The smart monitoring and automation control system for fish aquarium based on internet of things technology

Afifah, Yasmine; Hermanu, B A Chico; Rosadi, Rizal Abdulrozaq; Hafiz, Mohammad

doi:10.1063/1.5098193

Cited by 11 publications

(4 citation statements)

References 2 publications

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“…The next research suggested smart monitoring with IoT technology to provide an automated process to retrieve and transfer the data to the breeders. The proposed model of the research successfully measures the parameters along with the automation process through wireless [10]. Another study also suggested an IoT-based aquaculture monitoring and control by adding several sensors for an accurate reading.…”

Section: Introductionmentioning

confidence: 98%

Internet of Things-based Water pH Level Monitoring for Arowana Cultivation

Daru

Christanto

Vydia

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The Arowana fish cultivation is a special cultivation that grows decorative fish instead of consumption. Unlike consumption fish, Arowana fish require a strict water pH level to live healthily. Hence, the cultivator must carefully maintain the water to prevent high acidity levels in the aquarium. A high acid level in the water may cause severe disease or death to Arowana. However, detecting acidity levels in the water required a particular tool, such as litmus paper. Litmus paper provided accurate acid detection by color indication. A strip of litmus paper is required for every aquarium to detect the acidity level. Buying many litmus papers may increase the unnecessary cost of cultivation. This research proposed acidity level monitoring by implementing Internet of Things technology to allow automation and remote monitoring. According to the evaluation result, the proposed model is capable of detecting the state of the acidity level with an accuracy of up to 100%. Besides that, the detection range of the proposed model is almost identical to a pH meter with a percentage error of less than 1% in many acidity levels.

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Section: Introductionmentioning

confidence: 98%

Internet of Things-based Water pH Level Monitoring for Arowana Cultivation

Daru

Christanto

Vydia

2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…Testing and measurements of water are carried out in a way that restricts the data to the precise moment that it was obtained. More advanced techniques include computers and sensors that can store data in memory for subsequent retrieval and analysis by technicians [1]. Currently, water monitoring systems use two different types of control techniques.…”

Section: Introductionmentioning

confidence: 99%

Improving Fish Quality and Yield: An Automated Monitoring System for Intensive Aquaculture

Anne Dashini Kannan,

Chong Peng Lean,

Chen

et al. 2024

Malaysian J. Sci. Adv. Tech.

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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.

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“…While [10]creates a system that has a temperature sensor and a live streaming process. Meanwhile, [11] has created a method that can detect fish's shape, length, and pattern.Inspired by other Automatic Smart Feeders.…”

Section: Introductionmentioning

confidence: 99%

Cultivation of Flowerhorn Species in Search of Superior Quality Seeds using IoT and Open CV

Ngarianto¹,

Purwanto²,

Andrean³

2022

IJETAE

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The Flowerhorn is a type of ornamental fish that many fish hobbyists are attracted to because of the uniqueness of its head and the beauty of the color of the scales. And has a high selling value. The treatment requires equipment: An aquarium, oxygen aerator pump, water filter, water pH meter, UV lamp, and fish feed. In keeping Flowerhorn fish in the aquarium, you must pay attention to the acidity of the water (pH) and the feeding schedule according to the needs of the Flowerhorn fish age.Flowerhorn fish is one of the most popular ornamental fish. However, it is a little difficult to find superior seeds. To get superior quality Flowerhorn fish, IoT technology is needed to monitor the development of Flowerhorn fish using a Deep Learning approach, namely the Convex Hull Algorithms from OpenCV. OpenCV is a method that can detect objects using a camera, and the results of the image storage will be saved to a computer database that can process objects that have been tracked. Using this IoT and OpenCV system, you can feed fish, adjust water pH automatically, and identify all Flowerhorn fish in the aquarium using a camera. And can distinguish the color pattern and size of the forehead of the ideal Flowerhorn fish. So, Flowerhorn fish develop optimally and have a high selling value.

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The smart monitoring and automation control system for fish aquarium based on internet of things technology

Cited by 11 publications

References 2 publications

Internet of Things-based Water pH Level Monitoring for Arowana Cultivation

Internet of Things-based Water pH Level Monitoring for Arowana Cultivation

Improving Fish Quality and Yield: An Automated Monitoring System for Intensive Aquaculture

Cultivation of Flowerhorn Species in Search of Superior Quality Seeds using IoT and Open CV

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