Guan, Low Ming and Yakub, Fitri and Hanapiah, Ahmad Redzuan Mohd and Rahim, Muhamad Sharifuddin Abd and Azizan, Azizul and Ab Rashid, Mohd Zamzuri (2023) Water quality detection system using real time vision computing with trash collector. In: 14th IEEE Control and System Graduate Research Colloquium, ICSGRC 2023, 5 August 2023, Shah Alam.
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Abstract
The increasing pace of industrialization and population has led to an ever-increasing demand for water, accompanied by a rise in water pollution levels. While industrial growth brings economic stability to nations, it has profound consequences for environmental resources. Both renewable and non-renewable resources are exploited to manufacture industrial products, resulting in the production of non-degradable waste that is frequently discarded into water bodies. This research focuses on finding a viable solution to reduce river water pollution and promote awareness of river quality. The proposed solution involves the development of a water quality detection system that utilizes real-time vision computing and a litter collector to monitor water quality and collect floating debris on the water surface. The system is designed with a centralized microcontroller (Arduino Mega) acting as the control center, transmitting data to a cloud-based monitoring platform. It is integrated into the litter collector, equipped with a surveillance camera for safety during debris collection. The microcontroller also controls the movement of the Seabin using a radio frequency controller. Through the integration of an Arduino program, this research has achieved significant outcomes by enabling simultaneous monitoring of multiple water quality parameters and offering control capabilities through the frequency controller.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Detection system, IoT, Real time, Trash collector, Water quality |
| Divisions: | Faculty Of Electrical Technology And Engineering |
| Depositing User: | Anis Suraya Nordin |
| Date Deposited: | 17 Oct 2024 12:22 |
| Last Modified: | 17 Oct 2024 12:22 |
| URI: | http://eprints.utem.edu.my/id/eprint/28040 |
| Statistic Details: | View Download Statistic |
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