AI Powered Medical Waste Management with IoT

Abstract

Effective medical waste management is essential for reducing environmental and public health risks. Traditional manual sorting is inefficient and error-prone. This paper introduces SmartMedWaste, an end-to-end system leveraging IoT and AI to enhance medical waste management. Using NodeMCU ESP8266, ultrasonic sensors, IR sensors, and robotic arms, the system captures and classifies waste images, directing robotic arms for precise segregation. This integration improves accuracy, operational efficiency, and regulatory compliance while promoting sustainable practices in healthcare facilities. Key contributions include an automated waste management framework and the implementation of an advanced ResNeXt architecture based deep learning model for efficient waste segregation. The ResNeXt based deep learning model, integrated into the system, classifies the medical waste with an impressive accuracy of $\mathbf{9 7. 9 3 \%}$.