IOT Based Garbage Monitoring System

Abstract

Intelligent solutions that maximize collection, improve safety, and lessen environmental impact are required to meet the growing need for effective, sustainable waste management in urban and semi-urban settings. The design and implementation of an Internet of Things-based garbage monitoring system that uses cloud computing, real-time data collecting, and sensor integration to expedite the waste collection process is presented in this study. The system improves worker safety and environmental awareness by using gas sensors (MQ-135) to detect dangerous gases like ammonia and methane and ultrasonic sensors to track bin fill levels. GPS modules offer accurate location tracking, and a NodeMCU microcontroller gathers and sends this data over Wi-Fi to cloud platforms (ThingSpeak and Virtuino). Dynamic route optimization is made possible by real-time warnings and an intuitive dashboard, which lowers needless travel, operating expenses. GPS modules offer accurate location tracking, and a NodeMCU microcontroller gathers and sends this data over Wi-Fi to cloud platforms (ThingSpeak and Virtuino). Dynamic route optimization is made possible by real-time notifications and an intuitive dashboard, which lowers greenhouse gas emissions, operational expenses, and pointless travel. The suggested system is flexible and scalable for use in a variety of settings, such as public institutions, residential complexes, industrial zones, and towns. The solution supports the objectives of smart cities and makes the urban ecosystem cleaner, safer, and more responsive by integrating data-driven decision-making.