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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 6

Published on: June 2026

GREENMIND:AI-POWERED SMART FARMING ECOSYSTEM

Sakshi V. Taru Vaishnavi K. Ahivale Pradnya R. Sakunde

Dr. B. H. Patil

Department of Electronics and Telecommunication Engineering

Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering and Technology Baramati, India

 
DOI:https://doi.org/10.55041/ijcope.v2i6.286

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Abstract

Agriculture is evolving toward intelligent automa-tion driven by artificial intelligence and Internet of Things tech-nologies. This paper presents GreenMind, an integrated smart farming ecosystem designed to monitor environmental parame-ters and automate irrigation and fertilizer delivery. The proposed system employs sensor networks, ESP32 microcontroller, cloud connectivity, and machine learning based plant health analysis. Real-time monitoring combined with automated decision-making improves crop productivity while reducing water and fertilizer wastage. Experimental results validate system reliability and demonstrate its suitability for precision agriculture applications. Index Terms—Smart Agriculture, IoT, Machine Learning,

Precision Farming, ESP32, Automation.

How to Cite this Paper

Taru, S. V., Ahivale, V. K. & Sakunde, P. R. (2026). GreenMind:AI-Powered Smart Farming Ecosystem. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(6). https://doi.org/10.55041/ijcope.v2i6.286

Taru, Sakshi, et al.. "GreenMind:AI-Powered Smart Farming Ecosystem." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 6, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i6.286.

Taru, Sakshi,Vaishnavi Ahivale, and Pradnya Sakunde. "GreenMind:AI-Powered Smart Farming Ecosystem." International Journal of Creative and Open Research in Engineering and Management 02, no. 6 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i6.286.

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References


  1. Kusuma, S. Rajashree, M. L. Chayadevi, Mona, K. S. Shreedevi, and S. Geetha, “Intelligent Plant Watering System: Smart City,” in Proc. IEEE Int. Conf. on Smart Cities and Sustainable Development (ICSSSD), June 2024.

  2. Rashmi Sharma, V. Mishra, and S. Shrivastava, “Enhancing Crop Yields through IoT-Enabled Precision Agri-culture,” in Proc. IEEE Int. Conf. on Smart Computing and Systems (ICSCAS), June 2023.

  3. B. Smith, and C. D. Jones, “Architectural Tradeoffs in Edge Com- puting for IoT Agriculture,” IEEE Sensors Journal, vol. 25, no. 8, pp. 4001-4010, Aug. 2025.

  4. H. Patel, and R. K. Singh, “Accuracy and Calibration Challenges of Low-Cost NPK and pH Sensors for Smart Farming,” J. of IoT and Embedded Systems, vol. 12, no. 1,45-58, Jan. 2024.

  5. K. Gajula, J. Singamsetty, V. C. Dodda, and L. Kuruguntla, “Prediction of Crop and Yield in Agriculture Using Machine Learning Techniques,” in Proc. IEEE Int. Conf. on Computational Intelligence and Engineering (ICCIE), July 2021.

  6. Rajput, S. Chaudhary, L. Varshney, and D. Singh, “IoT-Based Smart Agriculture Monitoring Using NodeMCU and Blynk App,” in Proc. IEEE Int. Conf. on Computing and Communication (ICCC), Aug. 2022.

  7. K. K. Sahoo, A. S. Mohanty, S. M. Senapati, andL. Behera, “Edge Computing Framework for Real-Time Monitoring in Precision Agriculture,” IEEE Internet of Things Journal, vol. 10, no. 5, pp. 3801- 3810, May 2023.

  8. S. Patel, and A. V. Shah, “Comparative Analysis of Deep Learning Inference using TensorFlow Lite on Resource-Constrained Devices,” IEEE Access, vol. 10, pp. 5890-5900, 2022.

  9. Li, and C. Chen, “Scalable Fog-to-Cloud Orchestra-tion for Smart Agriculture Applications,” IEEE Transactions on Industrial Informatics, vol. 17, no. 3, pp. 2101-2111, Mar. 2021.

  10. A. Singh, and V. K. Sharma, “IoT-Based Elec-trochemical Sensors for Non-Destructive Monitoring of Soil Macronutrients (NPK),” Sensors and Actuators B: Chemical, vol. 398, Jan. 2024.

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