Adaptive smart farming system using Internet of Things (IoT) and artificial intelligence (AI) modeling

Abstract

The agricultural sector allowed for very diverse management in the global economy, where the sector is being strengthened to be part of the commercial growth engine. The firm belief in incorporating information and communication technology (ICT) with agricultural systems influenced the expansion of a mechanized system to classify and organize agricultural products. Conventional farming is based on observations and is highly familiar which is quite laborious and time-consuming, consequently, the need for continuous monitoring of crops can be a difficulty for the farmers. The technologically advanced system initiates the monitoring and mapping process by capturing and predicting the general characterization. The integration of the Internet of Things (IoT) and artificial intelligence (AI) plays a dynamic role in the concept of smart farming, using such applications as monitoring systems to observe crop yield estimation, irrigation, nutrient management, disease identification, and weather forecast. This paper proposes a framework to enable advanced AI according to user-defined variables, of which sensors are an important feature and contributor. As an interface between a sensor and IoT as a medium, it offers great potential for outstanding performance. The results obtained using this integrated approach are very promising and can be used significantly for any other application of precision agriculture.