Implementasi Sistem Terintegrasi Deep Learning dan Firebase untuk Klasifikasi Sampah dan Kontrol Otomatis
Abstract
The SMARTBIN system was developed as a solution based on the Internet of Things (IoT) and artificial intelligence to overcome waste management problems in Indonesia, especially in automatic sorting of organic and inorganic waste. This system uses a smartphone camera to take images of trash, which are then processed using a TensorFlow-based deep learning model on the backend server. The classification results are saved in Firebase Firestore and used to control the ESP32 actuator that opens the bin lid automatically (right for organic, left for inorganic). The web interface provides real-time data visualization, including the amount of classified waste. Testing shows high classification accuracy and an average response time of under 5 seconds. This system offers great potential to support smart cities and environmental sustainability, with suggestions for improving datasets and connectivity as well as integrating plastic recycling.
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