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Irrigation intelligence—enabling a cloud-based Internet of Things approach for enhanced water management in agriculture

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Abstract

Advanced sensor technology, especially those that incorporate artificial intelligence (AI), has been recognized as increasingly important in various contemporary applications, including navigation, automation, water under imaging, environmental monitoring, and robotics. Data-driven decision-making and higher efficiency have enabled more excellent infrastructure thanks to integrating AI with sensors. The agricultural sector is one such area that has seen significant promise from this technology using the Internet of Things (IoT) capabilities. This paper describes an intelligent system for monitoring and analyzing agricultural environmental conditions, including weather, soil, and crop health, that uses internet-connected sensors and equipment. This work makes two significant contributions. It first makes it possible to use sensors linked to the IoT to accurately monitor the environment remotely. Gathering and analyzing data over time may give us valuable insights into daily fluctuations and long-term patterns. The second benefit of AI integration is the remote control; it provides for essential activities like irrigation, pest management, and disease detection. The technology can optimize water usage by tracking plant development and health and adjusting watering schedules accordingly. Intelligent Control Systems (Matlab/Simulink Ver. 2022b) use a hybrid controller that combines fuzzy logic with standard PID control to get high-efficiency performance from water pumps. In addition to monitoring crops, smart cameras allow farmers to make real-time adjustments based on soil moisture and plant needs. Potentially revolutionizing contemporary agriculture, this revolutionary approach might boost production, sustainability, and efficiency.

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Authors and Affiliations

  1. Department of Electrical Engineering, College of Engineering, University of Anbar, Anbar, Iraq

    Yousif Al Mashhadany & Hamid R. Alsanad

  2. College of Engineering Technology, Al-Kitab University, r, Kirkuk, Iraq

    Mohanad A. Al-Askari

  3. Information Systems Department/College of Computer Science and Information Technology, University of Anbar, Anbar, Iraq

    Sameer Algburi

  4. Department of Electrical, Electronic and Systems Engineering, cFaculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM, 43600, Bangi, Malaysia

    Bakr Ahmed Taha

Authors
  1. Yousif Al Mashhadany
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  2. Hamid R. Alsanad
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  3. Mohanad A. Al-Askari
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  4. Sameer Algburi
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  5. Bakr Ahmed Taha
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Contributions

Y.A, wrote the main manuscript text, Conceptualization and Methodology, H. R. A , and M.A. A , investigation, Conceptualization and methodology, S.A and B. A.T, Review & Editing. All authors have reviewed and accepted the published version of the manuscript.

Corresponding author

Correspondence to Yousif Al Mashhadany.

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Al Mashhadany, Y., Alsanad, H.R., Al-Askari, M.A. et al. Irrigation intelligence—enabling a cloud-based Internet of Things approach for enhanced water management in agriculture. Environ Monit Assess 196, 438 (2024). https://doi.org/10.1007/s10661-024-12606-1

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