Vehicle Camera and ANN Detection of Forgotten Items
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Solution Overview
Problem
Existing technologies lack an effective solution for detecting items left behind in vehicles, which can lead to safety hazards and property loss.
Innovation Solution
A vehicle system equipped with cameras and an artificial neural network (ANN) that monitors the vehicle's interior and exterior to identify items brought into the vehicle and alert the user if they are forgotten upon exiting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cameras and ANN are installed to detect forgotten items, then detection capability is improved, but device complexity increases
Solution Approach 1:
The camera system and ANN are designed to perform multiple functions: detecting forgotten items, monitoring vehicle surroundings, and identifying objects for autonomous driving decisions. This multi-functionality justifies the added complexity by providing comprehensive detection capabilities across different scenarios.
Solution Approach 2:
The system continuously captures images and processes them through the ANN in advance to build a database of detected items and their locations. This preliminary processing enables rapid detection and alert generation when the vehicle stops, without requiring complex real-time analysis at the moment of detection.
2Measurement precision
If the system continuously monitors vehicle interior and exterior, then detection accuracy is improved, but energy consumption increases
Solution Approach 1:
The monitoring system operates periodically rather than continuously, activating at key moments such as when the vehicle starts, stops, or when motion is detected. This periodic operation maintains detection accuracy for forgotten items while significantly reducing overall energy consumption compared to continuous monitoring.
Solution Approach 2:
The system uses the vehicle's existing sensor infrastructure and processing capabilities to perform detection tasks, rather than adding dedicated high-power monitoring components. This self-service approach leverages available resources efficiently, reducing the energy burden of continuous monitoring.
3Reliability
If the system alerts users about forgotten items, then safety is improved, but loss of time occurs due to system processing
Solution Approach 1:
The system performs preliminary detection and tracking of items throughout the vehicle journey, maintaining a ready state of knowledge about what items are present and where they are located. This preliminary action enables immediate alert generation upon vehicle stop without requiring time-consuming analysis at the critical moment.
Solution Approach 2:
The system provides continuous feedback to the user through the mobile application, notifying them of detected items and their locations. This feedback mechanism allows users to make informed decisions about item retrieval without delaying the vehicle departure, as alerts are provided in advance or in real-time during the journey.
Data Source
AI summary
Systems, methods and apparatuses to detect an item left in a vehicle and to generate an alert about the item. For example, a camera configured in a vehicle can be used to monitor an item associated with a user of the vehicle. The item as in an image from the camera can be identified and recognized using an artificial neural network. In response to a determination that the item recognized in the image is left in the vehicle after the user has exited the vehicle, an alert is generated to indicate that an item is in the vehicle but the user is leaving the vehicle.