Smart Waste Bins using DCNN and Internet of Things

Waste sorting poses significant challenges because of several factors, including a lack of awareness and education about proper disposal, inadequate infrastructure and collection systems, cultural practices that discourage segregation, economic factors without financial incentives, confusion due to the absence of clear guidelines and regulations for waste sorting, and time and convenience constraints. These challenges give rise to various health issues. Improper waste disposal can result in the spread of diseases through pests and rodents. Burning or burying mixed waste releases pollutants that can lead to respiratory problems. Hazardous waste, when not correctly separated, can contaminate groundwater, and unsorted waste may pose injury risks for waste workers and scavengers, including sharp objects and hazardous materials. In our study, we present a smart waste segregation system and describe the development of an intelligent waste bin designed to categorize deposited waste into various groups according to its nature, spanning from household-level waste to municipal-level waste.. This smart waste bin employs Deep Convolutional Neural Networks (DCNN) to sort the waste and incorporates ultrasonic sensors, moisture sensors, and rotary actuators. This integration enables the efficient sorting and segregation of waste placed into the smart waste bin. Combining the DCNN with actuators and sensors enhances the effectiveness of waste sorting. The implementation of these sensors will be carried out using Arduino UNO R3 and the ESP32 Camera Module