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Publication: IIP Proceedings Year: 2022, Month: November Page No: 119-124, ISSN/ISBN: 978-93-95632-81-2, DOI/Link: https://rsquarel.org/assets/docupload/rsl2023F9D55D6938C5E38.pdf
MACHINE LEARNING BASED NUTRIENT OPTIMIZATION FOR SMART AQUAPONICS SYSTEM
Area/Stream: Artificial Intelligence, Authors: Prof. Ragini Sharma Keywords: IOT, fishes, plants, machinelearning, sensor, growth, nutrients Book Name /series: Futuristic Trends in Artificial Intelligence, Volume 2, Book 17, Part 5, Chapter1Publication: IIP Proceedings Year: 2022, Month: November Page No: 119-124, ISSN/ISBN: 978-93-95632-81-2, DOI/Link: https://rsquarel.org/assets/docupload/rsl2023F9D55D6938C5E38.pdf
Abstract:
Agriculture is considered as the primary occupation by a vast population of India. Considering the population of India, maximum yield of crops is the major requirement, which in turn requires a vast land with appropriate soil nutrients. The proposed aquaponics system provides a soil less solution of growing crops in less space. The IOT enabled automatic system monitors and maintains the temperature, humidity, pH and NPK nutrients in the tank water. The system automatically controls the operation of lights and fans depending upon the readings of temperature and humidity sensors. The concentration of nutrients in the biofilter are monitored through pH sensors. If concentration is high, then the water is diluted or else nutrients are added in the biofilter. The complete system can be monitored through a mobile app. The readings from various sensors were taken at particular interval of time and considered as a dataset for machine learning model for monitoring the growth of the plant. The amount of ammonium and nitrates were considered to be the prime parameters for predicting the growth of plant through machine learning models. The proposed system can be considered as an automatic soil less, temperature controlled agriculture solution for growing crop in limited area.
Cite this: Prof. Ragini Sharma,"MACHINE LEARNING BASED NUTRIENT OPTIMIZATION FOR SMART AQUAPONICS SYSTEM", Futuristic Trends in Artificial Intelligence, Volume 2, Book 17, Part 5, Chapter1 , November, 2022, 119-124, 978-93-95632-81-2, https://rsquarel.org/assets/docupload/rsl2023F9D55D6938C5E38.pdf
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