Optical Waste Sorter UPC Extraction and Bin Assignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current waste disposal methods rely heavily on manual handling and classification, which can lead to errors and regulatory violations due to the lack of precise identification and sorting of hazardous waste products, especially when products with complex compositions or unknown identities are involved.
Innovation Solution
A system comprising an item sorter device with optical sensors and a processor that captures and analyzes data to identify waste products, applies site-specific classification rules, and communicates with a waste identification system to determine the appropriate disposal bin, utilizing UPC data and web scrapers to retrieve product information when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual handling and classification methods are used for waste disposal, then operational simplicity is maintained, but classification accuracy and reliability deteriorate due to human error and lack of precise identification
Solution Approach 1:
The patent replaces manual mechanical classification with an automated optical scanning system that uses optical sensors to capture images of waste products, processes the images through algorithms to identify product types and hazardous materials, and automatically determines disposal bin assignments. This substitution of mechanical human classification with optical-detection-based automation resolves the contradiction by achieving high classification accuracy while managing system complexity through modular design.
2Measurement precision
If automated identification systems are implemented to improve classification accuracy, then measurement precision improves, but ease of operation deteriorates due to increased system complexity
Solution Approach 1:
The system enables self-service automation where the optical scanning system independently performs waste product identification, classification, and bin assignment without requiring human operators to manually examine or categorize items. The system serves itself by automatically processing images, comparing them against databases of known products, and generating disposal instructions, thereby improving identification accuracy while maintaining operational simplicity through automation.
3Measurement precision
If comprehensive product database searches are conducted to ensure accurate waste identification, then measurement precision improves, but loss of time increases due to extensive data processing
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing images of waste products in a comprehensive database before actual classification is needed. When a waste item is scanned, the system compares it against this pre-prepared database of known products, significantly reducing the time required for identification and classification while maintaining high accuracy through the use of pre-analyzed reference data.
4Reliability
If manual waste classification is used, then device complexity is minimized, but reliability deteriorates due to regulatory violations and improper disposal
Solution Approach 1:
The system implements feedback mechanisms where the optical scanning system continuously monitors waste products, compares them against disposal regulations and classification criteria, and provides real-time feedback on proper bin assignments. This feedback loop ensures reliable compliance with disposal regulations by automatically adjusting classifications based on regulatory requirements, thereby improving reliability while managing system complexity through rule-based decision-making.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system reduces errors and regulatory risks by ensuring accurate classification and handling of waste products, improving employee efficiency and cost management by automating the sorting process and providing precise disposal guidance.
Implementation Method 1
at least one optical device configured to capture optical data associated with a waste product
Data Source
AI summary
In some embodiments, a system may include an item sorter device. The item sorter device may include at least one optical device configured to capture optical data associated with a waste product, a display, and a processor coupled to the at least one optical device and to the display. The processor may be configured to automatically extract universal product code (UPC) data from the optical data, search one or more data sources based on the UPC data to determine a match, determine a bin of a plurality of bins for storage of the waste product based on the match and based on site-specific classification rules, and provide a graphical interface to the display indicating the determined bin.