Vehicle Diagnostic System for Early Issue Detection
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Solution Overview
Problem
Current transportation systems lack an efficient method to identify and address issues in stationary vehicles and notify similar moving vehicles of potential problems, which can lead to delayed maintenance and increased costs.
Innovation Solution
A system that determines issues in stationary vehicles, identifies the cause, and notifies moving vehicles with similar characteristics, using a processor and blockchain technology to facilitate communication and data sharing across the transportation network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a system monitors and diagnoses issues in stationary vehicles, then early detection and prevention capabilities are improved, but system complexity and implementation costs increase
Solution Approach 1:
The system segments the vehicle monitoring function into two parts: a comprehensive diagnostic system for stationary vehicles that identifies issues and determines causes, and a simpler notification system for moving vehicles that receives alerts about potential issues based on matched characteristics. This segmentation allows the complex diagnostic functionality to be concentrated in stationary settings while keeping the moving vehicle system simpler.
Solution Approach 2:
The system performs preliminary diagnostic actions on stationary vehicles before they become moving vehicles. By identifying issues and determining causes while the vehicle is stationary, the system can notify moving vehicles of potential problems before they occur, enabling preventive maintenance rather than reactive repair.
2Loss of time
If the system notifies moving vehicles of potential issues, then maintenance timing is improved, but information processing and communication requirements increase
Solution Approach 1:
The system extracts only the essential diagnostic information from the comprehensive stationary vehicle diagnosis and transmits it to moving vehicles as notifications. Rather than transmitting all diagnostic data, the system identifies and communicates only the critical issue characteristics and maintenance alerts, reducing information processing requirements while maintaining timely maintenance capability.
Solution Approach 2:
The system introduces a communication network as an intermediary between stationary and moving vehicles. This intermediary handles the complex information processing, matching characteristics between vehicles, and transmitting only relevant notifications to moving vehicles, thereby reducing the information processing burden on individual vehicle systems.
3Measurement precision
If characteristic matching between vehicles is performed, then notification accuracy is improved, but computational requirements and processing time increase
Solution Approach 1:
The system applies local quality by performing characteristic matching selectively rather than universally. It matches characteristics between the stationary vehicle with diagnosed issues and specific moving vehicles that exhibit similar characteristics, rather than notifying all vehicles. This selective approach improves notification accuracy for relevant vehicles while reducing overall computational requirements.
Solution Approach 2:
The system changes parameters by focusing on key distinguishing characteristics rather than comparing all vehicle parameters. By identifying and matching only the most relevant characteristics that indicate potential issues, the system achieves accurate notifications while significantly reducing computational complexity and processing time.
Data Source
AI summary
An example operation includes one or more of determining an issue related to a stationary transport, determining a cause of the issue, determining moving transports that do not have the issue, but exhibit characteristics similar to the cause, and based on the characteristics, notifying the moving transports of a potential of the issue.