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IoT-Based Smart Irrigation System in Aquaponics Using Ensemble Machine Learning

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Soft Computing and Signal Processing ( ICSCSP 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 840))

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Abstract

Aquaponics is a sustainable farming method that combines aquaculture and hydroponics to grow plants and fish in a closed-loop system. In this research paper, an irrigation system based on aquaponics is proposed, which uses real-time sensor data from the fish tank and crop soil to improve the efficiency of the system. The system is designed to make informed decisions about crop irrigation needs by visualizing the data for analytics. The study compares the accuracy of three classification algorithms, KNN, Naive Bayes, and ANN, to decide when to irrigate the soil based on real-time sensor data. The proposed irrigation system includes two sets of sensors, one for the fish tank and the other for the crop soil, which is processed by an Arduino board and sent to Adafruit’s cloud platform for visualization and analytics. This cloud-based platform allows easy access to real-time data, enabling efficient monitoring and control of the irrigation system. Additionally, the study visualizes the results obtained from using regular water and lake water in the aquaponics system.

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References

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Author information

Authors and Affiliations

  1. Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Chennai, India

    Aishani Singh & A. Arulmurugan

  2. Department of Networking and Communications, SRM Institute of Science and Technology, Kattankulathur, Chennai, India

    Dhruv Bajaj & M. Safa

  3. Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan

    A. John

Authors
  1. Aishani Singh
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  2. Dhruv Bajaj
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  3. M. Safa
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  4. A. Arulmurugan
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  5. A. John
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Corresponding author

Correspondence to M. Safa .

Editor information

Editors and Affiliations

  1. Faculty of Science and Technology, International Institute of Advance Technology (ICATSUC), Sarawak, Malaysia

    Hushairi Zen

  2. Department of Computer Science, University of South Australia, Adelaide, SA, Australia

    Naga M. Dasari

  3. Department of Electronics and Communication Engineering, Malla Reddy Engineering College for Women, Secunderabad, India

    Y. Madhavee Latha

  4. Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India

    S. Srinivasa Rao

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Singh, A., Bajaj, D., Safa, M., Arulmurugan, A., John, A. (2024). IoT-Based Smart Irrigation System in Aquaponics Using Ensemble Machine Learning. In: Zen, H., Dasari, N.M., Latha, Y.M., Rao, S.S. (eds) Soft Computing and Signal Processing. ICSCSP 2023. Lecture Notes in Networks and Systems, vol 840. Springer, Singapore. https://doi.org/10.1007/978-981-99-8451-0_17

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