Smart Waste Bin Classification With User Rewards

Solution Overview

Problem

Current public trash receptacles lack effective incentives for proper waste disposal, leading to improper sorting of waste and increased burden on waste management companies.

Innovation Solution

A smart waste bin system using recurrent convolutional neural networks for waste classification and stereo video input, which provides financial rewards to users for disposing of waste correctly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional trash receptacles with labeled openings are used, then waste classification guidance is provided, but there is no incentive for users to deposit waste into the correct opening and human error remains high

Engineering Contradiction:

Improvewaste sorting accuracyVSAvoiduser disposal effort

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system provides immediate visual feedback to users through a display device that shows whether the deposited item was correctly classified. The system captures an image of the deposited item, compares it against the intended receptacle type, and provides feedback to the user. This feedback mechanism increases sorting accuracy by guiding users to place items correctly while maintaining ease of operation through automated classification.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent replaces manual waste classification by workers with an automated image recognition system using a processing device and machine learning models. The system automatically classifies waste items based on captured images, eliminating the need for human workers to manually sort waste while maintaining high accuracy in waste classification.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If waste management companies hire workers to sort garbage manually, then proper classification can be achieved, but labor costs and operational burden increase significantly

Engineering Contradiction:

Improvewaste classification accuracyVSAvoidwaste management system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces manual waste classification by workers with an automated image recognition system using a processing device and machine learning models. The system automatically classifies waste items based on captured images, eliminating the need for human workers to manually sort waste while maintaining high accuracy in waste classification.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The waste management system performs self-service classification by automatically identifying and sorting waste items using image recognition technology. The system captures images of deposited items, processes them through machine learning models, and automatically determines the correct receptacle type, eliminating the need for human intervention in the classification process.

Inventive Principle:

Principle #25Self-service

3Ease of operation

If small financial rewards are provided for waste disposal, then some incentive is given, but the reward is not seen as worth the effort by many users

Engineering Contradiction:

Improveuser disposal motivationVSAvoidwaste volume

Core Design Contradiction:

Ease of operationVSQuantity of substance

Solution Approach 1:

The system dynamically adjusts the reward amount based on the type, quantity, and difficulty of waste items deposited. Instead of providing a fixed small reward, the system varies the compensation parameter to reflect the actual effort and value of the disposal task, making the reward more meaningful and motivating users to properly dispose of waste.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system provides immediate visual feedback to users through a display device that shows whether the deposited item was correctly classified. The system captures an image of the deposited item, compares it against the intended receptacle type, and provides feedback to the user. This feedback mechanism increases sorting accuracy by guiding users to place items correctly while maintaining ease of operation through automated classification.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250292217A1Systems and methods for item management

Publication Date: 2025.09.18 QUANATA LLC

AI summary

An apparatus including one or more sensors, a deposit region, one or more processors, and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform certain operations. The operations include obtaining data of one or more items received into the deposit region, the data captured by the one or more sensors when the one or more items are in the deposit region. The operations also include classifying the one or more items as one or more types based at least on the data comprising two or more of: (i) one or more weights of the one or more items, (ii) one or more sizes of the one or more items, (iii) one or more materials of the one or more items, or (iv) one or more overall conditions of the one or more items. The operations additionally include determining an offer based at least on the one or more types of the one or more items. The operations further include presenting the offer to a user. The operations additionally include, when the user accepts the offer, exchanging with the user according to the offer. Other embodiments are described.