SENSOR BASED AUTOMATED SMART WASTE SEGREGATION SYSTEM

Abstract

Rapid urban population growth has greatly increased the amount of solid garbage produced, posing major problems for public health, environmental sustainability, and effective trash management. Traditional trash segregation techniques, which mostly rely on human sorting, are frequently ineffective, time-consuming, labor-intensive, and put workers in dangerous situations. This study suggests designing and implementing an intelligent sensor-based automated waste segregation system to address these problems and enhance waste management procedures' precision, effectiveness, and hygienic conditions. The suggested system makes use of a variety of cutting-edge sensing technologies, such as infrared or ultrasonic sensors to detect the presence and location of waste products, moisture sensors to identify biodegradable (wet) trash, and inductive sensors to detect metallic elements. A microcontroller that serves as the central control unit processes the real-time data that these sensors continuously collect. Based on programmed decision-making algorithms, the system classifies the waste and activates actuators such as servo motors to direct materials into separate compartments designated for wet, dry, and metallic waste. Additionally, real-time monitoring of bin status, system performance, and garbage levels is made possible by the integration of Internet of Things (IoT) technology, which helps smart city frameworks make data-driven decisions and improve collection schedules. This function improves the   sustainability   and   overall   efficiency   of   the   system. In summary, the suggested automated trash segregation system provides an affordable, scalable, 
and eco-friendly solution that tackles contemporary waste management issues while encouraging 
resource efficiency, cleanliness, and sustainable urban growth.