Vehicle Usage Pattern Recognition for Automatic User Identification
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Solution Overview
Problem
Conventional methods for identity recognition in vehicle cockpits require manual input of credentials, leading to cumbersome and inefficient user experiences.
Innovation Solution
An object recognition method that compares vehicle usage data with reference data to determine similarity, automatically recognizing users based on preset thresholds, eliminating the need for manual input and enhancing efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual input of identity credentials is used for user recognition, then recognition accuracy can be ensured, but operation complexity increases and user experience deteriorates
Solution Approach 1:
The system automatically collects vehicle usage data (seat position adjustments, climate control settings, audio preferences, etc.) and uses this data for identity recognition without requiring manual input from users. The vehicle itself serves as the identification medium through its usage patterns, eliminating the need for users to manually enter credentials or perform verification operations.
Solution Approach 2:
The patent replaces manual mechanical operations (typing credentials, pressing buttons, scanning QR codes) with automated data collection and analysis systems. Sensors and control units automatically monitor vehicle usage parameters and compare them against stored profiles to identify users, substituting mechanical user actions with electronic detection and processing.
2Reliability
If manual identity verification is implemented, then security can be maintained, but time consumption increases and productivity decreases
Solution Approach 1:
The system pre-collects and stores vehicle usage data patterns for each authorized user during previous vehicle operations. These usage profiles (seat positions, temperature preferences, radio settings, etc.) are prepared in advance and stored in the control unit, enabling rapid comparison and recognition when the vehicle is started without requiring real-time verification operations.
Solution Approach 2:
The system continuously monitors vehicle usage parameters throughout operation, maintaining an ongoing record of user behavior patterns. This continuous data collection allows the system to dynamically update usage profiles and perform recognition at any time without interrupting vehicle operation, eliminating the need for separate verification steps.
3Ease of operation
If automated recognition systems are implemented, then user experience is improved, but system complexity increases
Solution Approach 1:
The system uses the existing vehicle control unit and sensor network to serve multiple functions: original vehicle control operations plus identity recognition. The same sensors that monitor vehicle operation (seat position sensors, climate control sensors, audio system sensors) are also used to collect recognition data, eliminating the need for separate dedicated recognition hardware and reducing overall system complexity.
Solution Approach 2:
The patent combines the identity recognition system with the vehicle's existing control and monitoring systems. The control unit that manages vehicle operations also performs data comparison and user identification, merging multiple functions into a single integrated system rather than adding separate complex recognition infrastructure.
Data Source
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AI summary
The disclosure relates to an object recognition method and system, a computer device, a storage medium, and a computer program product. The method includes: obtaining, in response to a trigger signal for a preset behavior state of an object, vehicle usage data of the object and reference vehicle usage data of at least one recognized candidate object; and determining that a similarity between the vehicle usage data and the reference vehicle usage data is greater than a preset threshold and that the object is recognized. The object recognition method and system disclosed herein simplify the recognition step, improve the recognition efficiency, and implement automatic object recognition.