CLOUD COMPUTING TECHNOLOGY PRACTICES AND PERFORMANCE OF AGRICULTURE PROJECTS IN NYANDARUA COUNTY, KENYA

Emma Wamaitha Mbugua, Dr. Yusuf Muchelule

Abstract


Cloud computing has surfaced as a transformative technology with the eventuality to revise the agriculture industry. Cloud computing technology and agriculture practices was a crucial research area to cover, to increase farm productivity. In recent times, cloud- based results have been increasingly integrated into agricultural practices, offering growers and stakeholders access to advanced data analytics, remote monitoring, and perfection agriculture capabilities. Cloud computing in agriculture encompasses operations, from crop operation and supply chain optimization of end products. Farmers are now using cloud- based platforms to collect, store, and dissect vast quantities of data from detectors, satellites, and literal records. This data- driven approach enables informed decision-making, resource optimization, and bettered agriculture issues. The benefits of cloud computing in agriculture are multifarious. It empowers growers to make data- driven opinions, optimize resource allocation, and enhance crop yields while reducing input costs. Precision agriculture, made possible through Cloud- computing technology tools, allows for targeted irrigation, fertilization, and pest control, leading to further sustainable agriculture practices. Cloud computing platforms also facilitated real- time access to request information, enabling farmers to make informed choices about when and where to sell their products. However, the relinquishment of cloud computing in agriculture isn't without challenges, espousing this technology and ensuring that small- scale and resource- constrained growers can pierce and profit from cloud technology which remains a challenge in numerous regions. The research data was collected from 196 staff members and farmers within Nyandarua county that consisted of ICT, communication, finance, administration, agriculture, Economic planning, trade and youth empowerment departments. Primary data was collected by the use administered questionnaire and secondary data from Nyandarua County government materials and records. The questionnaires were reviewed and evaluated for content validity and reliability. Descriptive and inferential statistics was utilized in the analysis of data and presented by means of Statistical Package for Social Sciences (SPSS V27). Analyzed data was in the form of graphs, tables and charts while qualitative findings were presented thematically.  It is thus governments and associations to increasingly recognize the significance of bridging the digital peak in agriculture to ensure equitable access to technology- driven benefits for all growers.

Key Words: Cloud computing technology, agriculture practices, Stakeholders’ Engagement, Policy Regulation, Performance, Agriculture Projects, Nyandarua County

Full Text:

PDF

References


Alali, F. A., & Yeh, C. L. (2012). Cloud computing: Overview and risk analysis. Journal of Information Systems, 26(2), 13-33.

Ashokkumar, K., Chowdary, D. D., & Sree, C. D. (2019, October). Data analysis and prediction on cloud computing for enhancing productivity in agriculture. In IOP Conference Series: Materials Science and Engineering (Vol. 590, No. 1, p. 012014). IOP Publishing.

Beriya, A., & Saroja, V. N. (2019). Data-Driven Decision Making for Smart Agriculture (No. 8). ICT India Working Paper.

Diaby, T., & Rad, B. B. (2017). Cloud computing: a review of the concepts and deployment models. International Journal of Information Technology and Computer Science, 9(6), 50-58.

Dinesh, E., & Ramesh, L. (2019). E-Farming Platform for Agriculture Parameter Monitoring through Cloud Computing. Int. J. Recent Technol. Eng, 7(6), 616-619.

Elamir, A. M., Jailani, N., & Bakar, M. A. (2013). Framework and architecture for programming education environment as a cloud computing service. Procedia Technology, 11, 1299-1308

Forcén-Muñoz, M., Pavón-Pulido, N., López-Riquelme, J. A., Temnani-Rajjaf, A., Berríos, P., Morais, R., & Pérez-Pastor, A. (2021). Irriman platform: Enhancing farming sustainability through cloud computing techniques for irrigation management. Sensors, 22(1), 228.

Ghilic-Micu, B., Stoica, M., & Uscatu, C. R. (2014). Cloud Computing and Agile Organization Development. Informatica Economica, 18(4).

