Asset Fingerprinting for Decoding Non-Standard Vehicle Data Messages
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Solution Overview
Problem
Existing asset tracking systems struggle to accurately identify and decode data messages from vehicles that deviate from standardized communication protocols, particularly in electric vehicles, due to the increasing use of proprietary messaging protocols, leading to inefficiencies in data collection and identification.
Innovation Solution
An asset tracking system and data analysis system collaborate to determine an asset type fingerprint and generate signal definitions for decoding data messages by analyzing unique criteria in the messages, utilizing a repository of known data messages and fingerprints to identify and decode proprietary data types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If asset tracking systems use pre-loaded standardized protocols for decoding CAN messages, then data collection is reliable for standardized assets, but the system cannot adapt to vehicles using non-standardized communication protocols
Solution Approach 1:
The system performs preliminary actions by collecting raw CAN messages during a fingerprinting phase before actual data collection begins. These messages are analyzed to identify protocol characteristics, message formats, and data structures in advance, allowing the system to adapt to non-standardized protocols without real-time complexity
Solution Approach 2:
An intermediary protocol identification layer is introduced between the standardized asset tracking system and diverse vehicle protocols. This intermediary analyzes CAN messages, identifies protocol types through fingerprinting, and translates non-standardized protocols into standardized formats that the tracking system can process
2Loss of information
If the system collects data messages from all asset types, then comprehensive data coverage is achieved, but difficulty increases in identifying asset type and selecting correct decoding protocols
Solution Approach 1:
The system uses message fingerprinting to create unique 'signatures' or 'color codes' for different asset types based on their CAN message characteristics. These fingerprints act as identifiers that allow rapid classification of asset types without manual intervention, enabling the system to handle diverse protocols through pattern recognition
Solution Approach 2:
The protocol identification process is segmented into distinct phases: message collection, fingerprint analysis, protocol classification, and decoding selection. This segmentation breaks down the complex task of handling diverse protocols into manageable steps, improving both accuracy and efficiency
3Measurement precision
If the system uses a large library of signal definitions for various asset types, then decoding accuracy improves for known asset types, but system resources and initialization time increase
Solution Approach 1:
Signal definitions and protocol configurations are loaded and prepared in advance during system initialization or first-time setup. The fingerprinting process pre-identifies asset types and loads only the necessary signal definitions for those specific types, avoiding the need to load all possible protocol definitions before use
Solution Approach 2:
The signal definition library is dynamically loaded based on identified asset types rather than being statically loaded in full. The system adapts its resource usage by loading only the relevant protocol definitions needed for the currently tracked assets, reducing memory usage and initialization time
Data Source
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AI summary
Systems and methods for asset type fingerprinting and signal definition generation are provided. An example method involves receiving data messages from an asset, failing to identify an asset type fingerprint, requesting an asset type fingerprint for the asset from an asset data analysis system, providing access to data messages received from the asset to the asset data analysis system, generating a proposed asset type fingerprint that uniquely identifies the asset among known asset type fingerprints based on unique criteria identified in the data messages received from the asset, linking the proposed asset type fingerprint to a specified set of signal definitions that indicates how data messages are to be decoded from an asset of the proposed asset type fingerprint, and configuring the asset tracking system to obtain asset information from the asset by decoding data messages received from the asset with reference to a specified set of signal definitions.