E-bike Event Detection via Bicycle-Wireless Data Fusion
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Solution Overview
Problem
Existing systems fail to effectively detect unexpected events associated with electric bicycles, such as collisions or falls, which require immediate assistance, due to the lack of reliable algorithms and sensors specifically designed for these vehicles.
Innovation Solution
A system comprising a bicycle data unit, a wireless device data unit, an unexpected event module, and an alert module that receives and processes data from both the electric bicycle and a wireless device to identify unexpected events and send alert messages to an assistance center via a cellular network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If algorithms and sensors from motor vehicles are used to detect unexpected events on electric bicycles, then the system can identify events based on vehicle parameters, but the detection reliability is insufficient for electric bicycles
Solution Approach 1:
The patent applies local quality by developing detection algorithms specifically tailored to electric bicycle characteristics rather than using generic motor vehicle algorithms. The system monitors electric bicycle-specific parameters such as motor torque, battery voltage, and wheel speed to accurately detect events like collisions or falls that are unique to e-bike operation
Solution Approach 2:
The system achieves universality by creating a multi-functional detection platform that can identify various types of unexpected events on electric bicycles including collisions, falls, and mechanical failures. The unified algorithm processes multiple data sources (bicycle sensors, wireless device accelerometers, and environmental data) to provide comprehensive event detection across different scenarios
2Measurement precision
If a comprehensive sensor system is implemented to detect all types of unexpected events, then detection accuracy improves, but the device complexity increases
Solution Approach 1:
The patent merges data from multiple sources including the electric bicycle's built-in sensors and wireless device accelerometers into a unified detection algorithm. This combination approach enhances measurement precision by cross-validating signals from different sensors while maintaining manageable system complexity through integrated processing
Solution Approach 2:
The system introduces an intermediary processing layer that receives raw data from various sensors, filters and contextualizes the information, and then feeds processed data to the detection algorithm. This intermediary layer simplifies the overall system architecture by centralizing data processing functions and reducing the complexity of direct sensor-to-detection connections
3Loss of time
If real-time event detection is implemented to provide immediate assistance, then the response time is reduced, but the computational requirements and system complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-configuring detection algorithms with threshold values and event patterns before actual events occur. The processor continuously monitors sensor data against these pre-established criteria, enabling rapid real-time detection without requiring complex computational analysis during critical moments
Solution Approach 2:
The detection system operates through periodic sampling of sensor data at optimized intervals rather than continuous processing. This periodic action reduces computational complexity by processing data at strategic moments when events are most likely to occur, while maintaining effective real-time response capability
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables timely and accurate detection of unexpected events on electric bicycles, reducing the risk of injury by initiating assistance promptly and minimizing false positives through data fusion from both the bicycle and wireless device.
Implementation Method 1
an acceleration sensor configured to determine an acceleration of the wireless device
Data Source
AI summary
An unexpected event detection system is provided for a rider operating an electric bicycle. The system includes a bicycle data unit configured to receive bicycle data from the electric bicycle; a wireless device data unit configured to receive device data from a wireless device; an unexpected event module coupled to receive the bicycle data from the bicycle data unit and to receive the device data from the wireless device, the unexpected event module configured to identify an unexpected event associated with the electric bicycle based on the bicycle data and the device data and to generate an alert message upon identification of the unexpected event; and an alert module coupled to the unexpected event module and configured to initiate sending the alert message to an assistance center.