Evaluating the impact of real-time NPK sensor integration on crop productivity insmart farming systems

Authors

  • Deepa Sonal Department of Computer Science, Patna Women's College, Patna, India Author
  • Md. Abu Azhar Wasi Department of Botany, Al--Hafeez College, V. K. S. University, Ara, India Author
  • Aprajita Krishna Department of Physics, Patna Women's College, Patna, India Author
  • Sangeeta Kumari School of Education, Nalanda Open University, Nalanda, India Author

DOI:

https://doi.org/10.56294/la2025154

Keywords:

Smart farming, NPK sensors, crop productivity, precision agriculture, real-time monitoring, nutrient management, IoT in agriculture

Abstract

This research examines the impact of integrating real-time NPK (Nitrogen, Phosphorus, Potassium) sensors within smart farming systems on crop productivity. A model-based approach was employed to design and implement a precision nutrient management system that combines sensor data acquisition, cloud analytics, and algorithm-driven decision-making for fertilizer application. The objective was to optimize nutrient delivery based on current soil conditions, crop type, and growth stage. Field experiments were conducted with wheat crops across two controlled plots: one managed using conventional methods and the other utilizing the proposed sensor-based system. The results emphasize that sensor-integrated precision farming significantly enhances input efficiency, minimizes environmental impact, and boosts economic returns. These findings support the broader adoption of NPK sensor technology in smart agriculture. Recommendations are made for integrating such systems into scalable agricultural models, particularly in regions experiencing high input costs or facing environmental sustainability challenges.

References

1. Alimul Haque M., Haque S., Rahman M., Kumar K. ZS. Potential Applications of the Internet of Things in Sustainable Rural Development in India. In: Proceedings of Third International Conference on Sustainable Computing [Internet]. Springer, Singapore; 2022. p. 455–67. Available from: https://link.springer.com/chapter/10.1007%2F978-981-16-4538-9_45#citeas

2. Md Alimul Haque, Shameemul Haque KK and NKS. Digital Transformation and Challenges to Data Security and Privacy [Internet]. Anunciação PF, Pessoa CRM, Jamil GL, editors. Digital Transformation and Challenges to Data Security and Privacy. IGI Global; 2021. (Advances in Information Security, Privacy, and Ethics). Available from: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-4201-9

3. Sonal D, MISHRA M, SHRIVASTAVA S, MISHRA B, Sonal D, MISHRA M, et al. Agri-IoT Techniques for repelling animals from cropland. 2022 Jun;12681.

4. Almrezeq N, Haque MA, Haque S, El-Aziz AAA. Device Access Control and Key Exchange (DACK) Protocol for Internet of Things. Int J Cloud Appl Comput [Internet]. 2022 Jan;12(1):1–14. Available from: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJCAC.297103

5. Kumar Mishra M, Sonal D. Object Detection: A Comparative Study to Find Suitable Sensor in Smart Farming. Springer Proc Complex. 2022;685–93.

6. Jagadeesan M, Selvaraj PA, Kumar M, Kumar V, Kumar G. IOT Enabled for Smart Farming. New Front Commun Intell Syst. 2021;425–35.

7. Haque MA, Sonal D, Haque S, Kumar K. Internet of Things for Smart Farming. Internet of Things and Machine Learning in Agriculture. 2021.

8. Sonal D, Mishra K, Haque A, Uddin F. A Practical Approach to Increase Crop Production Using Wireless Sensor Technology. LatIA. 2024 Jan;2:10–10.

9. Sinwar D, Dhaka VS, Sharma MK, Rani G. AI-based yield prediction and smart irrigation. In: Internet of Things and Analytics for Agriculture, Volume 2. Springer; 2020. p. 155–80.

10. Giordano S, Seitanidis I, Ojo M, Adami D, Vignoli F. IoT solutions for crop protection against wild animal attacks. 2018 IEEE Int Conf Environ Eng EE 2018 - Proc. 2018;1(710583):1–5.

11. Divya R, Chinnaiyan R. Reliable AI-Based Smart Sensors for Managing Irrigation Resources in Agriculture—A Review. In: International Conference on Computer Networks and Communication Technologies. Springer; 2019. p. 263–74.

12. Ajit Kumar S. Applications of IoT in Agricultural System. Int J Agric Sci Food Technol [Internet]. 2020 May 26;6(1):041–5. Available from: https://www.peertechz.com/articles/IJASFT-6-153.php

13. Kaloxylos A, Eigenmann R, Teye F, Politopoulou Z, Wolfert S, Shrank C, et al. Farm management systems and the Future Internet era. Comput Electron Agric. 2012;89:130–44.

14. Muangprathub J, Boonnam N, Kajornkasirat S, Lekbangpong N, Wanichsombat A, Nillaor P. IoT and agriculture data analysis for smart farm. Comput Electron Agric. 2019;156:467–74.

Published

2025-05-04

How to Cite

1.
Sonal D, Azhar Wasi MA, Krishna A, Kumari S. Evaluating the impact of real-time NPK sensor integration on crop productivity insmart farming systems. Land and Architecture [Internet]. 2025 May 4 [cited 2025 Aug. 29];4:154. Available from: https://la.ageditor.ar/index.php/la/article/view/154