IoT-Enabled Smart Waste Management Systems Using RFID and Sensors

Abstract

Rapid urbanization has stressed municipal solid waste management (SWM) systems, causing missed pickups, overflowing bins, high fuel consumption, and significant greenhouse gas emissions. This manuscript proposes and evaluates an IoT-enabled smart waste management system that integrates RFID-tagged containers with multi-sensor smart-bin nodes (ultrasonic fill-level, load-cell weight, tilt, temperature/gas) connected via low-power wide-area networks to edge gateways and a cloud analytics stack. Unique EPC-based RFID identities ensure asset traceability and bin–vehicle event logging, while sensors provide near–real-time fill-state telemetry. An analytics pipeline forecasts fill trajectories and dynamically solves a capacitated vehicle routing problem with time windows (VRPTW), producing on-demand collection routes that minimize distance and overflow risk. We describe a modular architecture covering hardware design, energy management, device firmware, networking, data models, and security-by-design measures.

A simulation study of a mid-size city ward (≈2 km × 2 km, 250 bins, three trucks) and an emulated 12-week operational log demonstrate reductions in route distance (≈31%), fuel use (≈32%), overflow incidents (≈62%), and collection cycle time (≈33%), alongside a packet delivery ratio above 97% and multi-year battery life projections under adaptive duty-cycling. Statistical analysis (paired tests, effect sizes) confirms improvements across key KPIs. The results suggest that combining RFID provenance with sensor-driven optimization materially improves operational efficiency, service reliability, and environmental outcomes, while creating transparent audit trails for compliance and performance-based contracting. We conclude with deployment guidance and limitations relating to connectivity heterogeneity, sensor drift, and behavior change requirements.