AgriDrone: Automated Fertilizer and Pesticide Distribution System
Authors/Creators
-
1.
JIS University
Description
Agriculture plays a vital role in economic
development and global food security, yet traditional
methods of fertilizer and pesticide application remain
labor-intensive, time-consuming, and
often result in
uneven chemical distribution and environmental harm.
The proposed AgriDrone: Automated Fertilizer and
Pesticide Distribution System introduces an unmanned
aerial vehicle (UAV)-based solution designed to enhance
precision farming through automated and controlled
agrochemical spraying. The system integrates GPS-based
navigation, programmable flight control, and a precision
dispensing mechanism to ensure uniform coverage across
agricultural fields while minimizing chemical wastage.
Equipped with sensors for monitoring field conditions
and crop density, the drone can optimize spray patterns
and intensity in real time, thereby improving efficiency
and reducing operational costs. By eliminating direct
human involvement in chemical spraying, the system also
minimizes health risks to farmers. Experimental
evaluation indicates that the AgriDrone system achieves
faster coverage, improved uniformity, and reduced input
usage compared to conventional manual methods.
Overall, the proposed system offers a cost-effective,
scalable, and environmentally sustainable solution that
supports modern precision agriculture and enhances crop
productivity.
Files
Final year project Research Paper.pdf
Files
(300.6 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:cbce64c9bcd4e09926a7f928f014ca73
|
300.6 kB | Preview Download |
Additional details
Additional titles
- Alternative title (English)
- Drone Based pesticide and fertilizer spraying system
References
- [1] C. Zhang and J. M. Kovacs, "The application of small unmanned aerial systems for precision agriculture: A review," Precision Agriculture, vol. 19, no. 4, pp. 693–712, 2018. [2] D. C. Tsouros, S. Bibi, and P. G. Sarigiannidis, "A review on UAV-based applications for precision agriculture," Information, vol. 10, no. 11, p. 349, 2019. [3] Y. Huang, S. J. Thomson, W. C. Hoffmann, Y. Lan, and B. K. Fritz, "Development and prospect of unmanned aerial vehicle technologies for agricultural production management," International Journal of Agricultural and Biological Engineering, vol. 6, no. 3, pp. 1–10, 2013. [4] A. Koirala, K. B. Walsh, Z. Wang, and C. McCarthy, "Deep learning for real-time fruit detection and orchard management using UAV imagery," Computers and Electronics in Agriculture, vol. 162, pp. 219–227, 2019. [5] J. Li and P. Wang, "Design and optimization of multi rotor UAV spraying systems for precision agriculture," Journal of Agricultural Engineering Research, vol. 210, pp. 45–56, 2022. [6] P. Lottes, T. Hörsch, J. Pfeifer, and C. Stachniss, "UAV based crop and weed classification for smart farming," IEEE Robotics and Automation Letters, vol. 2, no. 4, pp. 1990 1997, 2017. [7] E. R. Hunt and C. S. T. Daughtry, "What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?" International Journal of Remote Sensing, vol. 39, no. 15–16, pp. 5345–5376, 2018. [8] Food and Agriculture Organization of the United Nations, The State of Food and Agriculture 2020: Overcoming Water Challenges in Agriculture. Rome, Italy: FAO, 2020.