IoT-Based Smart Farming: A Plant Monitoring System for Precision Agriculture

Authors

  • Rashika Singh Department of Computer Science & Engineering, Moradabad Institute of Technology, Moradabad, INDIA.
  • Prashant Raghav Department of Computer Science & Engineering, Moradabad Institute of Technology, Moradabad, INDIA.
  • Nisha Saini Department of Computer Science & Engineering, Moradabad Institute of Technology, Moradabad, INDIA.
  • Neha Department of Computer Science & Engineering, Moradabad Institute of Technology, Moradabad, INDIA.
  • Saurabh Srivastava Department of Computer Science & Engineering, Moradabad Institute of Technology, Moradabad, INDIA.

DOI:

https://doi.org/10.55544/sjmars.icmri.8

Keywords:

IoT, Smart Farming, Precision Agriculture, Plant Monitoring, Sensors, Cloud Computing, Machine Learning

Abstract

Precision agriculture, leveraging data-driven insights, is crucial for optimizing crop yield and resource utilization. This paper presents an IoT-based smart farming system designed for real-time plant monitoring. The system incorporates various sensors to measure soil moisture, temperature, humidity, and light intensity, integrated with microcontrollers and cloud-based platforms. Key features include automated irrigation, remote monitoring via mobile applications, and predictive analytics for disease detection. The research contributes to enhancing agricultural efficiency through IoT-enabled precision farming, demonstrating significant improvements in resource management and crop productivity. Experimental results showcase the system’s accuracy and reliability in real-world farming environments. 

References

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Published

2025-07-27

How to Cite

Singh, R., Raghav, P., Saini, N., Neha, & Srivastava, S. (2025). IoT-Based Smart Farming: A Plant Monitoring System for Precision Agriculture. Stallion Journal for Multidisciplinary Associated Research Studies, 1(1), 47–51. https://doi.org/10.55544/sjmars.icmri.8

Issue

2025: 2nd International Conference on Recent Trends in Multidisciplinary Research and Innovation (ICMRI)

Section

Conference Articles

License

Copyright (c) 2025 Stallion Journal for Multidisciplinary Associated Research Studies

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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