Camera-Based Waste Contamination Detection With AI Anonymization
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Solution Overview
Problem
Current waste management systems face challenges in identifying banned waste during collection due to manual processes prone to error, leading to contamination of waste streams and environmental risks, with no effective method to tie contamination events to a location and maintain privacy of waste generators.
Innovation Solution
An AI-based system using multiple camera angles and edge devices processes images or video streams to identify individual materials in waste containers, providing automated contamination detection and fill-level assessment while ensuring privacy through anonymization and remote AI processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual waste auditing is used to identify banned waste, then personnel can visually inspect waste containers, but the process is prone to error and only considers the first 30% of waste, leading to contamination of waste streams
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated optical system consisting of cameras, image processing units, and AI algorithms. The system captures images of waste containers and automatically identifies banned waste materials, eliminating human error and increasing both reliability and productivity of the inspection process.
Solution Approach 2:
The system enables self-service inspection where the waste auditing process performs its own analysis without requiring human personnel to manually examine each container. The automated image recognition system independently identifies contaminants, freeing personnel from repetitive manual inspection tasks.
2Loss of information
If manual waste auditing is used, then personnel can identify banned waste, but it is impossible to tie contamination events to a specific location, and the waste company assumes the risk and disposal costs
Solution Approach 1:
The system implements feedback by capturing location data (GPS coordinates) alongside waste container images and automatically analyzing them to identify banned waste. This creates a closed-loop system where contamination events are immediately tied to specific locations and customers, providing feedback for accountability and preventing future violations.
Solution Approach 2:
The system performs preliminary identification of banned waste at the collection point before the waste is transported to landfills. By detecting contaminants early and recording location information, the system prevents contaminated waste from entering the stream and enables immediate corrective action.
3Extent of automation
If cameras are used to capture waste images, then automated identification can be achieved, but privacy concerns arise regarding waste generator information
Solution Approach 1:
The system extracts only the necessary information for waste identification and contamination detection from the captured images, while deliberately excluding or anonymizing personally identifiable information about waste generators. This selective extraction maintains automation benefits while protecting privacy.
Solution Approach 2:
The patent introduces an intermediary processing layer that acts as a mediator between image capture and data storage. This intermediary automatically redacts or anonymizes sensitive personal information from images before they are stored or analyzed, allowing automated waste identification while protecting waste generator privacy.
Data Source
AI summary
Methods and system for identifying individual materials from waste streams are disclosed. A request can be received from a requester to assess waste within a waste container. Media in the form at least one of still images or video streams can be accessed from at least one camera located in association with a waste container. The media can be transmitted to an artificial intelligence (AI) platform for processing to determine the class of individual materials contained in the media and provide identification with a confidence level. A data file containing processing results can be created. A response can be generated and transmitted to the requester that initiated the request. The response can include data that further includes all materials found by the AI platform as contained in the media with a confidence level for each and at least one of an identification of the requester, container identification, and container location.