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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Smart waste management and classification system using advanced IoT and AI technologies.

Abdullah Alourani¹, M Usman Ashraf², Mohammed Aloraini³

¹Department of Management Information Systems, College of Business and Economics, Qassim University, Buraydah, Saudi Arabia.

Peerj. Computer Science

|June 26, 2025

Summary

This study introduces an intelligent solid waste management system (iSSWMs) using AI and IoT for smart collection and segregation of plastic, glass, and metal waste. The system achieved 99.7% accuracy in segregating recyclable materials.

Keywords:

Artificial intelligence Cloud manufacturing service Industrial Internet of Things Intelligent manufacturing system Machine learning Solid waste recycling Waste management system

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Area of Science:

Environmental Science
Computer Science
Engineering

Background:

Municipal solid waste management is a critical global challenge.
Ineffective waste segregation hinders recycling and resource recovery.
Emerging technologies offer solutions for efficient waste management.

Purpose of the Study:

To develop an intelligent and smart solid waste management system (iSSWMs).
To enable smart collection and segregation of recyclable materials (plastic, glass, metal).
To contribute to environmental protection and public health goals.

Main Methods:

Phase 1: Smart waste collection using IoT-enabled bins and a mobile application.
Phase 2: Deep learning model (VGG-19) for automated waste segregation.
Integration of artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT).

Main Results:

The iSSWMs effectively integrates smart collection and segregation.
The VGG-19 model achieved 99.7% accuracy in segregating plastic, glass, and metal.
The system demonstrates high efficiency in identifying and separating recyclable waste.

Conclusions:

iSSWMs offers a promising framework for modernizing solid waste management.
The integration of AI, ML, and IoT enhances recycling efficiency.
This approach contributes to a cleaner environment and supports broader public health objectives.