Abstract
Traditional waste management system operates based on daily schedule which is highly inefficient and costly. The existence of public bins have proved its ineffectiveness in the public as people do not dispose their waste properly. With the development of Internet of Things (IoT) the traditional waste management system can be replaced with smart sensors embedded into the system to perform real time monitoring and allow for better waste management. The purpose of this project is to develop a smart waste management system using microcontroller, ultrasonic sensor, global positioning system, Wi-Fi module: ESP-01 and TensorFlow based deep learning model. Wifi module: ESP-01 and ESP-32 sends the sensor data and TensorFlow performs real time object detection and classification. Ultrasonic sensors will be embedded into waste bins to monitor the filling level of the waste. Global positioning system (GPS) module is integrated to monitor the location and real time of the bin. Wi-Fi module: ESP-01 is used to transmit data about the location, real time and filling level of the bin. This system will be of great benefits such as; cost efficiency which will be achieved by optimizing collection routes based on actual fill levels rather than fixed schedule, improved cleanliness is another benefit, real time monitoring helps prevents overflow situations by ensuring timely collections based on actual need. The waste detection capabilities will allow waste management organizations to better understand what materials are being disposed of. Challenges that can be faced are; implementation cost since some of materials are not locally available on the market and user resistance to changes on technology.