Author: Dimas Akmarul Putera ; Ansarullah Lawi ; Filmada Ocky Saputra ; Sri Handayani ; Yun Arifathu Fatimahl ; Ivan Muhammad Reza ; Sholikun ; Zainal Arifin Hasibuan ; Alvendo Wahyu Aranski
DOI: 10.1109/ICIC64337.2024.10957619
Abstract
Effective and efficient waste management system is a significant challenge in coastal areas. This research proposes the development of innovative model for waste management system using IoT and machine learning. The system consists of hardware such as cameras and image sensors installed in coastal locations to monitor the volume and types of waste. The image data collected from these devices is stored and analyzed using image processing techniques. The YOLO (You Only Look Once) algorithm is used to identify and classify the types of waste. The identified data is then used to train a machine learning model, which allows for the prediction of future waste volume and types. These predictions are used to optimize waste collection schedules, reduce operational costs, plan the types of waste processing, and minimize environmental impact. With this holistic approach, the system is expected to enhance the efficiency and sustainability of waste management, providing an innovative solution to waste management issues in coastal areas. © 2024 IEEE.
Author keywords
Environment; Image Processing; IoT; Machine Learning; Waste Management
This article can be accessed at: https://www.scopus.com/pages/publications/105004578932?
