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Cost-effective IoT-based intelligent irrigation system

Author

Listed:
  • C. S. Anagha

    (Birla Institute of Technology and Science Pilani)

  • Pranav M. Pawar

    (Birla Institute of Technology and Science Pilani)

  • P. S. Tamizharasan

    (Birla Institute of Technology and Science Pilani)

Abstract

Agriculture contributes to the growth of human civilization. An adequate amount of water (irrigation) is needed for healthy crops and to increase productivity. Water scarcity is a major problem the world faces, where agriculture consumes a significant portion of freshwater. Many researchers concentrate on imparting intelligence in irrigation systems using machine learning (ML) in recent days. With the emergence of Internet of Things (IoT) technology, devices can communicate with each other. It makes systems like IoT and ML a successful solution for precision agriculture to reduce human intervention in plant irrigation. The paper presented a detailed comparative review of state-of-the-art work in the intelligent automated irrigation system, and contributed the IoT based cost-effective intelligent irrigation system. The developed system uses temperature, soil moisture, humidity, and weather forecast data to take intelligent decisions to automate irrigation using an ML algorithm. The proposed system shows 99.6% accuracy for the accurate prediction of soil moisture as compared with state-of-the-art. The proposed system is also cost-efficient in terms of time (by reducing the time require for training a model), and money (by saving power and human labour requirement).

Suggested Citation

  • C. S. Anagha & Pranav M. Pawar & P. S. Tamizharasan, 2023. "Cost-effective IoT-based intelligent irrigation system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 263-274, March.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:1:d:10.1007_s13198-023-01854-y
    DOI: 10.1007/s13198-023-01854-y
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    References listed on IDEAS

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    1. Mota, Margarida & Marques, Tiago & Pinto, Teresa & Raimundo, Fernando & Borges, António & Caço, João & Gomes-Laranjo, José, 2018. "Relating plant and soil water content to encourage smart watering in chestnut trees," Agricultural Water Management, Elsevier, vol. 203(C), pages 30-36.
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