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

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.