Waste Management Apparatus for Real-Time Contamination Analysis
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Solution Overview
Problem
There is a need for waste collection companies and their customers to obtain added value information about the waste collected during a waste collection tour to improve sorting quality.
Innovation Solution
A waste management apparatus mounted on a waste collection vehicle, equipped with optical sensors and a processing unit, continuously acquires images of waste, detects objects, classifies them, identifies new objects entering the vehicle, and sends information to a remote server, including object class, time, and location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If optical sensors and image processing are implemented on waste collection vehicles, then information quality about waste composition is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces manual waste inspection and classification with optical sensing systems and automated image processing algorithms. Cameras and sensors capture waste composition data, while software algorithms automatically classify materials, eliminating the need for manual sorting and information gathering by workers.
Solution Approach 2:
The system creates digital copies of waste streams through imaging and sensing, generating virtual representations that can be analyzed without physically handling or manually inspecting the actual waste materials. This allows information extraction while minimizing direct human interaction with potentially hazardous waste.
2Measurement precision
If continuous image acquisition is performed while the vehicle is in service, then measurement precision of waste data is improved, but energy consumption increases
Solution Approach 1:
Instead of truly continuous operation, the system uses periodic image acquisition triggered by waste deposition events or at regular intervals during collection. The imaging system activates only when needed to capture new waste entering the vehicle, reducing energy consumption while maintaining sufficient data coverage for accurate composition analysis.
Solution Approach 2:
The system performs preliminary processing of images on-board using embedded computers and algorithms, filtering and analyzing data before transmission. This preliminary action reduces the need for high-energy continuous communication and allows the system to transmit only essential information, lowering overall energy requirements.
3Productivity
If real-time object detection and classification is performed, then productivity of waste analysis is improved, but device complexity increases
Solution Approach 1:
The waste analysis system is divided into segmented functional modules: image capture, preprocessing, object detection, classification, and data transmission. Each module handles a specific task independently, allowing parallel processing and improving overall productivity while keeping individual components manageable in complexity.
Solution Approach 2:
The patent introduces an on-board computer system as an intermediary between the optical sensors and the remote server. This intermediary performs initial image processing, object detection, and classification locally, then transmits only essential results to the server, reducing communication bandwidth requirements and enabling faster real-time analysis.
Data Source
AI summary
Using a waste management apparatus mounted on a waste collection vehicle, images of the waste dumped into a hopper are acquired. Objects are detected and a class is assigned to each object in a predefined classification e.g. using an AI module. New objects are determined amongst the detected objects and information about the new objects are sent to a remote server, where each new object is mapped to an expected type of waste collection tour, suing a mapping table where sorting rules are stored. An actual type of waste collection tour is obtained, and a rate of waste contamination is calculated for a given location of the waste collection vehicle during a given waste collection tour as a function of the number of new objects identified, which classes are mapped with an expected type of waste collection tour other than the actual type of the given waste collection tour.