Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/20232
Title: IOT Application: Fish Farm Monitoring by Controlling Water Quality in Ponds and Tanks
Authors: WAN NUR QISTINA BINTI WAN SHUKRY
Bachelor of Engineering Technology (Hons.) i n Medical Electronics
Issue Date: 6-Sep-2018
Abstract: The water quality monitoring system is important especially in aquaculture industry for example in fish farm, to ensure that the water quality is maintains at the optimum range to prevent a fish kills caused by the poor water quality. This problem will lead to a huge loss to the affected fish farmers. A water quality monitoring system consist of a dissolved oxygen sensor, pH sensor and water temperature sensor using CC3200 Launchpad as the microcontroller, integrated with Internet of Things (IOT) platform is set up to enable the real-time remote water monitoring system. The system is designed to efficiently monitor the water quality in fresh-water fish farm, specifically the water parameters suitable for the catfish habitat. Instead of testing the system in the real catfish farm, it is tested using a water that is simulated to the water quality for the catfish habitat. The output from the sensors is processed by the microcontroller and transmitted to the cloud server via Wi-Fi. As the system is integrated with IOT platform, this feature enables the user to easily monitor the water quality remotely on the user interface by accessing the specific Internet Protocol (IP) address on their portable electronics devices such as smartphone, laptop and others. The water quality parameters are successfully monitored and analyzed using the IOT platform integrated monitoring system which produced a real-time data to the user. Hence, it proves that the application of the IOT monitoring system improves the operation in fish farms in terms of maintaining the water quality in optimal condition.
Description: Top 20
URI: http://ir.unikl.edu.my/jspui/handle/123456789/20232
Appears in Collections:Final Year Project - UniKL BMI



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