IoT-Driven Artificial Intelligence Technique for Fertilizer Recommendation Model
Bhuvaneswari Swaminathan, Saravanan Palani, V. Subramaniyaswamy, Ketan Kotecha, Vinay Kumar
Abstract
Smart farming systems emphasize the need for modern technologies like the Internet of Things, Cloud, and Artificial Intelligence (AI) in the agricultural process. The digital transformation accelerates conventional farming practices to increase crop production with quality. Earlier works failed to integrate AI with sensor technology, guiding agricultural practitioners in a successful direction. Therefore, we propose an architectural model with four layers, including sensor, network, service, and application, aid in deploying a smart farming system with limited energy consumption. Moreover, focusing on the application layer, we implement a deep learning approach to build a fertilizer recommendation system that matches the expert's opinion. Finally, the whole system outcomes are presented as a single mobile application for farmers’ ease of use.