Helmet Camera Accident Detection for Shared Electric Bicycles
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Solution Overview
Problem
Existing traffic accident detection methods for electric bicycles rely on manual operation, leading to delays in rescue and low detection efficiency, especially with the increasing number of shared electric bicycles.
Innovation Solution
A method using a helmet-mounted camera on an electric bicycle to automatically detect traffic accidents by entering snapshot or video recording modes based on real-time state information, determining accident severity, and sending alerts to target objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operation method is used for traffic accident detection, then staff members can monitor and report accidents, but detection efficiency is low and rescue time is delayed
Solution Approach 1:
The electric bicycle system performs self-detection of traffic accidents using its own sensors and camera, eliminating dependence on manual monitoring by staff members. The bicycle automatically captures images, identifies accidents, and sends alerts, enabling the system to serve itself in the detection process.
Solution Approach 2:
The patent replaces the mechanical manual monitoring system with an automated electronic detection system. Sensors and cameras on the electric bicycle automatically detect accidents through image processing and data analysis, substituting human operators with electronic automation to improve efficiency and reduce response time.
2Productivity
If automated detection system is implemented, then detection efficiency improves, but device complexity increases due to additional sensors and cameras
Solution Approach 1:
The electric bicycle system integrates multiple functions into a single platform: the camera serves both for navigation assistance and accident detection, while sensors monitor both riding conditions and potential collisions. This multi-functionality reduces the need for separate dedicated devices, managing complexity while maintaining high detection efficiency.
Solution Approach 2:
The patent combines accident detection functionality with the existing electric bicycle control and navigation systems. By merging the camera and sensor data processing with the bicycle's existing computational resources, the system avoids adding separate complex processing units, thereby improving detection capabilities without proportionally increasing overall system complexity.
Data Source
AI summary
The present disclosure provide a method for detecting traffic accidents by using the helmet of an electric bicycle, and the method includes: acquiring real-time state information of the electric bicycle; controlling a camera mounted on a front of the helmet of the electric bicycle to enter a snapshot mode and acquiring environment image information captured by the camera according to a first preset time interval in response that the electric bicycle is in the started state; and in response that the environment image information comprises the preset traffic accident image, controlling the camera to enter a first video recording mode, and sending the environment image information of a first preset period of time recorded by the camera and/or a first warning command to a first target object after waiting for the first preset period of time.