Gill, A., Kaur, T., & Devi, Y. K. (2022, August). Application of Machine Learning Techniques in Modern Agriculture: A Review. In Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing (pp. 263-270).

Hoefer, C. N., & Karagiannis, G. (2010, December). Taxonomy of cloud computing services. In 2010 IEEE Globecom Workshops (pp. 1345-1350). IEEE.

Hofman, I., & Visser, O. (2021). Towards a geography of window dressing and benign neglect: The state, donors and elites in Tajikistan’s trajectories of post-Soviet agriculture change. Land Use Policy, 111, 105461.

Katzan Jr, H. (2010). The education value of cloud computing. Contemporary Issues in Education Research (CIER), 3(7), 37-42.

Kimani, J. G. (2017). Challenges facing integration and use of ICT in the management of county governments in Kenya. Journal of Information Technology, 1(1), 1-1.

Kituku, K. M. (2012). Adoption of cloud computing in Kenya by firms listed in the Nairobi Stock Exchange (Doctoral dissertation, University of University).

Kyalo, M. A., Kimeli, C. M., & Evans, A. (2017). An Assessment Of Factors Influencing Service Delivery In County Governments In Kenya: A Study Of County Government Of Kitui, Kenya. International Journal of Innovative Research and Advanced Studies, 4(8), 253-262.

Leng, K., Bi, Y., Jing, L., Fu, H. C., & Van Nieuwenhuyse, I. (2018). Research on agricultural supply chain system with double chain architecture based on blockchain technology. Future Generation Computer Systems, 86, 641-649.

Patel, H. B., & Kansara, N. (2021). Cloud Computing Deployment Models: A Comparative Study. International Journal of Innovative Research in Computer Science & Technology (IJIRCST).

Pradhan, L., Mohapatro, B. B., Dehuri, S., & Panda, A. K. (2015). E-agriculture: A New Instrument for Indian Farmers. EVERYMAN’S SCIENCE, 227.

Prasad, K. S. N., Sirisha, C. N., Kumar, C. N., Deekshitha, A., & Gunninka, D. (2021). Cloud computing in agriculture-an affordable way to achieve smart farming. Int. J. Comput. Sci. Commun.(ISSN: 0973-7391), 12(2), 52-61.

Qin, T., Wang, L., Zhou, Y., Guo, L., Jiang, G., & Zhang, L. (2022). Digital technology-and-services-driven sustainable transformation of agriculture: Cases of China and the EU. Agriculture, 12(2), 297.

Rajak, A. A. (2022). Emerging technological methods for effective farming by cloud computing and IoT. Emerging Science Journal, 6(5), 1017-1031.

Shawish, A., & Salama, M. (2013). Cloud computing: paradigms and technologies. In Inter-cooperative collective intelligence: Techniques and applications (pp. 39-67). Berlin, Heidelberg: Springer Berlin Heidelberg.

Šilerová, E., Pechrová, M., & Hennyeyová, K. (2016). Utilization of cloud computing in Agricultural Holdings. Proceedings of Agriculture perspectives XXV, 358-364.

Sun, C. (2012). Research of E-Commerce based on cloud computing. In Advances in Computer Science and Information Engineering: Volume 2 (pp. 15-20). Springer Berlin Heidelberg.

Surbiryala, J., & Rong, C. (2019, August). Cloud computing: History and overview. In 2019 IEEE Cloud Summit (pp. 1-7). IEEE.

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.

Upadhyay, A., & Yadav, I. (2022, May). Application of Internet of Things and Cloud Computing to Enhance the Agro-productivity. In Proceedings of International Conference on Communication and Artificial Intelligence: ICCAI 2021 (pp. 173-182). Singapore: Springer Nature Singapore.

Yandong, Z., & Yongsheng, Z. (2012, August). Cloud computing and cloud security challenges. In 2012 International Symposium on Information Technologies in Medicine and Education (Vol. 2, pp. 1084-1088). IEEE.


Refbacks

  • There are currently no refbacks.