Exterior Camera Services for Vehicle-Sharing Fleet Monitoring
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Solution Overview
Problem
Vehicle-sharing and ride-hailing fleets lack effective exterior camera services for monitoring and managing vehicle interactions, cleanliness, and security.
Innovation Solution
A method and system utilizing sensors and cameras on vehicles to detect interactions with other vehicles, determine proximity, and transmit image data to a remote computing system for analysis, including activating cameras based on sensor data, generating cleanliness scores, and authenticating users for engine control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cameras are continuously activated to monitor vehicle interactions and cleanliness, then monitoring reliability is improved, but energy consumption increases
Solution Approach 1:
The camera system operates periodically rather than continuously, activating only when sensor data triggers specific events such as detected vehicle proximity or contact. This periodic activation maintains monitoring reliability for critical events while significantly reducing overall energy consumption compared to continuous operation.
Solution Approach 2:
The system uses sensor data from the vehicle's existing sensor network to automatically trigger camera activation without requiring continuous manual monitoring or constant camera operation. The sensors serve themselves by providing the intelligence needed to activate cameras only when necessary, reducing energy consumption while maintaining reliable monitoring.
2Measurement precision
If multiple cameras are activated to capture comprehensive image data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system activates specific cameras based on the local situation detected by sensors, such as which side of the vehicle is near another vehicle or which area requires monitoring. This selective activation provides high-quality image data for relevant areas without the complexity of having all cameras constantly active or permanently installed in all possible positions.
Solution Approach 2:
The camera system transitions from a static configuration to a dynamic one where cameras are selectively activated based on real-time sensor data. This dynamic activation allows the system to achieve high measurement precision for critical events while maintaining lower device complexity by using the same physical cameras in different configurations as needed.
3Measurement precision
If sensor data is continuously processed to detect vehicle proximity and contact, then detection precision is improved, but use of energy increases
Solution Approach 1:
The sensor data processing occurs periodically or event-driven rather than continuously, with the processor analyzing sensor inputs only at intervals or when specific thresholds are reached. This approach maintains high detection precision for vehicle proximity and contact events while reducing the continuous energy burden of constant data processing.
Solution Approach 2:
The system performs preliminary filtering and analysis of sensor data to determine whether activation conditions are met before triggering full camera activation and detailed processing. This preliminary action maintains detection precision by thoroughly analyzing critical data while reducing overall energy consumption by avoiding full processing for non-critical situations.
Data Source
AI summary
A method and system are disclosed and include obtaining sensor data from at least one sensor of a subject vehicle. The method also includes determining whether the sensor data indicates one of (i) a first vehicle has contacted the subject vehicle and (ii) the first vehicle is located within a threshold distance of the subject vehicle. The method also includes selectively activating, in response to one of (i) the first vehicle contacting the subject vehicle and (ii) the first vehicle being located within the threshold distance, at least one camera of the subject vehicle. The method also includes obtaining image data of the first vehicle from the at least one camera. The method also includes transmitting the image data to a remote computing system.