A Systematic Review on Crop-Yield Prediction through Unmanned Aerial Vehicles

In recent years, with the increase in big data technologies the Machine learning is an important decision support tool, smart farming observes the behavior of climate change over the crops to predict the yield of the crop, whether the yield will be high or low in certain factors. A systematic literature review has been performed for the purpose of identifying the extent of research work in the field of crop yield prediction using machine learning based approaches. This study aims to perform comparative analysis over the existing approaches for the sake of identifying the most frequently reported issue in the crop yield prediction along with the approaches which are most suitable for the resolution of these issues. Study interprets, evaluate and identify the available researches related to the explicit field. This paper presents the significance of crop yeild prediction and how developing countries are adopting machine learing algorithms. The total 37 research articles has been selected over which the SLR is documented. The study shows that RF, SVm and CNN is most common algorithms for crop yeild prediction.