• Mohammed Moizuddin Abdulla
• Malkari Sravani

Rapid population growth around the world has resulted in the improper management of trash in many nations, which has led to a number of health problems and environmental damage. Only once or twice a week are collected by the waste-collection vehicles. The garbage in the trashcan gets dispersed across the streets as a result of poor waste collection procedures. As a result, an effective solution for smart and effective waste management combining machine learning (ML) techniques and the Internet of things (IoT) is suggested in order to overcome this dilemma. The authors' suggested approach makes use of a moisture sensor, an ultrasonic sensor, and an Arduino UNO microcontroller. To calculate the trash index of a particular dumping site, image processing will be applied. Additionally, a hardware prototype for the suggested framework will be created. As a result, the proposed approach to effective waste management achieves the goal of creating clean, pollution-free cities.

Arduino UNO, Dustbin, Internet of Things, Machine Learning, Smart Waste Management System, Smart cities.

"IoT Enabled Smart Waste Management System using Machine Learning Techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.b217-b221, September-2022, Available :http://www.jetir.org/papers/JETIR2209128.pdf

"IoT Enabled Smart Waste Management System using Machine Learning Techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppb217-b221, September-2022, Available at : http://www.jetir.org/papers/JETIR2209128.pdf