OTUNIYIA JENISSI CHUKWUEMEKA

Rapid urbanization and shifting consumption patterns have led to an unprecedented increase in municipal solid waste generation, posing significant environmental and public health challenges. Traditional manual waste sorting is inefficient, unhygienic, and increasingly hazardous for waste management workers. This project presents the design and fabrication of an automated, smart Waste Segregation System capable of detecting and sorting mixed waste into three distinct categories: metallic, wet/organic, and dry/plastic. The physical architecture of the system consists of a hopper-fed conveyor belt driven by a high-torque DC motor, mounted on a durable structural frame. The intelligence of the system relies on an array of sensors integrated with an Arduino Mega microcontroller. An inductive proximity sensor is utilized to identify metallic objects, while a calibrated moisture/capacitive sensor detects organic and wet matter. Items that do not trigger these sensors are classified by default as dry non-metallic waste (such as plastics or paper). Upon material identification, the microcontroller processes the signals in real time and activates a mechanical sorting mechanism—consisting of servo-controlled flaps and pneumatic actuators—to direct the waste item into its designated collection bin. Experimental testing of the fabricated prototype demonstrated a high sorting accuracy rate of approximately [Insert your percentage, e.g., 92%] with an average processing time of [Insert time, e.g., 2–4 seconds] per item. The system successfully minimizes human intervention, increases recycling efficiency, and offers a cost-effective, scalable solution for smart city waste management initiatives.