Farmer Assistant

Abstract

Agriculture plays a very key role in the growth of a country like Pakistan where quarter of its GDP is produced by agriculture every year. Top agricultural countries in the world with the passage of time evolve their agriculture with the technology. While in contrast to that, the problem is that Pakistan is still using the conventional agricultural techniques for their farming and not taking advantage from the latest technology. There is not any online platform that provides farmers of Pakistan that which crop is suitable according to their soil, when to use fertilizer, about weather forecast and awareness of technology for farming. Due to unavailability of any platform or guidance, farmers take random decision based on their knowledge without considering many factors like climate change and ultimately these decisions sometimes lead towards the loss and this loss in a way effects the agricultural rate of Pakistan. The problem of finding the right crop for the right soil is solved if we provide a platform where we recommend farmers that which crop is suitable according to your soil by taking some input regarding that soil. By using that platform guidance and awareness to farmers also be provided. Machine learning is used for the recommendation of crop. Different classification algorithms K Nearest Neighbour, Decision Tree, Logistic Regression, Support Vector Machine and Random Forest are used for the recommendation system. The best accurate algorithm is further used for recommendation. Further system is deployed into a mobile application which is farmer friendly and has an interactive outlook