<![CDATA[Medical waste presents a serious threat to health and the environment if not properly managed, especially in clinical facilities that require high hygiene standards. Manual waste disposal is still commonly practiced, which increases the risk of cross-contamination and reduces operational efficiency. This research aims to design and develop an automated and hygienic SmartBin system for medical waste using Artificial Intelligence (AI) and edge computing technologies without relying on internet connectivity. The system employs distance and weight sensors controlled by an Arduino Uno R3 microcontroller, along with a local image recognition module to classify medical waste based on type. All classification and system responses are processed locally to ensure fast and independent operation. A notification feature using visual and audio indicators is included to alert staff when the bin is full or when hazardous waste is detected. Testing conducted in a simulated clinical environment demonstrated a classification accuracy rate of 92% and reduced direct human contact by up to 85%. This study concludes that the SmartBin system, powered by AI and edge computing and supported by the Arduino Uno R3, offers an effective solution for improving hygiene and safety in medical waste management.]]>
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