Implementasi Dan Deteksi Tong Sampah Pintar Menggunakan Esp8266 dengan Algoritma CNN - Denice; Ravellia oska amanda; Eric Pradana Nst; Jaya Bardi; Dhanny Rukmana Manday (LPPM Universitas Mulia, 2025)
Waste accumulation due to ineffective management has become a challenge in the modern era. This study designs an Internet of Things(IoT)-based smart trash bin system using ESP8266, an HC-SR04 ultrasonic sensor, and a servo motor to monitor waste volume and automatically open or close the lid. The ESP8266-CAM and a Convolutional Neural Network (CNN) model are utilized for classifying organic and inorganic waste, with data communicated to a Flutter-based mobile application via Wi-Fi. The system also integrates a GPS module and Google Maps API navigation to guide an RC car to the trash bin location. Results show the CNN model achieved a validation accuracy of 83.18%, and the system functions effectively for capacity detection and automation. This solution offers efficient household waste management, real-time monitoring, and automatic classification, helping to reduce emptying frequency, minimize physical contact, and raise environmental awareness. This research provides a foundation for further IoT development in environmental and sustainable waste management.