm rate, ensures data security, enables rapid rescue of high-risk accidents and effective management of low-risk events, and provides rich information dimensions to support accident cause analysis.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application relates to the technical field of intelligent traffic and vehicle safety, and discloses a vehicle accident detection and early warning method and system. The method comprises the following steps: collecting multi-modal sensor data of a vehicle in real time and synchronously storing the data in a local device and a cloud; judging whether the data is abnormal based on a preset algorithm; if the data is abnormal, performing comprehensive risk assessment, outputting an accident type, a severity level and a probability value; and performing a hierarchical response according to the risk level: triggering an emergency alarm, data security and short-distance broadcasting for a high-risk event; reporting a platform and starting an in-vehicle safety confirmation process for a medium-risk event; and silently recording and notifying a vehicle owner for a low-risk event. Corresponding systems are a vehicle-mounted intelligent terminal, a near-field emergency unit, a distributed data storage network and a cloud analysis platform. Through multi-sensor data and intelligent hierarchical response, the application significantly improves the accuracy of accident detection and the efficiency of emergency response, and ensures data security through local-cloud dual backup.
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