Abstract
The growing interest in the fish farming industry is driven by the depletion of natural fish stocks in the market. However, intensive aquaculture systems, which involve raising fish in artificial tanks and cages, can lead to challenges such as low-quality fish and increased mortality rates, depending on the species being cultivated. To address these issues and maximize yield, this paper proposes a fish quality monitoring system with automatic correction. The system focuses on monitoring and maintaining critical water quality parameters essential for fish growth, including temperature, water level, and pH level. The system comprises an Arduino connected to sensors and a web-based application for data collection and monitoring. Correction devices such as an aquarium heater, a valve, and a water pump are integrated into the system to maintain these parameters at optimal levels for fish development. To assess the system's efficiency and reliability, two fish monitoring setups were compared: one using the proposed controlled system and the other using a traditional setup. Results indicate that the controlled system increased efficiency, reduced stress on fish farmers, decreased fish mortality rates, and improved product quality compared to the traditional setup.
Reference56 articles.
1. Afifah, C. H. B. A., R. A. Rosadi, and M. R. Hafiz, “The smart monitoring and automation control system for fish aquarium based on internet of things technology,” AIP Conf. Proc., vol. 2097, no. 1, p. 030018, Apr. 2019, doi: 10.1063/1.5098193
2. P. L. Chong, Y. Y. Than, S. Ganesan, and P. Ravi, “An Overview of IoT Based Smart Home Surveillance and Control System: Challenges and Prospects,” Malaysian Journal of Science and Advanced Technology, pp. 54–66, 2022, doi: https://doi.org/10.56532/mjsat.v2iS1.121
3. Peng Lean Chong, S. Ganesan, Yin Ying Than, and P. Ravi, “Designing an Autonomous Triggering Control System via Motion Detection for IoT Based Smart Home Surveillance CCTV Camera,” Malaysian Journal of Science and Advanced Technology, pp. 80–88, Mar. 2023, doi: https://doi.org/10.56532/mjsat.v2is1.120
4. P. K. Ng, P. L. Chong, J. A. Yeow, Y. J. Ng, and R. Jeyakumar Nathan, “Ergonomic Work from Home Recommendations Using TRIZ,” in Human Factors in Engineering Manufacturing Systems, Automation, and Interactions, Boca Raton: Taylor & Francis, 2023, pp. 65–82.
5. D. W. H. Tan, P. K. Ng, E. E. M. Noor, A. Saptari, C. C. Hue, and Y. J. Ng, “Development and Usability Testing of a Finger Grip Enhancer for the Elderly,” Robotics, vol. 11, no. 1, p. 5, Dec. 2021, doi: https://doi.org/10.3390/robotics11010005
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献