AI-Driven Debris Detector for Real-Time Robot Vacuum Triggering
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Solution Overview
Problem
Current cleaning systems often fail to promptly address debris on surfaces, such as spills or broken items, which can remain unsightly and pose hazards for extended periods, especially if they include sharp or toxic substances, due to scheduled cleaning times that do not align with when debris occurs.
Innovation Solution
A debris detector using artificial intelligence and cameras to compare frames and send notifications to initiate cleaning by robotic vacuums or alert humans when debris exceeds a threshold, including location data and potential hazards, and can guide the vacuum around obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If scheduled cleaning is used, then cleaning operations can be performed systematically, but debris remains on surfaces for extended periods creating hazards
Solution Approach 1:
The system performs preliminary detection of debris before scheduled cleaning time arrives. The camera continuously monitors surfaces and detects debris early, allowing the system to alert users or trigger immediate cleaning actions before the preset cleaning schedule, thus eliminating hazards while maintaining systematic operation
Solution Approach 2:
The system implements feedback by continuously monitoring surfaces with a camera and comparing current images against reference images. When debris is detected through image difference analysis, the system provides immediate feedback via notifications to users or automated responses by sending location data to robotic vacuums, enabling real-time response rather than waiting for scheduled cleaning
2Loss of time
If continuous monitoring is implemented, then debris can be detected immediately, but energy consumption and system complexity increase
Solution Approach 1:
The system uses periodic action by capturing frames at specific intervals rather than continuous monitoring. The camera takes periodic snapshots of monitored surfaces, compares them against reference images, and only activates full detection processing when changes are detected, thereby reducing energy consumption while maintaining timely debris detection capability
Solution Approach 2:
The system applies partial action by performing full image comparison processing only when necessary - specifically when frame differences exceed a threshold indicating potential debris. For normal periods with no changes, the system uses minimal processing, thus reducing energy consumption while maintaining the ability to detect debris immediately when it appears
3Measurement precision
If AI image recognition is used, then debris detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system uses partial action by implementing a two-stage detection process. First, a simple frame difference threshold check is performed to identify potential debris areas. Only when this threshold is exceeded does the system activate the full AI image recognition processing, thus maintaining high detection accuracy while reducing computational resource usage during normal operation
Solution Approach 2:
The detection process is segmented into distinct stages: frame capture, initial difference comparison, threshold evaluation, and AI-based debris confirmation. This segmentation allows the system to use computationally simple methods for routine monitoring and reserve complex AI processing only for cases requiring detailed analysis, balancing accuracy with resource efficiency
Data Source
AI summary
In some aspects, a debris detector includes one or more processors and a memory storage device to store instructions executable by the one or more processors to: receive a frame captured by a camera, receive a subsequent frame captured by the camera, compare the frame to the subsequent frame to determine a difference, and based on determining that the difference is greater than a threshold, send a notification indicating that debris has been detected. The notification may include location data identifying a location where the debris is located. Receiving the notification may cause a robot vacuum to initiate cleaning the location identified in the notification.