Smart Waste Receptacle Vision System for Sorting Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
It is difficult for end users to determine what waste is recyclable and what is not, leading to contamination of recyclable waste and reduced recycling efficiency, and existing product subscription services often deliver products based on estimated needs rather than actual usage.
Innovation Solution
A smart waste receptacle system equipped with sensors and a vision system that identifies waste through images, categorizes it as recyclable or non-recyclable, and can reorder supplies based on identified waste, while also gathering information on product usage patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a smart waste receptacle with image acquisition and vision system is added to a waste bin, then waste identification accuracy is improved, but device complexity increases
Solution Approach 1:
The smart waste receptacle integrates multiple functions into a single device: image acquisition through cameras, vision processing to identify waste types, categorization into recyclable/non-recyclable bins, and automated reordering capabilities. This multi-functionality approach consolidates what would otherwise require separate systems into one unified receptacle, managing complexity while enhancing capabilities.
Solution Approach 2:
The system automatically identifies waste types using image processing, determines recyclability status, and initiates reordering of products without requiring manual user intervention. The vision system and controller work autonomously to process waste identification and trigger supply replenishment, reducing the need for complex manual operations.
2Productivity
If automated reordering based on actual usage is implemented, then inventory management is improved, but loss of information about usage patterns increases
Solution Approach 1:
The system continuously monitors waste composition through image analysis and uses this feedback to automatically adjust reordering decisions. The vision system provides ongoing information about actual waste types and quantities, which feeds back into the controller to optimize inventory management and product replenishment based on real usage patterns rather than estimates.
Solution Approach 2:
The patent replaces manual inventory tracking and estimation-based reordering with automated electronic systems. Image processing and vision algorithms substitute for manual auditing, while electronic controllers automatically manage reordering processes, improving efficiency while capturing detailed usage information through digital means.
3Measurement precision
If multiple waste bins for different categories are used, then waste sorting accuracy is improved, but device complexity increases
Solution Approach 1:
The waste receptacle is divided into multiple separate bins, each dedicated to specific waste categories (recyclable vs. non-recyclable). This segmentation allows the system to handle different waste types separately, improving sorting accuracy while the modular design helps manage overall system complexity through clear functional separation.
Solution Approach 2:
Different portions of the receptacle system are optimized for specific functions: certain bins are designated for recyclable materials while others handle non-recyclable waste. The vision system focuses its analysis on specific waste items, and the controller applies category-specific handling rules, creating local optimization throughout the system.
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
The system effectively sorts waste, reduces contamination by ensuring correct disposal of recyclables, and optimizes product replenishment by automating reordering based on actual usage patterns, enhancing recycling efficiency and inventory management.
Implementation Method 1
A camera, or other sensor, is mounted on or near the smart waste receptacle and configured to acquire an image of waste
Data Source
AI summary
Embodiments relate generally to waste receptacles and more particularly to smart waste receptacles capable of identifying waste. A waste receptacle may identify waste using machine vision and perform a task in response to identifying the waste. In an embodiment, the smart waste receptacle may instruct a user to direct the waste to one of a plurality of waste bins based on a category of the waste. In an embodiment, the smart waste receptacle may place an order to replenish the stock of a product based on the identification of waste. In an embodiment, the smart waste receptacle is created by attaching a smart device to a standard waste receptacle.