Automated Whiteboard Cleaning System Using Motion Detection and Image Classification
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Solution Overview
Problem
Existing whiteboard cleaning systems require human intervention to determine when to clean the whiteboard, leading to inefficiencies and lack of automation in the cleaning process.
Innovation Solution
An automated system that uses a user movement sensor and a whiteboard capture camera, combined with an image classification module, to detect user inactivity and determine if the whiteboard needs cleaning, triggering an automated wiper to clean the board without human input, employing AI and machine learning for image processing and binary classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If an automated system with sensors and image classification is implemented, then the extent of automation is improved, but the device complexity increases
Solution Approach 1:
The system enables the whiteboard cleaning process to be self-service by automatically detecting user inactivity through motion sensors, capturing whiteboard images, classifying whether cleaning is needed through image processing algorithms, and triggering the wiper mechanism without any human intervention. The system serves itself by making autonomous decisions about when cleaning is required.
Solution Approach 2:
The patent replaces manual mechanical operations with automated systems. The motion sensor substitutes for human observation, the image capture camera and classification algorithm substitute for human visual inspection, and the automated wiper mechanism substitutes for manual wiping actions. This substitution of mechanical and human processes with automated systems increases automation while managing complexity through modular design.
2Productivity
If the system captures and classifies images to determine cleaning needs, then the productivity is improved, but the use of energy increases
Solution Approach 1:
The system employs periodic action by capturing whiteboard images only at specific intervals triggered by user inactivity detection, rather than continuously monitoring. The motion sensor detects when the user has been inactive for a predetermined period, then triggers a single image capture and classification cycle. This periodic operation significantly reduces energy consumption compared to continuous monitoring while maintaining high productivity by focusing computational resources only when necessary.
Solution Approach 2:
The system uses feedback mechanisms where the image classification result directly controls whether the wiper is activated. The classification module analyzes the captured image and provides feedback about the whiteboard's cleanliness state, which then determines the next action. This feedback loop ensures energy is consumed only when cleaning is actually needed, optimizing both productivity and energy efficiency.
Data Source
AI summary
A whiteboard cleaning system includes a user movement sensor that determines when a user is inactive; a whiteboard capture camera that makes an image of the whiteboard when the user movement sensor detects that the user is inactive; a classification module that classifies the image with a pre-trained image data set using an augmentation technique to enhance the size of the image data set and determines whether the whiteboard needs to be cleaned based on the classification, through transfer learning, using the image data set; and a wiper that cleans the whiteboard when the classification module determines that the whiteboard needs to be cleaned.