Mustafovski, Rexhep and Petrovski, Aleksandar (2024) Intelligent Waste Management System (IWMS): Deep Learning Enabled Sorting with Bin-Fill Sensor Integration. In: Environmental Protection and Disaster Risks (EnviroRisks 2024), 16 Nov 2024, Sofia, Bulgaria.
Full text not available from this repository. (Request a copy)Abstract
This research introduces an innovative waste management system leveraging deep learning algorithms in conjunction with Raspberry Pi 3 and intelligent bins, enhanced by a bin-fill sensor. The system offers a comprehensive solution for efficient waste sorting and bin management. Utilizing cameras connected to the Raspberry Pi, the deep learning model accurately identifies various types of garbage in real-time. Upon classification, the corresponding intelligent bin's lid is automatically opened through actuators controlled by the Raspberry Pi. Additionally, a bin-fill sensor integrated into each bin detects the level of waste accumulation, providing crucial data for optimizing waste collection schedules. This multi-faceted approach aims to revolutionize waste management processes, facilitating automated sorting, and timely waste collection, thereby contributing to sustainable environmental practices. The project underscores the synergy between deep learning, edge computing, and sensor technology in developing intelligent waste management solutions.
Item Type: | Conference or Workshop Item (Paper) |
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Subjects: | Engineering and Technology > Other engineering and technologies |
Divisions: | Military Academy |
Depositing User: | Redzep Mustafovski |
Date Deposited: | 16 Sep 2025 08:18 |
Last Modified: | 16 Sep 2025 08:18 |
URI: | https://eprints.ugd.edu.mk/id/eprint/36401 |