INTELLIGENT AGRICULTURAL PEST MANAGER DRONE IN PAKISTAN

Shahzad Nasim; Munaf Rashid; Sidra Abid Syed; Imtiaz Brohi

doi:10.34016/pjbt.2023.20.02.816

Authors

Shahzad Nasim Begum Nusrat Bhutto Women University, Faculty of Management Information Science and Technology, Sukkur, Pakistan
Munaf Rashid Ziauddin University, Department of Computer Science and Software Engineering, Karachi, Pakistan
Sidra Abid Syed Sir Syed University of Engineering and Technology, Department of Biomedical Engineering
Imtiaz Brohi Government College University, Hyderabad

DOI:

https://doi.org/10.34016/pjbt.2023.20.02.816

Keywords:

Pesticide spray, drones, agricultural monitoring, weather monitoring

Abstract

This paper’s primary goal is to develop an agriculture drone for spraying pesticides. We discuss an architecture based on unmanned aerial vehicles (UAVs) in this study. Pesticides must be used in agriculture if the quality of large-scale output is to be maintained. It is crucial to increase agriculture's production and efficiency by employing cutting-edge technology to replace employees with intelligent equipment like robots. The research suggests a novel method to replace people in a number of agricultural tasks, including the identification of insect presence, the application of pesticides and fertilizers, etc. The created method entails building a prototype that makes use of basic, affordable equipment including a microprocessor, different motors, and terminal equipment to assist farmers in a variety of operations related to crop fields. Design and build an autonomous drone-based surveillance system capable of identifying injured crops and spraying pesticides in specified regions as needed. To combine an image processing and Artificial Intelligence based real time algorithm to determine crop health and evaluate the need for pesticides, as well as a weather monitoring system that can assist anticipate weather conditions

Metrics

Metrics Loading ...

References

Aqeel-ur-Rehman, Z. A. S., Shaikh, N. A., & Islam, N. An integrated framework to develop context-aware sensor grid for agriculture. Australian Journal of Basic and Applied Sciences, 4(5), 922-931. (2010).

Avtar, Ram, and Teiji Watanabe, eds.Unmanned aerial vehicle: Applications in agriculture and environment. Springer International Publishing, (2020). DOI: https://doi.org/10.1007/978-3-030-27157-2

Bacco, M., Berton, A., Ferro, E., Gennaro, C., Gotta, A., Matteoli, S., ... & Zanella, A. Smart farming: Opportunities, challenges and technology enablers. 2018 IoT Vertical and Topical Summit on Agriculture-Tuscany (IOT Tuscany), 1-6. (2018). DOI: https://doi.org/10.1109/IOT-TUSCANY.2018.8373043

Chang, C. L., & Lin, K. M. (2018). Smart agricultural machine with a computer vision-based weeding and variable-rate irrigation scheme. Robotics, 7(3), 38. DOI: https://doi.org/10.3390/robotics7030038

Devi, G., Sowmiya, N., Yasoda, K., Muthulakshmi, K., & Balasubramanian, K. (2020). Review on application of drones for crop health monitoring and spraying pesticides and fertilizer. J. Crit. Rev, 7(6), 667-672. DOI: https://doi.org/10.31838/jcr.07.06.117

Huuskonen, J., & Oksanen, T. Soil sampling with drones and augmented reality in precision agriculture. Computers and electronics in agriculture, 154, 25-35. (2018). DOI: https://doi.org/10.1016/j.compag.2018.08.039

Jatoi, Fizza Zainab. "Agriculture in Pakistan and it's impact on Economic growth. Available at SSRN 3771914 (2020). DOI: https://doi.org/10.2139/ssrn.3771914

Khamuruddeen, Shaik, K. Leela, K. Sowjanya, and B. Battula. "Intelligent Pesticide Spraying System using Quad Copter. Int. J. Recent Technol. Eng 7 302-305. (2019):

Mazhar, N., Shirazi, S. A., & Javid, K. Desertification vulnerability and risk analysis of Southern Punjab Region, Pakistan using geospatial techniques. J Biodivers Environ Sci, 12(6), 273-282.(2018)

Mogili, U. R., & Deepak, B. B. V. L. Review on application of drone systems in precision agriculture. Procedia computer science, 133, 502-509. (2018). DOI: https://doi.org/10.1016/j.procs.2018.07.063

Nadia Ahmed Uqaili, 5 reasons why Pakistan has the potential to be one of the most powerful countries of the world, Daily Times https://dailytimes.com.pk/282824/5-reasonswhy-pakistan-has-the-potential-to-be-one-of-the-most-powerful-countries-of-the-world. (August 13, 2018),

Qin, W., Xue, X., Zhang, S., Gu, W., & Wang, B. Droplet deposition and efficiency of fungicides sprayed with small UAV against wheat powdery mildew. International Journal of Agricultural and Biological Engineering, 11(2), 27-32. (2018). DOI: https://doi.org/10.25165/j.ijabe.20181102.3157

Rana, M. A. Reshaping agriculture using the nuclear techniques: The Pakistan case. Agricultural Sciences, 9(9), 1168-1172. (2018). DOI: https://doi.org/10.4236/as.2018.99081

Sadhana, B., Naik, G., Mythri, R. J., Hedge, P. G., & Shyama, K. S. B. Development of quad copter based pesticide spraying mechanism for agricultural applications. Int. J. Innov. Res. Electr. Electron. Instrum. Control Eng, 5(2), 121-123.(2017). DOI: https://doi.org/10.17148/IJIREEICE/NCAEE.2017.27

Shivaji, C. P., Tanaji, J. K., Satish, N. A., & Mone, P. P. Agriculture drone for spraying fertilizer and pesticides. Int. J. Res. Trends Innov, 2, 34-36. (2017).

Unmanned aerial vehicle applications in agriculture. Paper presented at the IOP Conference Series: Materials Science and Engineering. Radoglou-Grammatikis, P., Sarigiannidis, P., Lagkas, T., & Moscholios, I. J. C. N. (2020).

Veroustraete, F. The rise of the drones in agriculture. EC agriculture, 2(2), 325-327. (2015).

Waqas, M. S., Cheema, M. J. M., Waqas, A., & Hussain, S. (2016, February). Enhancing water productivity of potato (Solanum tuberosum L.) through drip irrigation system. In Proceedings of the 2nd International Conference on Horticultural Sciences, Faisalabad, Pakistan (pp. 16-18).

Waqas, M. S., Cheema, M. J. M., Hussain, S., Ullah, M. K., & Iqbal, M. M. (2021). Delayed irrigation: An approach to enhance crop water productivity and to investigate its effects on potato yield and growth parameters. Agricultural Water Management, 245, 106576. DOI: https://doi.org/10.1016/j.agwat.2020.106576

Zhang, P., Zhang, Q., Liu, F., Li, J., Cao, N., & Song, C. (2017, July). The construction of the integration of water and fertilizer smart water saving irrigation system based on big data. In 2017 IEEE international conference on computational science and engineering (CSE) and IEEE international conference on embedded and ubiquitous computing (EUC) (Vol. 2, pp. 392-397). IEEE. DOI: https://doi.org/10.1109/CSE-EUC.2017.258