IoT & AI Enabled Information and Communication Technologies in Transforming Rural Communities via Digital Agriculture

• Published in: 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) pp. 1 - 6
• Main Authors: Raj, Nihal, Masih, Jolly, Selvaraj, Krishnamoorthy, G, Pavithra, Ramkumar, E.V.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 04.04.2024
• Subjects: Agriculture Transformation; Artificial Intelligence; Digital Agriculture; Empowerment; Information and Communication Technologies (ICTs); Internet of Things; Policy Analysis; Rural areas; Rural Communities; Smart agriculture; Soil moisture; Sustainability; Temperature distribution; Temperature measurement; Temperature sensors
• DOI: 10.1109/ICONSTEM60960.2024.10568764

Through the widespread use of ICTs, the convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) has sparked a revolutionary transformation in rural farming. This study delves at the dynamic interplay of IoT, AI, and ICTs as they pertain to digital agriculture and their far-reaching effects on rural areas. The study's findings show that Internet-of-Things (IoT) sensors can monitor things like soil moisture, temperature, and humidity in real-time, and that artificial intelligence (AI) algorithms can interpret this data to deliver predictive insights that optimize resource allocation and boost crop yields. These learnings are shared through an ICT platform, which helps to close the digital divide and give rural farmers more agency. In order to promote broad use of technology in rural regions, it is crucial to have policies and incentives in place that are helpful to do so. Privacy of data and reducing prejudice are two ethical factors that contribute to fair results. Collectively, these results show how much progress can be made towards ending rural poverty, improving food security, reducing the digital gap, fostering sustainability, and propelling broad economic expansion. Collaboration across disciplines, model improvement, cost-effectiveness, and innovative applications are key steps for the future of rural community technology development.