Assessing Soil Nutrients Through Iot for Enhanced Farming And Agricultural Intelligence

Year : 2024 | Volume :12 | Issue : 01 | Page : –
By

    Titus George

  1. G. Soniya Priyatharsini

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

Abstract

Soil 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.

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

[This article belongs to Research & Reviews: A Journal of Embedded System & Applications(rrjoesa)]

How to cite this article: Titus George, G. Soniya Priyatharsini.Assessing Soil Nutrients Through Iot for Enhanced Farming And Agricultural Intelligence.Research & Reviews: A Journal of Embedded System & Applications.2024; 12(01):-.
How to cite this URL: Titus George, G. Soniya Priyatharsini , Assessing Soil Nutrients Through Iot for Enhanced Farming And Agricultural Intelligence rrjoesa 2024 {cited 2024 Apr 04};12:-. Available from: https://journals.stmjournals.com/rrjoesa/article=2024/view=139127


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Regular Issue Subscription Review Article
Volume 12
Issue 01
Received March 18, 2024
Accepted March 27, 2024
Published April 4, 2024