Automated Telematics System for Manufacturer-Specific CAN Data Collection
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Solution Overview
Problem
Current methods for collecting manufacturer-specific CAN data from vehicles are manually intensive, time-consuming, and prone to human error due to the variability of manufacturer-specific CAN messages across different vehicle types and models, which are not standardized.
Innovation Solution
A method and telematics system that collect and process CAN data using definition data to identify and define CAN payload data bytes and IDs for undefined manufacturer-specific data, involving subprocesses and monitoring devices to automatically determine and modify definition data for specific vehicle types, enabling the collection of manufacturer-specific CAN data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual reverse engineering methods are used to identify manufacturer-specific CAN messages, then data collection can be performed on any vehicle type, but the process becomes manually intensive, time-consuming and prone to human error
Solution Approach 1:
The system enables self-service by allowing the automated system to automatically identify, collect, and define manufacturer-specific CAN messages without requiring manual technician intervention. The monitoring devices autonomously capture CAN data, identify unique messages, and update definition data structures, eliminating the need for manual reverse engineering while maintaining high accuracy.
Solution Approach 2:
The patent replaces the mechanical manual process of reverse engineering with an automated electronic system. Instead of technicians manually accessing vehicles and analyzing CAN messages, monitoring devices with processors automatically capture, analyze, and define manufacturer-specific messages, substituting human mechanical work with automated computational processes.
2Adaptability or versatility
If technician access to each vehicle is required for data collection, then manufacturer-specific CAN messages can be identified, but the process becomes manually intensive and scalable only with additional resources
Solution Approach 1:
The system achieves universality by designing monitoring devices that can handle multiple vehicle types through a single automated platform. The definition data structure and automated identification process work across different manufacturers and vehicle models, allowing one system to perform the function of multiple specialized manual processes, thereby improving productivity without sacrificing adaptability.
Solution Approach 2:
The system implements feedback by using collected CAN data to automatically update definition data structures. As the system encounters manufacturer-specific messages from various vehicle types, it learns from the data, refines its definitions, and improves its ability to identify and collect messages from new vehicle types, enabling scalable productivity growth without additional manual resources.
3Ease of operation
If standardized CAN message definitions are used, then data collection is simplified, but manufacturer-specific unique messages cannot be captured
Solution Approach 1:
The system applies segmentation by separating CAN message definitions into standardized portions (from industry standards) and manufacturer-specific portions (uniquely identified through automated collection). This allows the system to maintain simplicity through standardized definitions while simultaneously capturing unique manufacturer-specific messages, preventing information loss without complicating the overall operation.
Solution Approach 2:
The definition data structure is made dynamic, allowing it to evolve from static standardized definitions to include discovered manufacturer-specific messages. The system automatically updates definitions based on collected data, enabling the data collection process to adapt and capture unique messages while maintaining the operational simplicity of standardized approaches for common messages.
Data Source
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AI summary
Methods and systems for identifying manufacturer-specific controller-area (CAN) data for a vehicle type are provided. Manufacturer-specific CAN data may be identified by processing defined CAN data having a correlation relationship with the target data and undefined manufacturer-specific CAN data for determining if there is a correlation relationship therebetween. Also provided are methods and systems for identifying and automatically collecting manufacturer-specific CAN data for a vehicle type.