Waste Collection Vehicle Optical Sensor System for 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 to acquire images of waste, process them to detect objects, classify them, determine new objects entering the vehicle, and send information to a remote server including the class, time, and location of the new objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If optical sensors and image processing are installed on waste collection vehicles to detect and classify waste objects, then information quality about waste composition is improved, but device complexity and cost increase
Solution Approach 1:
The waste collection vehicle is equipped with an optical sensor system that serves multiple functions: detecting waste objects, classifying them by type, tracking their movement, and transmitting data to remote servers. This multi-functional approach consolidates what could be separate systems into a unified apparatus, improving information quality while managing device complexity through integration
Solution Approach 2:
The patent replaces manual waste inspection and classification with an automated optical sensing and image processing system. The processor automatically detects, classifies, and tracks waste objects in images, substituting human labor and mechanical sorting with optical and computational systems, thereby improving information quality about waste composition
2Loss of time
If continuous image acquisition is performed while the vehicle is in service, then real-time waste monitoring is improved, but energy consumption and data processing load increase
Solution Approach 1:
The optical sensor is configured to acquire images continuously during waste collection operations, creating a periodic sampling of waste entering the vehicle. This periodic image acquisition provides real-time monitoring capability while allowing the system to process discrete image frames rather than continuous video streams, managing energy consumption and data processing load
Solution Approach 2:
The system performs preliminary processing of images by detecting and tracking waste objects as they enter the vehicle, identifying new objects before they are fully processed. This preliminary detection and tracking allows the system to focus computational resources on significant events (new waste entries) rather than processing every pixel of every image frame, reducing overall energy consumption
3Measurement precision
If the system distinguishes new objects from previously detected objects, then waste contamination rate calculation is improved, but processing complexity increases
Solution Approach 1:
The system implements feedback by comparing currently detected waste objects with previously detected objects in the waste stream. The processor identifies new objects by detecting changes in the waste composition over time, using feedback from prior detections to establish a baseline. This feedback mechanism enables precise calculation of waste contamination rates by highlighting deviations from normal waste composition
Solution Approach 2:
The system creates digital representations (copies) of detected waste objects through image processing and object detection algorithms. By working with these digital copies rather than physical waste samples, the system can efficiently compare and analyze waste composition without handling physical materials, reducing processing complexity while maintaining measurement precision
Data Source
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AI summary
At a waste management apparatus (5) mounted on a waste collection vehicle (1), images of the waste dumped into a hopper (2) are acquired. Objects are detected and a class is assigned to each object in a predefined classification e.g. by using an Al module. New objects are determined amongst the detected objects and information about the new objects are sent to a remote server. At the remote server, 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 at said given location which classes are mapped with an expected type of waste collection tour other than the actual type of the given waste collection tour.