Assessing Soil Nutrients Through Iot for Enhanced Farming And Agricultural Intelligence

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Year : April 4, 2024 at 5:55 pm | [if 1553 equals=””] Volume :12 [else] Volume :12[/if 1553] | [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] : 01 | Page : –

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    Titus George, G. Soniya Priyatharsini

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  1. Student, Associate Professor, Department of CSE, SRM INSTITUTE OF SCIENCE AND TECHNOLOGY, Ramapuram, Chennai, Department of CSE, Dr. MGR Educational and Research university, Maduravoyal, Chennai, Tamil Nadu, Tamil Nadu, India, India
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Abstract

nSoil fertility is of paramount importance in agriculture, as it directly impacts the capacity of plants to flourish and develop. Recent advancements in technology, such as soil sensors and Arduino, offer effective means to assess soil nutrients. Key nutrients for agriculture, including nitrogen, phosphorous, and potassium, are vital for plant development and are considered primary contributors to soil fertility. Monitoring these nutrients enables farmers to gauge the specific needs of the soil and determine the appropriate amount to enhance fertility. By utilizing proposed Nitrogen Phosphorous Potassium (NPK) Sensors, this method facilitates the rapid and accurate measurement of soil fertility. While various methods exist for assessing soil nutrients, the appeal of NPK sensors lies in their cost- effectiveness and practicality. Nitrogen, potassium, and phosphorus are very well-known and vital minerals for plant growth. Correct ratios of these minerals boost plant growth but due to less scientific knowledge farmers, use these minerals mindlessly which results in wastage of these minerals and this also results in pollution. IoT can give precise information on how much nutrients are really necessary. This paper explores the analysis and comparison of soil nutrient levels through the application of the kernel density estimation algorithm and machine learning approaches, providing valuable insights into soil health for informed agricultural practices.

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Keywords: Soil nutrients, NPK Sensor, machine learning, Kernel density, Sensor

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Research & Reviews: A Journal of Embedded System & Applications(rrjoesa)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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How to cite this article: Titus George, G. Soniya Priyatharsini Assessing Soil Nutrients Through Iot for Enhanced Farming And Agricultural Intelligence rrjoesa April 4, 2024; 12:-

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How to cite this URL: Titus George, G. Soniya Priyatharsini Assessing Soil Nutrients Through Iot for Enhanced Farming And Agricultural Intelligence rrjoesa April 4, 2024 {cited April 4, 2024};12:-. Available from: https://journals.stmjournals.com/rrjoesa/article=April 4, 2024/view=0

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References

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[1] Madhumathi, R., T. Arumuganathan, and R. Shruthi. & Soil NPK and Moisture analysis using Wireless Sensor Networks.& 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2020.
[2] Muhammed Ayaz,Mohammad Ammad Uddin, Zubair Sharif, AliMansour, El-Hadi,M.Aggoune, “Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk”IEEE ,2019,Vol.7,129551-129583.
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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Review Article

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Volume 12
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 01
Received March 18, 2024
Accepted March 27, 2024
Published April 4, 2024

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