Work

Sustainable Smart Waste Sorting Through Reject-Aware IoT and Calibrated Vision: A Measurement-Calibrated Selective Routing Prototype

Year: 2026

Type: article

Abstract: Smart waste systems can support sustainable recycling only when sensing, classification, and routing decisions are linked to transparent uncertainty management. This study aims to develop and evaluate a measurement-calibrated, risk-aware selective routing prototype for sustainable smart waste sorting under bench-scale conditions. The proposed prototype integrates an HC-SR04 ultrasonic sensing layer, Arduino Nano control, ESP8266 wireless synchronization, calibration-based fill level conversion, median filtering, exponential smoothing, hysteresis, and persistence-driven alert logic with a conveyor-based single-item vision-routing layer. The sorting layer routes items into glass, metal, plastic, trash, or a reject stream using a reject-aware VGG19 classifier with true logit temperature scaling and calibrated confidence gating. A quantitative prototype-level experimental evaluation was conducted using a five class benchmark of 2527 TrashNet images under a stratified 75/10/15 hold-out design, with cardboard and paper serving as outlier-exposure samples for the reject class. The final model achieved 88.13% test accuracy, 88.15% weighted F1, and 96.60% reject class F1. With a final policy tau = 0.70, the system routed 76.09% of routing class test items with 92.66% routed precision, while reject recall reached 98.66% and reject false acceptance was limited to 1.34%. Structured perturbation testing showed that severe visual degradation reduced automatic routing coverage but mostly shifted uncertain cases toward rejection. The contribution of this work is a transparent prototype-level mechanism that links calibrated sensing, calibrated visual confidence, selective rejection, and actuation-aware routing to support recycling stream purity under bounded uncertainty. Future work should validate the approach under multi-bin, multi-object, and field deployment conditions.

Source: Sustainability

DOI: 10.3390/su18147498

Author: Abdalilah Alhalangy

Institution: Qassim University

Language: English

Topic: Municipal Solid Waste Management

Subfield: Waste Management and Disposal

Field: Environmental Science

Domain: Physical Sciences

SDGs: Responsible consumption and production, Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,896