Vehicle Contextual Assistant for Driver Authentication and Fault Detection
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Solution Overview
Problem
Current vehicle diagnostic systems primarily serve technicians and lack functionality for vehicle owners, failing to provide new features or data collection and analysis capabilities beyond standard diagnostic functions.
Innovation Solution
A system that integrates with a vehicle's engine bus to collect and analyze data from sensors, including image and acoustic data, to identify authorized drivers, detect faults, and provide recommendations, using a processor and memory to execute instructions for facial recognition, gesture analysis, and contextual information processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If diagnostic systems are integrated with vehicle engine bus to collect and analyze data from multiple sensors, then vehicle management capabilities and safety features are enhanced, but device complexity increases
Solution Approach 1:
The system integrates multiple diagnostic functions into a single platform that can collect and analyze data from various sensors including image sensors, acoustic sensors, and vehicle bus data. The processor executes multiple types of analysis (facial recognition, gesture analysis, fault detection) through a unified system, allowing one device to perform many different diagnostic and monitoring functions rather than requiring separate systems for each function
Solution Approach 2:
The system nests multiple data collection and analysis functions within a hierarchical structure where the processor executes instructions from memory to coordinate data from various sensors and process them through layered analysis stages. The facial recognition system, gesture analysis, and fault detection capabilities are nested within the overall vehicle diagnostic platform, with each function operating as a specialized module within the broader system architecture
2Reliability
If facial recognition and gesture analysis are implemented using optical sensors, then access control and safety features are improved, but measurement precision requirements increase
Solution Approach 1:
The system uses feedback mechanisms where the processor continuously analyzes image data from optical sensors to identify facial features and gestures, compares them against stored profiles, and adjusts recognition parameters based on confidence levels. The system can request additional verification or adjust sensitivity thresholds based on the quality of detected features, improving reliability while managing precision requirements through adaptive feedback loops
Solution Approach 2:
The system performs preliminary actions by pre-processing image data to enhance facial features before recognition analysis, and by pre-storing authorized user profiles and gesture patterns. The optical sensors are calibrated in advance and the system maintains lookup tables of recognized facial structures, allowing faster and more reliable identification without requiring extremely high real-time measurement precision for every parameter
Data Source
AI summary
The present disclosure is directed to methods and apparatus that may collect data from at a vehicle. Data may be collected by connecting to a port of an on board diagnostic bus at the vehicle or this data may be received via a wireless communication interface. Collected data may be stored at a database and this data may be analyzed to identify whether a person at a vehicle is authorized to access or drive the vehicle. This collected data may also be analyzed to identify faults that may occur at a vehicle and recommendations to responding those faults may be provided to a driver of the vehicle via a user interface such as a speaker or display at the vehicle.