Vehicle Service Event Detection From Transaction Data
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Solution Overview
Problem
Current vehicle maintenance and repair systems rely on manual record-keeping of mileage-based servicing, leading to inaccurate record-keeping and unnecessary wear and tear, and lack of efficient methods to track service events across transactions.
Innovation Solution
A system that analyzes transaction data using machine-learning techniques to detect and store vehicle service events, enabling automated record-keeping and providing service reminders through a mobile application, while integrating with banking and third-party reporting services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual record-keeping of vehicle service events is used, then input from multiple individuals (drivers, mechanics, parts distributors) is required, but this leads to inaccurate record-keeping and time-consuming processes
Solution Approach 1:
The system enables automatic self-recording of service events through transaction data monitoring. Service events are automatically detected and recorded when relevant transactions are identified, eliminating the need for manual input from multiple individuals while maintaining high accuracy through automated data capture from trusted sources
Solution Approach 2:
The patent replaces the manual mechanical process of record-keeping with an automated electronic system. Machine learning models and automated transaction monitoring replace the manual data entry process, transforming the system from human-operated to system-operated, thereby improving accuracy while reducing operational complexity
2Loss of time
If manual recording of service events is performed, then service timing can be tracked, but this results in delayed detection and processing of service events
Solution Approach 1:
The system continuously monitors transaction data streams in real-time to detect service events as they occur. This continuous automated monitoring eliminates delays inherent in manual periodic recording, ensuring service events are detected and recorded immediately when relevant transactions are processed
Solution Approach 2:
The system performs preliminary detection and classification of potential service events through automated transaction analysis before formal recording. Machine learning models pre-process transaction data to identify and flag service-related transactions, preparing them for immediate recording without manual intervention delays
3Reliability
If accurate service records are maintained manually, then service history can be documented, but this requires significant effort from multiple parties and is rarely maintained accurately
Solution Approach 1:
The system automatically maintains service history records through self-service automation. Transaction data is automatically captured, processed, and stored without requiring active participation from drivers, mechanics, or parts distributors, making the process extremely easy to operate while ensuring high reliability through consistent automated data capture
Solution Approach 2:
The patent introduces an intermediary automated system that mediates between various service stakeholders and the record-keeping process. This intermediary system captures data from multiple sources automatically, reconciles information, and maintains unified service records, eliminating the need for direct coordination between multiple parties while ensuring data reliability
4Loss of information
If traditional service tracking methods are used, then basic mileage-based servicing can be monitored, but this lacks integration with transaction data and provides incomplete service event information
Solution Approach 1:
The system performs multiple functions through a single integrated platform: it monitors transactions, detects service events, classifies event types, and maintains service records. This multi-functional approach consolidates what would otherwise require separate systems for each function, achieving complete service event data capture without proportionally increasing system complexity
Solution Approach 2:
The patent merges transaction monitoring with service event detection and record-keeping into a unified system. By combining these previously separate functions into one integrated system that processes transaction data to automatically identify and record service events, the system achieves complete service information capture while managing complexity through functional integration
Data Source
AI summary
Embodiments are generally directed systems, devices, methods, and techniques to detect vehicle service events in transactions, and to store the vehicle service events in a data store.