An Edge-Enabled Multi-Sensor IoT Framework for Real-Time Smart Waste Monitoring Using Raspberry Pi Pico W and Cloud Data Management

Abstract

The rapid rise of urban populations and the production of municipal solid waste has led to the increasing occurrence of overflowing waste bins, inefficient fixed-time collection, dangerous gas accumulation, and a lack of access to real-time waste information. Current low-cost smart trash monitoring systems are mostly confined to single-sensor systems, simple fill-level detection, limited edge processing, lack of cloud integration and scalability to multi-bin systems. The design and development of an edge-enabled Internet of Things (IoT) smart trash monitoring platform using a Raspberry Pi Pico W for real-time multi-sensor data collecting, local processing, automated operation, and cloud-based data management is described in this research. The suggested system consists of an infrared proximity sensor to identify the user, a servo motor to automatically operate the lid, a metal detection module to identify metallic waste locally, an ultrasonic sensor to measure the fill level of the waste, a gas sensor to monitor gaseous conditions, and a moisture sensor to measure the moisture of the waste. The main edge computing node is the Raspberry Pi Pico W, responsible for sensor collection, local data processing, parameter calculation, time synchronization, creation of JSON packets, and wireless transfer to the cloud. The processed waste data is communicated by Wi-Fi using REST-based communication and saved in an organized Supabase cloud database. The exclusive device identities and synced timestamps agree for unified data administration and ascendable process of numerous smart-bin nodes. The research legalizes the stable assembly of multi-sensor data, the timely automatic lid initial and finishing, local detection of metal substances, stable wireless communication, fruitful synchronization with the cloud based on REST, and the organized storing of real-time excess records. The created platform offers a low-cost, flexible, and scalable hardware and cloud organization for smart city intelligent waste management applications.