Farming in the Cloud Computing Applications in Agriculture
DOI:
https://doi.org/10.55938/wlp.v1i2.106Keywords:
Precision Agriculture, Cloud Computing, Smart Agriculture, Digital Farming, Agri-Tech InnovationsAbstract
With the objective to address constraints and promote sustainability in climate-smart agricultural practices, this study investigates the technological foundations of cloud-based Internet of Things (IoT) applications in agriculture. This study explores the establishment of a cloud-based and artificial intelligence (AI) platform for digital agriculture that provides farmers with a complete solution. Leveraging knowledge from previous research, it analyzes the benefits of combining cloud computing and AI. The aim of climate-smart agriculture is to promote sustainability and productivity in agriculture. Agricultural digitization can be greatly supported by cloud computing, an emerging field. This survey examines at the technology behind cloud computing and how it's employed in climate-smart agriculture, with an emphasis on trends and limitations. In an effort to maintain food production while boosting resource management, cloud-based monitoring can be streamlined in an array of industries, including agricultural. The objective of this chapter is to implement Agriculture 4.0 by exploring the application of IoT, cloud computing, and big data in agribusiness. It also discusses emerging trends and a conceptual design for the Digital Farming ecosystem.
References
1. Mekala, M. S., & Viswanathan, P. (2017, August). A Survey: Smart agriculture IoT with cloud computing. In 2017 international conference on microelectronic devices, circuits and systems (ICMDCS) (pp. 1-7). IEEE.
2. Namani, S., & Gonen, B. (2020, March). Smart agriculture based on IoT and cloud computing. In 2020 3rd International Conference on Information and Computer Technologies (ICICT) (pp. 553-556). IEEE.
3. Jaiganesh, S., Gunaseelan, K., &Ellappan, V. (2017, March). IOT agriculture to improve food and farming technology. In 2017 Conference on Emerging Devices and Smart Systems (ICEDSS) (pp. 260-266). IEEE.
4. Tawalbeh, M., Quwaider, M., &Lo’ai, A. T. (2021, May). IoT cloud enabeled model for safe and smart agriculture environment. In 2021 12th International Conference on Information and Communication Systems (ICICS) (pp. 279-284). IEEE.
5. Zamora-Izquierdo, M. A., Santa, J., Martínez, J. A., Martínez, V., &Skarmeta, A. F. (2019). Smart farming IoT platform based on edge and cloud computing. Biosystems engineering, 177, 4-17.
6. Symeonaki, E., Arvanitis, K. G., &Piromalis, D. D. (2017). Review on the Trends and Challenges of Cloud Computing Technology in Climate-Smart Agriculture. HAICTA, 66-78.
7. Liu, S., Guo, L., Webb, H., Ya, X., & Chang, X. (2019). Internet of Things monitoring system of modern eco-agriculture based on cloud computing. Ieee Access, 7, 37050-37058.
8. Symeonaki, E. G., Arvanitis, K. G., &Piromalis, D. D. (2019). Cloud computing for IoT applications in climate-smart agriculture: A review on the trends and challenges toward sustainability. In Innovative Approaches and Applications for Sustainable Rural Development: 8th International Conference, HAICTA 2017, Chania, Crete, Greece, September 21-24, 2017, Selected Papers 8 (pp. 147-167). Springer International Publishing.
9. Adetunji, K. E., & Joseph, M. K. (2018, August). Development of a Cloud-based Monitoring System using 4duino: Applications in Agriculture. In 2018 International conference on advances in big data, computing and data communication systems (icABCD) (pp. 4849-4854). IEEE.
10. Jinbo, C., Xiangliang, C., Han-Chi, F., & Lam, A. (2019). Agricultural product monitoring system supported by cloud computing. Cluster Computing, 22, 8929-8938.
11. Paraforos, D. S., & Griepentrog, H. W. (2021). Digital farming and field robotics: Internet of things, cloud computing, and big data. Fundamentals of Agricultural and Field Robotics, 365-385.
12. Pallathadka, H., Sajja, G. S., Phasinam, K., Ritonga, M., Naved, M., Bansal, R., & Quiñonez-Choquecota, J. (2022). An investigation of various applications and related challenges in cloud computing. Materials Today: Proceedings, 51, 2245-2248.
13. Rathor, S., & Kumari, S. (2021, October). Smart agriculture system using iot and cloud computing. In 2021 5th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1-4). IEEE.
14. Debauche, O., Mahmoudi, S., Manneback, P., & Lebeau, F. (2022). Cloud and distributed architectures for data management in agriculture 4.0: Review and future trends. Journal of King Saud University-Computer and Information Sciences, 34(9), 7494-7514.
15. Singh, S., Chana, I., &Buyya, R. (2020). Agri-Info: cloud based autonomic system for delivering agriculture as a service. Internet of Things, 9, 100131.
16. Dozono, K., Amalathas, S., & Saravanan, R. (2022). The impact of cloud computing and artificial intelligence in digital agriculture. In Proceedings of Sixth International Congress on Information and Communication Technology: ICICT 2021, London, Volume 1 (pp. 557-569). Springer Singapore.
17. Junaid, M., Shaikh, A., Hassan, M. U., Alghamdi, A., Rajab, K., Al Reshan, M. S., & Alkinani, M. (2021). Smart agriculture cloud using AI based techniques. Energies, 14(16), 5129.
18. Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2022). Enhancing smart farming through the applications of Agriculture 4.0 technologies. International Journal of Intelligent Networks, 3, 150-164.
19. Alharbi, H. A., & Aldossary, M. (2021). Energy-efficient edge-fog-cloud architecture for IoT-based smart agriculture environment. IEEE Access, 9, 110480-110492.
20. Mumtaz, R., García-Nieto, J., Hassan, S. A., Zaidi, S. A. R., & Iqbal, N. (2019). Precision agriculture techniques and practices: From considerations to applications. Sensors, 19(17), 3796.
21. Symeonaki, E., Arvanitis, K., &Piromalis, D. (2020). A context-aware middleware cloud approach for integrating precision farming facilities into the IoT toward agriculture 4.0. Applied Sciences, 10(3), 813.
22. O'Grady, M. J., Langton, D., & O'Hare, G. M. P. (2019). Edge computing: A tractable model for smart agriculture?. Artificial Intelligence in Agriculture, 3, 42-51.
23. Ferrández-Pastor, F. J., García-Chamizo, J. M., Nieto-Hidalgo, M., & Mora-Martínez, J. (2018). Precision agriculture design method using a distributed computing architecture on internet of things context. Sensors, 18(6), 1731.
24. Rathod, M. L., Shivaputra, A., Umadevi, H., Nagamani, K., & Periyasamy, S. (2022). Cloud Computing and Networking for SmartFarmAgriTech. Journal of Nanomaterials, 2022.
25. Saban, M., Bekkour, M., Amdaouch, I., El Gueri, J., Ait Ahmed, B., Chaari, M. Z., ... &Aghzout, O. (2023). A Smart Agricultural System Based on PLC and a Cloud Computing Web Application Using LoRa and LoRaWan. Sensors, 23(5), 2725.
26. Saura, J. R., Reyes-Menendez, A., & Palos-Sanchez, P. (2019). Mapping multispectral Digital Images using a Cloud Computing software: applications from UAV images. Heliyon, 5(2).
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Mansi Sahu, Kailash Bisht, Jasvinder Kaur
This work is licensed under a Creative Commons Attribution 4.0 International License.
