The problem Automated Precision Agriculture solves

Recently Farmer Suicides and Protests are all over the news. They have been committing suicides under pressure because of debts and money pressure. The main reason behind these problems is that they are not getting proper crop yield, sometimes their whole crop is destroyed by pest diseases, and also because of using primitive techniques to irrigate the field which results in overuse of water. So as a result a lot of freshwaters also gets wasted. This has been our major objective behind the project. We will be providing a complete package to the farmers to increase their Crop Yield by at least 40% and to use almost 50 per cent less water and also detect the diseases. Growing crops is a beautiful activity which makes a farmer proud of himself, for he has created a new life. Despite its beauty though, crop production requires varying farm activities and constant maintenance in order to provide a high and healthy yield.

Challenges we ran into

We faced problem in setting up the IoT module, also we faced difficulty in finding the datasets of crop data for training the model like there were many null values in the dataset it took a lot of time to preprocess the data. It was difficult to find the best algorithm to achieve maximum accuracy, we tried three different algorithms and then came up with the conclusion that Deep Neural Networks was the bast model to achieve maximum accuracy so it took a lot of time.