Optimizing Waste Collection Efficiency by NodeMCU enabled Ultrasonic Trash Can Surveillance and ThingSpeak Dashboards

Abstract

The use of inflexible route schedules for garbage collection results in inadequate waste disposal, posing environmental risks and incurring high operational expenses, including fuel costs and landfill fees, even when the waste containers are not completely full. This study utilizes a cost-effective Internet of Things (IoT) monitoring system to facilitate dynamic routing. The aim is to enhance the efficiency and frequency of waste collection by optimizing it based on real-time fill levels, rather than following fixed cycles. The prototype employs an ultrasonic distance sensor in conjunction with a NodeMCU ESP8266 micro-controller to detect the fill level of a trash can. The collected data is then transmitted to the ThingSpeak cloud platform. Real-time visualization dashboards display live data on waste levels in different containers, providing guidance for collection scheduling. The estimated scope entails conducting circuit simulation using Proteus, optimizing PCB layout, and developing an integrated IoT prototype connected to ThingSpeak for IoT analytics. Ultimately, integrating cost-effective IoT edge sensors such as ultrasonic ranging with cloud analytics dashboards greatly enhances effectiveness, sustainability, and intelligent allocation of resources in public trash collection. This results in economic and environmental advantages by reducing landfill overflow through the digitalization of smart cities.