IoT-Based Intelligent Trash Can Monitoring System for Scenic Areas Using Multi-Sensor Detection and LoRa Communication

Abstract

Traditional manual inspection of trash cans in scenic areas often faces low efficiency, delayed anomaly detection, and high maintenance costs due to the wide distribution of bins and complex terrain. To address these issues, this paper designs an intelligent trash can monitoring system based on the Internet of Things (IoT) that integrates multi-sensor fusion and low-power wide-area communication technology. The proposed system employs ultrasonic and pressure sensors to monitor the overflow state in real time, while temperature and orientation sensors detect fire and tilting anomalies. The STM32F103 microcontroller serves as the main control unit, responsible for data acquisition and system coordination. The collected data are transmitted via a LoRa communication module, enabling long-distance and low-power data exchange across mountainous scenic environments. The software design includes real-time sensing, data fusion, and event-triggered communication to enhance energy efficiency and response speed. Experimental validation demonstrates that the system can accurately detect overflow, fire, and tilt states, providing reliable real-time monitoring and alerting. This solution significantly improves the management efficiency of waste collection in scenic areas and supports the sustainable development of smart tourism infrastructure.