Abstract
Cloud computing technology and Artificial Intelligence (AI) techniques are becoming significant components in many applications across multiple domains, including agriculture. Cloud computing allows the mass storage of various types of data readily available for descriptive, predictive, and prescriptive analytics. AI techniques, such as deep neural networks, have achieved promising disease detection and yield prediction outcomes. Not many agricultural systems have applied cloud computing and AI and have been made available for farmers to use practically. This study discusses the design and development of a digital agriculture platform using AI and cloud technology. The proposed platform provides an end-to-end digital agriculture system to farmers. This study discusses the benefits of applying cloud computing and AI according to the proposed system and existing studies. The achieved outcomes delivered a significant edge over the conventional platform for digital agriculture. We developed a plant disease diagnosis model to enable farmers to identify diseases through a mobile application on the proposed platform. Our proposed model showed significant results for identifying and diagnosing plant diseases with high accuracy.
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The first and second authors thank RC Buminiaga for financial, domain expertise, and technical support for this research.
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Dozono, K., Amalathas, S., Saravanan, R. (2022). The Impact of Cloud Computing and Artificial Intelligence in Digital Agriculture. In: Yang, XS., Sherratt, S., Dey, N., Joshi, A. (eds) Proceedings of Sixth International Congress on Information and Communication Technology. Lecture Notes in Networks and Systems, vol 235. Springer, Singapore. https://doi.org/10.1007/978-981-16-2377-6_52
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DOI: https://doi.org/10.1007/978-981-16-2377-6_52
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