Multi-Function Device User Limit Enforcement via Edge Video Analysis
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Solution Overview
Problem
Existing multi-function devices (MFDs) lack effective mechanisms to enforce user limits based on policies, such as limiting the number of users for health or cost-saving reasons, which can lead to inefficiencies and potential health risks due to the lack of real-time monitoring and enforcement.
Innovation Solution
A method and system that utilize continuous video monitoring and analysis by applying an object detection model to generate annotated images with bounding boxes around detected persons, comparing the number of bounding boxes to a threshold, and deactivating the MFD if the threshold is exceeded, with the help of an edge device and a counting server to offload computationally intensive tasks, allowing for policy enforcement and notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time video monitoring and analysis is implemented to enforce user limits, then policy enforcement capability is improved, but device complexity and processing load increase
Solution Approach 1:
The patent extracts the computationally intensive video analysis function from the MFD by implementing an edge device that runs the object detection model. The MFD only receives processed results (bounding box counts) from the edge device, thereby enforcing user limits without bearing the processing load of real-time video analysis.
Solution Approach 2:
The edge device serves as an intermediary between the video camera and the MFD. It processes video frames through the object detection model and communicates only the essential information (number of detected persons) to the MFD, which then enforces the policy based on this simplified data.
2Reliability
If video analysis processing is performed on the MFD, then policy enforcement is achieved, but primary functions like printing and scanning may be interfered with due to processing load
Solution Approach 1:
The patent extracts the video processing workload from the MFD's main processor by dedicating an edge device for this purpose. This ensures that the MFD's computing resources remain available for primary functions like printing and scanning, preventing performance degradation while still enabling policy enforcement through the edge device's analysis results.
3Measurement precision
If object detection model is applied continuously to video images, then user limit enforcement accuracy is improved, but energy consumption increases
Solution Approach 1:
The system applies object detection continuously to ensure accurate user limit enforcement, but this processing is performed on the edge device rather than the MFD. This allows the MFD to achieve precise policy enforcement while the energy-intensive processing occurs on a separate device that does not share the MFD's energy constraints for primary operations.
Data Source
AI summary
A method is disclosed. For example, the method executed by a processor of a multi-function device (MFD) includes receiving a video image of a multi-function device (MFD), applying an object detection model to the video image to generate an annotated image with bounding boxes around persons detected in the video image, determining a number of the bounding boxes, determining that the number of bounding boxes is greater than a threshold in a policy associated with the MFD, and deactivating the MFD.