This paper present a way to aid farmers
focusing on profitable vegetable cultivation in Sri Lanka.
As agriculture creates an economic future for developing
countries, the demand of modern technologies in this
sector is higher. Key technologies used for this problem
are Deep Learning, Machine Learning and Visualization.
As the product, an android mobile application is
developed. In this application the users should input their
location to start the prediction process. Data
preprocessing is started when the location is received to
the system. The collected dataset divided into 3 parts. 80
percent for training, 10 percent for testing and 10 percent
for validation. After that the model is created using LSTM
RNN for vegetable prediction and ARIMA for price
prediction. Finally, for given location profitable crop and
predicted future price of vegetables are shown in the
application. Other than the prediction, optimizing for
multiple crop sowing according to the user requirements
and visualizing cultivation and production data on map
and graphs are also given in the application. This paper
elaborates the procedure of model development, model
training and model testing.
Keywords : Machine Learning, Android Application, Data preprocessing, LSTM, RNN, ARIMA, Linear Programming, Visualization, Polygons.