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Multiparameter optimization system with DCNN in precision agriculture for advanced irrigation planning and scheduling based on soil moisture estimation

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Abstract

Agriculture is a distinct sector of a country’s economy. In recent years, new patterns have evolved in the agricultural industry. In conjunction with sensor scaling down and precision agriculture, the field of remote sensor networks, such as the wireless sensor network (WSN), was developed. Its major purpose is to make horticultural operations simpler to identify, assess, and manage. This paper uses the proposed DCNN to predict soil moisture and plan irrigation for precision agriculture farmers to reduce water consumption used for cultivation and increase production yield by comparing water content during various stages of plant growth and integrating IoT applications into agriculture. It also optimizes the water level for future irrigation decisions to maintain crop growth and water stability. The data must be served and stored in the form of a grid view, according to Apriori and GRU (gated recurrent unit). Using numerous sensor and parameter modelling methodologies, this system assists in the prediction of irrigation planning based on irrigation needs. The predicted parameters include soil moisture, temperature, and humidity. This observed experimental data supports smart irrigation in crop production with a high yield and little water use. DCNN has a 98.5% experimental result accuracy rate and the MSE value is predicted in DCNN 99.25% of the time.

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All data generated or analyzed during this study are included in the manuscript.

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Authors and Affiliations

  1. Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, 627012, India

    Parasuraman Kumar & Anandan Udayakumar

  2. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    Anbarasan Anbarasa Kumar

  3. Department of Statistics, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, 627012, India

    Kaliaperumal Senthamarai Kannan

  4. Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, 627012, India

    Nallaperumal Krishnan

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  1. Parasuraman Kumar
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  2. Anandan Udayakumar
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  3. Anbarasan Anbarasa Kumar
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  4. Kaliaperumal Senthamarai Kannan
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Contributions

Parasuraman Kumar and Anandan Udayakumar are responsible for designing the framework, analyzing the performance, validating the results, and writing the article. Anbarasan Anbarasa Kumar, Kaliaperumal Senthamarai Kannan, and Nallaperumal Krishnan are responsible for collecting the information required for the framework, provision of software, critical review, and administering the process.

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Correspondence to Anandan Udayakumar.

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Kumar, P., Udayakumar, A., Anbarasa Kumar, A. et al. Multiparameter optimization system with DCNN in precision agriculture for advanced irrigation planning and scheduling based on soil moisture estimation. Environ Monit Assess 195, 13 (2023). https://doi.org/10.1007/s10661-022-10529-3

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