Smart Farming and Agribusiness Enhancement: Integrating Artificial Intelligence and the Internet of Things

Abstract

Through the research is to look to the role of artificial intelligence and Internet of things in smart farming. The aim is to promote modern agriculture by improving efficiency, crop yield, and the sustainable use of resources.

The combination of rich literature review with the use cases and field- level deployment of the AI and IoT based agri technologies. The study looks at applications like crop disease prediction using convolutional neural networks. It also examines IoT-enabled smart irrigation systems and unmanned aerial vehicles to monitor fields and collect data in real time.

The investigation reveals that AI or artificial intelligence models of high accuracy can identify crop diseases, predict yield, and automate decision-making in farm management. Networks (soil sensors, weather stations and satellites) will enable real-time monitoring of short-term weather and thus, spatial and temporal application of inputs. The combination of these technologies improves the productivity, reduces the water and fertilizer usage and minimizes the environmental damage.

This study presents a rich synthesis of AI and IoT applications in agriculture and both together can revolutionize agro-based systems.  It deals with existing problems such as compatibility of data, infrastructural limits at rural places, and scalable deployment models. The research adds to the knowledge base on digital agriculture and offers evidence-based insights for relevant policymakers, researchers, and agribusiness stakeholders.

Classification JEL: Q13, Q16, O33.  

Paper type: Theoretical Research