Aquaculture monitoring system using machine learning
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Author |
Polepalli Tarun Vijay Kumar, K. P. Siddhardha Varma Mudunuri, Sathish K., Ravi Kumar C. V. and Ashish P.
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e-ISSN |
1819-6608 |
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On Pages
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1700-1706
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Volume No. |
18
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Issue No. |
14
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Issue Date |
September 30, 2023
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DOI |
https://doi.org/10.59018/0723211
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Keywords |
Internet of Things, machine learning, aquaculture farming, Arduino Uno, node MCU, ESP8266.
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Abstract
Aquaculture is the farming of aquatic creatures for food and other purposes. It is a growing industry that provides
a significant amount of the world's seafood. Aquaculture management regulates and oversees these farms to ensure that
they are operating effectively and sustainably. Machine learning and IoT can play a significant role in aquaculture
management. Machine learning can be used to monitor and optimize farm conditions in real time, while IoT can be used to
monitor and manage farms remotely. These technologies can help improve yields, reduce costs, and improve sustainability.
In this paper, we propose an aquaculture management system using machine learning and IoT for fish and shrimp farms.
The system monitors the environment and collects data from sensors placed on the farm. The data is processed using
machine learning algorithms to identify patterns and predict problems. The system provides information on the optimum
conditions for farming and the best time to harvest. Monitoring various things like temperature and pH and providing feed
at the right time is important, which plays an important role in the output of the final crop.
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