Asset Message Decoding via Fingerprinting for Proprietary Vehicle Protocols
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Solution Overview
Problem
Existing asset tracking systems struggle to identify and decode data messages from vehicles that deviate from common 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 that utilizes an asset data analysis system to determine an asset type fingerprint and generate signal definitions for decoding data messages, by analyzing data from assets and updating local signal definitions based on received fingerprints and new protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If asset tracking systems use pre-loaded protocols and manufacturer-provided decoding instructions for standardized vehicles, then data collection reliability is improved, but device complexity and storage requirements increase, and adaptability to new vehicle types decreases
Solution Approach 1:
The system performs self-service by automatically determining asset type fingerprints and generating signal definitions without requiring pre-loaded protocols or manufacturer instructions. The asset tracking system autonomously analyzes received data messages, identifies unique signal features, and creates custom decoding protocols adaptively, eliminating the need for extensive preconfiguration while maintaining high data collection reliability across diverse vehicle types.
Solution Approach 2:
The system implements dynamic adaptability by transitioning from static pre-loaded protocols to dynamic fingerprint-based protocol generation. The asset tracking system continuously learns and adapts to different vehicle types by determining fingerprints from received messages and generating appropriate signal definitions in real-time, enabling seamless adaptation to new vehicle types without requiring updates to pre-loaded protocol libraries.
2Adaptability or versatility
If asset tracking systems attempt to identify asset type fingerprints locally for all asset types, then adaptability to diverse asset types is improved, but processing time and computational resources increase
Solution Approach 1:
The system applies partial action by focusing fingerprint determination efforts only on assets where standardized protocols fail. Rather than attempting comprehensive local analysis of all asset types, the system first tries standardized protocols and only initiates fingerprint determination when those fail, significantly reducing processing time while maintaining adaptability for non-standardized assets.
Solution Approach 2:
The system performs preliminary action by pre-determining and storing asset type fingerprints in a database during manufacturing or initial setup. When the same asset type is encountered again, the system retrieves pre-stored fingerprints instead of performing full analysis, dramatically reducing processing time for recurring asset types while maintaining adaptability for new types.
3Ease of operation
If asset tracking systems use standardized communication protocols only, then ease of operation is improved, but measurement precision for proprietary protocols decreases
Solution Approach 1:
The system introduces an intermediary layer consisting of asset type fingerprints and dynamically generated signal definitions between the standardized protocol framework and proprietary data messages. This intermediary enables the system to maintain the ease of operation provided by standardized protocols while achieving measurement precision for proprietary protocols by translating unique asset-specific message formats into the standardized framework through fingerprint-based adaptation.
Data Source
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AI summary
A method for by an asset tracking system is provided. An example method includes receiving a first plurality of data messages from an asset coupled to the asset tracking system and attempting to identify an asset type fingerprint based on the first plurality of messages. In response to failing to identify an asset type fingerprint based on the first plurality of messages, the example method further includes requesting a determined asset type fingerprint for the asset from an asset data analysis system, providing access to the first plurality of data messages to the asset data analysis system, receiving the determined asset type fingerprint for the asset from the asset data analysis system, and obtaining asset information from the asset by decoding a second plurality of data messages received from the asset in accordance with a set of signal definitions linked to the determined asset type fingerprint.