Soil Health Monitoring Through Computer-Based Systems: Techniques, Applications, and Future Trends

Soil Health Monitoring Through Computer-Based Systems: Techniques, Applications, and Future Trends
  IJETT-book-cover           
  
© 2025 by IJETT Journal
Volume-73 Issue-10
Year of Publication : 2025
Author : Girija Shankar Joshi, Sumit Chaudhary, Geetanjali Shukla, Rahul Mahala, Anurag Kumar
DOI : 10.14445/22315381/IJETT-V73I10P116

How to Cite?
Girija Shankar Joshi, Sumit Chaudhary, Geetanjali Shukla, Rahul Mahala, Anurag Kumar,"Soil Health Monitoring Through Computer-Based Systems: Techniques, Applications, and Future Trends", International Journal of Engineering Trends and Technology, vol. 73, no. 10, pp.192-202, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I10P116

Abstract
Soil health monitoring is crucial in sustainable agricultural and environmental management strategies due to soil degradation caused by chemical fertilizers, industrial agriculture, deforestation, and climate change. Traditional methods are slow, expensive, and laborious, leading to spatial and temporally variable soil health. The agricultural industry is transitioning to digital solutions using IoT sensors, remote sensing, AI, machine learning, GIS, and mobile-based applications. These technologies provide real-time data collection, analysis, and visualization, allowing farmers, researchers, and policymakers to understand soil variability, reduce input use, and develop long-term land management plans. The article reviews computer-based techniques for soil health monitoring, including IoT, remote sensing, and AI, and analyzes their applications in agriculture, sustainability, and soil management. It also identifies future trends, challenges, and research directions for precision soil health monitoring. Computer-aided soil health assessment offers real-time, affordable solutions for agriculture, replacing traditional methods. Technologies like IoT sensors, artificial intelligence, and machine learning improve accuracy and efficiency. These systems provide site-specific data, enabling farmers to make informed decisions about irrigation, fertilization, and crop management. However, barriers like investment cost, human capital, and data privacy need to be addressed.

Keywords
Soil health, Computer-based monitoring, Artificial Intelligence, Machine Learning, IoT, Precision agriculture.

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