i-manager Publications

AI Based Drone System for Sprinkling of Pesticides in Agriculture

0*, Aayushi Tyagi**, Lavkush Patel***, Jitendra Kumar Srivastava ****

*-*** Department of Electrical Engineering, B.N. College of Engineering and Technology, Lucknow, Uttar Pradesh, India.

Periodicity:October - December'2025

Abstract

Agriculture has long been essential to the world economy; however, it now confronts a variety of challenges, including environmental issues, limited land availability, and the need for increased crop production. To address these difficulties, modern agriculture is increasingly adopting technological advancements. One of the most promising developments is the integration of drones (Unmanned Aerial Vehicles-UAVs) into farming practices. This paper investigates the different uses of drones in agriculture, analyzes their effects on productivity, sustainability, and efficiency, and considers the future possibilities of drone technology in this field. Moreover, drones contribute to sustainability by promoting precision agriculture, which minimizes the environmental impact of farming activities. By applying resources only where needed, drones help in conserving water, reducing chemical use, and lowering carbon emissions.

Keywords

Drone, Advance technology (AI), Pesticides, Smart Farming, Image Processing.

How to Cite this Article?

Tyagi, A., Patel, L., and Srivastava, J. K. (2025). AI Based Drone System for Sprinkling of Pesticides in Agriculture. i-manager’s Journal on Future Engineering & Technology, 21(1), 45-50.

References

[1]. Abdollahi, A., Rejeb, K., Rejeb, A., Mostafa, M. M., & Zailani, S. (2021). Wireless sensor networks in agriculture: Insights from bibliometric analysis. Sustainability, 13(21), 12011.

[2]. Adão, T., Hruška, J., Pádua, L., Bessa, J., Peres, E., Morais, R., & Sousa, J. J. (2017). Hyperspectral imaging: A review on UAV-based sensors, data processing and applications for agriculture and forestry. Remote Sensing, 9(11), 1110.

[3]. Ajayi, O. G., Salubi, A. A., Angbas, A. F., & Odigure, M. G. (2017). Generation of accurate digital elevation models from UAV acquired low percentage overlapping images. International Journal of Remote Sensing, 38(8- 10), 3113-3134.

[4]. Al-Thani, N., Albuainain, A., Alnaimi, F., & Zorba, N. (2020). Drones for sheep livestock monitoring. In 2020 IEEE 20th Mediterranean Electrotechnical Conference (MELECON) (pp. 672-676). IEEE.

[5]. Ampatzidis, Y., & Partel, V. (2019). UAV-based high throughput phenotyping in citrus utilizing multispectral imaging and Artificial Intelligence. Remote Sensing, 11(4), 410.

[6]. Ang, K. L. M., & Seng, J. K. P. (2021). Big data and machine learning with hyperspectral information in agriculture. IEEE Access, 9, 36699-36718.

[7]. Anthony, D., Elbaum, S., Lorenz, A., & Detweiler, C. (2014). On crop height estimation with UAVs. In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 4805-4812). IEEE.

[8]. Aslan, M. F., Durdu, A., Sabanci, K., Ropelewska, E., & Gültekin, S. S. (2022). A comprehensive survey of the recent studies with UAV for precision agriculture in open fields and greenhouses. Applied Sciences, 12(3), 1047./div>

[9]. Bendig, J., Bolten, A., & Bareth, G. (2012). Introducing a low-cost mini-UAV for thermal-and multispectral- imaging. The I nternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39, 345-349.

[10]. Berni, J. A., Zarco-Tejada, P. J., Suárez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing, 47(3), 722-738.

[11]. Colomina, I., & Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 92, 79-97.

[12]. Everaerts, J. (2008). The use of unmanned aerial vehicles (UAVs) for remote sensing and mapping. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(2008), 1187-1192.

[13]. Natu, A. S., & Kulkarni, S. C. (2016). Adoption and utilization of drones for advanced precision farming: A review. International Journal on Recent and Innovation Trends in Computing and Communication, 4(5), 563–565.

[14]. Reinecke, M., & Prinsloo, T. (2017). The influence of drone monitoring on crop health and harvest size. In 2017 1st International Conference on Next Generation Computing Applications (NextComp) (pp. 5-10). IEEE.

[15]. Van Blyenburgh, P. (1999). UAVs: an overview. Air and Space Europe, 1(5), 43-47.

[16]. Zhang, C., & Kovacs, J. M. (2012). The application of small unmanned aerial systems for precision agriculture: a review. Precision Agriculture, 13(6), 693-712.

[17]. Zúñiga Espinoza, C., Khot, L. R., Sankaran, S., & Jacoby, P. W. (2017). High resolution multispectral and thermal remote sensing-based water stress assessment in subsurface irrigated grapevines. Remote Sensing, 9(9), 961.

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Online	15	15	200	15
Pdf & Online	35	35	400	25

AI Based Drone System for Sprinkling of Pesticides in Agriculture

Abstract

Keywords

How to Cite this Article?

References

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