AI Bicycle Component Control for Rider and Terrain Adaptation
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Solution Overview
Problem
Human-powered vehicle components lack adaptability to user-specific conditions and environmental factors, leading to suboptimal performance and usability.
Innovation Solution
Integration of an input device and artificial intelligence processor in human-powered vehicle components and mobile electronic devices to generate and apply control information for electric actuators, including automatic transmission, assist force, suspension, brake, and presentation systems, based on input data related to the vehicle, rider, and environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional control methods with predetermined conditions are used, then device complexity is reduced, but adaptability to user-specific conditions and environmental factors deteriorates
Solution Approach 1:
The artificial intelligence processor enables the control system to automatically adapt to user preferences and environmental conditions without requiring complex manual programming or frequent user intervention. The system learns from user inputs and sensor data to autonomously optimize vehicle component control, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The system dynamically changes control parameters based on real-time sensor data and AI processing, allowing the vehicle to adapt to varying conditions. This enables high adaptability through software-based parameter adjustment rather than hardware complexity, resolving the technical contradiction.
2Ease of operation
If artificial intelligence processor is integrated for adaptive control, then usability and performance optimization are improved, but device complexity increases
Solution Approach 1:
The patent replaces traditional mechanical control systems with an AI-based electronic control system. The artificial intelligence processor analyzes sensor data and generates control signals for various vehicle components, substituting complex mechanical linkages and manual control mechanisms with intelligent electronic control, thereby improving usability while managing complexity through software intelligence.
3Measurement precision
If multiple sensors and AI processing are added, then measurement precision and control accuracy are improved, but loss of time for data processing increases
Solution Approach 1:
The artificial intelligence processor is trained in advance with extensive datasets to enable rapid inference during actual operation. By performing the computationally intensive learning process beforehand and storing the learned models, the system can quickly process real-time sensor data without significant delays, resolving the contradiction between measurement precision and processing time.
Data Source
AI summary
A human-powered vehicle component includes an input device, to which first information related to at least one of a human-powered vehicle, a rider of the human-powered vehicle, and environment of the human-powered vehicle is input. The human-powered vehicle component further comprises an electric actuator and an artificial intelligence processor configured to generate second information for controlling the electric actuator in accordance with the first information input to the input device.