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Paper ID:IJSREM65565

IoT and AI Enabled Smart Agriculture System for Motor Monitoring and Crop Disease Detection Using ESP32

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65565

Volume:

10 |

6 |

Jun 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Shruti Waghmare

Shruti Waghmare

Electronics and telecommunication

Sinhgad academy of engineering kondwa

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Sharavni Milind walse

Sharavni Milind walse

Electronics and telecommunication

Sinhgad academy of engineering kondwa

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Mentors

Dr. K.M.Gaikwad

Dr. K.M.Gaikwad

Electronics and telecommunication

Sinhgad academy of engineering kondwa

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Abstract

The Smart Agriculture System using ESP32 for Motor Monitoring and Crop Health Management is designed to improve farming efficiency through the integration of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The system continuously monitors important agricultural parameters such as temperature, humidity, motor voltage, and current in real time. The ESP32 microcontroller collects and processes sensor data and transmits it to the Smart Kissan mobile application, enabling farmers to monitor field conditions and control irrigation motors remotely. In addition, the system incorporates an AI-based crop disease detection module that analyzes leaf images uploaded by farmers and provides disease predictions along with treatment recommendations. This integrated approach helps reduce manual effort, improve motor safety, enable early disease detection, increase crop productivity, and support sustainable farming practices. The proposed system offers a cost-effective, user-friendly, and scalable solution for modern agriculture.

KEYWORDS

ESP32 Smart Agriculture Internet of Things (IoT) Motor Monitoring Crop Health Management Artificial Intelligence Crop Disease Detection Smart Kissan App Remote Monitoring Precision Farming Smart Irrigation Sustainable Agriculture.

Cite This Article

Shruti Waghmare, Sharavni Milind walse, Dr. K.M.Gaikwad, "IoT and AI Enabled Smart Agriculture System for Motor Monitoring and Crop Disease Detection Using ESP32," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-4, Jun 2026.

Full Article/Conclusion

A.Summery of finding: The smart agriculture system using ESP32 effectively monitors soil moisture, temperature, and humidity in real time. It automatically controls the irrigation motor, reducing water wastage and manual effort. The system also helps in early detection of crop diseases and provides useful insights for better decision-making. Overall, it improves efficiency, saves resources, and supports sustainable farming.   B.Implication: This system shows that using smart technology in agriculture can improve efficiency and reduce water wastage. It helps farmers make better decisions through real-time data and automation. The project also supports sustainable farming and reduces manual effort. Overall, it highlights the importance of adopting IoT-based solutions in modern agriculture.

References

1. M. Budhia, G. Covic, and J. Boys, “Design and Optimization of Circular Magnetic Structures for Inductive Power Transfer Systems,” IEEE Transactions on Power Electronics, vol. 26, no. 11, pp. 3096–3108, Nov. 2011. 2. T. Imura and Y. Hori, “Maximizing Air Gap and Efficiency of Magnetic Resonant Coupling for Wireless Power Transfer Using Equivalent Circuit and Neumann Formula,” IEEE Transactions on Industrial Electronics, vol. 58, no. 10, pp. 4746–4752, Oct. 2011. 3. Y. Li, C. Ma, and Z. Luo, “Integration of Wireless Power Transfer with Electric Vehicle Dashboards for Smart Energy Systems,” Journal of Power Electronics and Drive Systems, vol. 4. no. 3, pp. 250–259, 2022. M. N. O. Sadiku, S. M. Musa, and O. D. Momoh, “Wireless Power Transfer: A Review,” International Journal of Engineering Research and Applications, vol. 4, no. 1, pp. 987–994, Jan. 2014. 5. K. Chen, “Advances in Wireless Charging Systems for Electric Vehicles,” IEEE Transactions on Transportation Electrification, vol. 4, no. 1, pp. 3–22, Mar. 2018.

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Publication Date

6/26/2026

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Review Rounds: 2

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