Vehicle Documentation System Using Sensor Segmentation
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Solution Overview
Problem
Current vehicle documentation systems lack efficiency in capturing consistent and high-quality images of vehicles for electronic review and bidding, particularly in varying environmental conditions and vehicle sizes, leading to suboptimal marketing and sales processes.
Innovation Solution
A vehicle documentation system equipped with multiple sensor systems, including cameras and light-intensity sensors, controlled by a booth controller device that adjusts lighting and captures images from various angles, using DMX protocol and computer vision for optimal image capture and processing, ensuring consistent documentation regardless of vehicle size or environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple sensor systems and controlled lighting are used to capture consistent high-quality images, then image quality and consistency are improved, but device complexity increases
Solution Approach 1:
The system divides the documentation task into multiple segments by using separate sensor systems positioned at different locations (front, rear, left, right) to capture images of different vehicle portions. Each sensor system independently captures images of its designated area, and the controller combines these segmented images into complete documentation sets, resolving the contradiction by achieving comprehensive coverage through modular segmentation rather than requiring a single complex system.
Solution Approach 2:
The controller device acts as an intermediary that coordinates between the multiple sensor systems, lighting systems, and the final documentation output. It receives images from various sensor systems, processes them according to vehicle size and type, controls lighting conditions, and generates the final documentation package. This intermediary coordination manages the complexity by providing centralized control over the distributed sensor systems.
2Adaptability or versatility
If the system adapts to different vehicle sizes and environmental conditions, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system dynamically adapts its operation based on detected vehicle characteristics. The controller receives images from sensor systems, determines vehicle size and type dynamically, and adjusts lighting conditions, sensor activation patterns, and documentation generation parameters accordingly. This dynamic adaptation allows the system to handle different vehicle sizes (compact cars to large trucks) and environmental conditions without requiring multiple fixed configuration systems.
Solution Approach 2:
The system uses feedback from the captured images to adjust its operation. The controller analyzes received images to determine vehicle size, position, and characteristics, then uses this feedback information to control lighting systems, adjust sensor parameters, and modify documentation generation. This closed-loop feedback mechanism enables automatic adaptation to different vehicle types and conditions, resolving the contradiction between versatility and complexity.
Data Source
AI summary
A distributed vehicle documentation system uses multiple sensor systems to capture vehicle information and generate vehicle documentation. A sensor system may be a micro server in communication with a sensor and a control device. In response to requests from the control device, the sensor system may analyze images input in order to identify an object in the images, and modifying the images based on the identified object. For example, in response to identifying a wheel in an image, the image may be cropped in order to be centered around the identified wheel. In the event that the sensor system cannot identify the object (e.g., cannot identify the wheel in the image), another image may be obtained with a different field of view based on a determined size of the vehicle.