Smart Waste Monitoring System Using Machine Learning for IoT-enabled Smart Green Campus

The growing population worldwide has created a huge increase in the generation of waste. Due to the critical problems rising over the globe, it is a must to go towards a sustainable world. Building a green campus would help towards achieving sustainability goals. To enable a green campus to handle waste, an efficient waste monitoring system is required. The integration of Internet of Things (IoT) and Machine Learning (ML) can improve existing systems and contribute to a greener environment. This paper proposes a Smart Waste Management system, which makes use of IoT sensors such as Ultrasonic, PIR, RFID in order to track the level of waste generated by bins in the campus environment. The data captured using these sensors are analyzed using ML techniques in order to predict waste generation for the university. The predictions will eventually allow the university to allocate task to the cleaners in advance, better manage the waste and also make recycling easier. A map displaying the shortest path to follow to empty the bins is implemented to help the cleaners in their daily tasks. A prototype of this system is proposed in this paper.