Journal of ISMAC
IRO Journals
Volume 7 — Issue 1 — March 2025

IoT based Soil Testing System with Recommendation of Organic Fertilizer

https://doi.org/10.36548/jismac.2025.1.004
Pages: 52-64
PDF
Geetha S.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Priya Archutha V.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Saran S.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Saravanan P.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
Yakesh K.
Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology
PDF

How to Cite

S., Geetha, Priya Archutha V., Saran S., Saravanan P., and Yakesh K. 2025. “IoT Based Soil Testing System With Recommendation of Organic Fertilizer”. Journal of ISMAC 7 (1): 52-64. https://doi.org/10.36548/jismac.2025.1.004.
ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver AMA

Download Citation

Endnote/Zotero/Mendeley (RIS) BibTeX

Keywords

— IoT
— Node MCU
— NPK value
— crops
— fertilizer
Published: 11-04-2025

Abstract

The research is about the proposed IoT-based soil testing system that focuses on improving soil quality by providing custom organic fertilizer recommendations and crop suggestions based on real-time soil analysis. The system makes use of a network of sensors, including moisture sensors and temperature and humidity sensors, to measure critical soil parameters. These readings are collected and processed using a Node MCU, which forms the basis of the data acquisition process. The data collected are analyzed with a machine learning approach. Initially, sensor readings are processed using the Random Forest algorithm to predict soil nutrient composition in terms of nitrogen (N), phosphorus (P), and potassium (K). Then, these values of nutrients are input into the Euclidean distance algorithm, which calculates the similarity that exists between the soil's current condition and a defined dataset of ideal soil profiles. The results on the suggested organic fertilizer and available crops are rendered on an easily accessible webpage that is user-friendly for farmers to use.

References

  1. Garg, Anchit, Priyamitra Munoth, and Rohit Goyal. "Application of soil moisture sensor in agriculture." In Proceedings of Internation Conference on Hydraulic, 2016. 8-10.
  2. Sukumar, P., Dr T. Kavitha, A. Deepika, and V. Jashnavi. "Real Time soil fertility analyzer using IOT." In National Conference on Emerging Trends In Information, Management And Engineering Sciences NC’e-TIMES, 2018. 1-10.
  3. Jayaprahas, J., S. Sivachandran, K. Navin, and K. Balakrishnan. "Real time embedded based soil analyzer." Inernational Journal of Advanced Research in computer and communication engineering 3, no. 3 (2014).
  4. Na, Abdullah, William Isaac, Shashank Varshney, and Ekram Khan. "An IoT based system for remote monitoring of soil characteristics." In 2016 International conference on information technology (InCITe)-the next generation IT summit on the theme-internet of things: Connect your Worlds, IEEE, 2016. 316-320.
  5. Sujatha, R., and R. Anitha Nithya. "A survey on soil monitoring and testing in smart farming using IoT and cloud platform." Int. J. Eng. Res. Appl 7, no. 11 (2017): 55-59.
  6. Bodake, Komal, Rutuja Ghate, Himanshi Doshi, Priyanka Jadhav, and Balasaheb Tarle. "Soil based fertilizer recommendation system using Internet of Things." MVP Journal of Engineering Sciences 1, no. 1 (2018): 13-19.
  7. Sri, A. N., and P. Ammi Reddy. "A Smart Framework for Agriculture Production Improvement using Web of Things." vol 50 (2017): 251-259.
  8. Joshi, P. P., and S. S. Kanade. "Wireless sensors and agriculture parameter monitoring: experimental investigation." J Electron Commun Eng Res 3, no. 8 (2017): 6-13.
  9. Kumar, C. Kishore, and Veeramuth Venkatesh. "Cloud based soil monitoring and smart irrigation system using IoT and precision farming." International Journal of Pure and Applied Mathematics 119, no. 18 (2018): 2011-2020.
  10. Suma, N., Sandra Rhea Samson, S. Saranya, G. Shanmugapriya, and R. Subhashri. "IOT based smart agriculture monitoring system." International Journal on Recent and Innovation Trends in computing and communication 5, no. 2 (2017): 177-181.
  11. Seshasai, K., P. Uma Sathyakam, and Kavicharan Mummaneni. "Optimal segmentation of Cu–CNT interconnects." Multiscale and Multidisciplinary Modeling, Experiments and Design 7, no. 4 (2024): 3539-3549.