Artificial Intelligence in Smart Agriculture: Applications and Challenges

Abstract

Artificial intelligence has been categorized as a subfield of computer science wherein machines perform smart learning tasks with the help of data and statical methods. Agriculture is one of the oldest social activities performed by humans. It provides many crucial things like raw materials, food, and employment. Due to the increasing population, it is the need of the hour that the agriculture sector should increase production of resources to match actual demand. Many agronomic factors such as weeds, pests, water condition and availability, and climate conditions impact overall yield. At present, methods used by farmers for management are traditional and insufficient to meet increased demand.  To match future demand, new innovative agriculture methos need to be adopted. Artificial intelligence techniques in smart farm monitoring can enhance the quality and quantity of yield.  This paper surveys different areas in agriculture where artificial intelligence is applicable. Artificial intelligence enables farmers to access farm-related data and analytical methods that will foster better agronomy, reduce waste, and improve efficiencies with minimum environmental impact. Various artificial intelligence techniques that make agriculture smarter than its previous forms are discussed. In this paper, the implementation of various artificial intelligence techniques in smart agriculture is studied. The aim of this study is to present different key applications and associated challenges to open up new future opportunities.