Optimizing waste management with integrated AIoT, edge computing, and LoRaWAN communication technologies

IF 6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Internet of Things Pub Date : 2025-03-28 DOI:10.1016/j.iot.2025.101546

Abdelaziz Daas , Bilal Sari , Fouzi Semchedine , Mourad Amad

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引用次数: 0

Abstract

This work presents Smart EcoRecycler Manager, an integrated waste management system designed to address inefficiencies in traditional recycling through automation and user engagement. The system combines a smart bin with AI-driven waste sorting, low-power wireless communication (LoRaWAN), and a user-friendly mobile app to incentivize recycling. Key innovations include: AI-powered waste classification achieving 99% accuracy for plastic and metal sorting, enabled by machine learning on low-cost edge devices (ESP32-CAM), Real-time optimization of waste collection routes, reducing operational costs compared to conventional methods, A gamified rewards system that boosts user participation through redeemable points, addressing low recycling rates.

The system uniquely integrates edge computing for real-time processing, LoRaWAN for long-range communication, and cloud platforms (Firebase) for scalable data management. Performance testing demonstrates significant improvements in waste segregation accuracy, cost efficiency, and user engagement. By combining these features, our solution addresses critical gaps in existing systems, such as limited scalability, high energy consumption, and poor user incentives. This work advances smart waste management by providing a practical, low-cost framework suitable for urban and remote areas alike, with measurable environmental and economic benefits.

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通过集成AIoT、边缘计算和LoRaWAN通信技术优化废物管理

这项工作提出了智能生态回收管理器，这是一个综合废物管理系统，旨在通过自动化和用户参与来解决传统回收效率低下的问题。该系统将智能垃圾箱与人工智能驱动的垃圾分类、低功耗无线通信（LoRaWAN）和用户友好的移动应用程序相结合，以激励回收。主要创新包括：通过低成本边缘设备（ESP32-CAM）上的机器学习，人工智能垃圾分类的塑料和金属分类准确率达到99%；垃圾收集路线的实时优化，与传统方法相比，降低了运营成本；通过可兑换积分提高用户参与度的游戏化奖励系统，解决了低回收率问题。该系统独特地集成了用于实时处理的边缘计算、用于远程通信的LoRaWAN和用于可扩展数据管理的云平台（Firebase）。性能测试证明了在废物分离准确性、成本效率和用户参与度方面的显著改进。通过结合这些特性，我们的解决方案解决了现有系统中的关键缺陷，例如有限的可伸缩性、高能耗和较差的用户激励。这项工作通过提供适用于城市和偏远地区的实用、低成本框架来推进智能废物管理，并具有可衡量的环境和经济效益。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Internet of Things Multiple-

CiteScore

3.60

自引率

5.10%

发文量

115

审稿时长

37 days

期刊介绍： Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.