• Abhijeet D.Salwe
• Prof.Lokesh S.Khedekar

Crop cultivation is one of the oldest activities of civilization. For a long time, crop production was carried out based on knowledge passed from generation to generation. The Indian economy, dominatingly, depends upon farming along with agro-industry things. The soil ingredients (like Nitrogen, Phosphorous, Potassium), crop rotation, soil clamminess, atmospheric and surface temperature, precipitation, etc, play an efficient role in cultivation. The present evidence related to this field includes a model which is incorporated with ML algorithms (Random Forest, Decision Tree, Artificial Neural Network) to determine best crop. In this paper, the proposed model is enhanced by applying deep learning techniques and along with the prediction of crop, a clear information is achieved regarding the amounts of soil ingredients needed with their expenses separately. It provides a better accuracy than the existing model. It analyzes the given data and help the farmers in predicting a crop which in return help in gaining profits. The climatic and soil conditions of land are taken into consideration to predict a proper yield.

Crop,CloudComputing,Machine,Deep Learning

"A Survey On Smart Agriculture Crop Yield Prediction Using Deep Learning And Cloud Computing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 8, page no.a864-a867, August-2021, Available :http://www.jetir.org/papers/JETIR2108113.pdf

"A Survey On Smart Agriculture Crop Yield Prediction Using Deep Learning And Cloud Computing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 8, page no. ppa864-a867, August-2021, Available at : http://www.jetir.org/papers/JETIR2108113.pdf