Assisting Farmers in Optimizing their Crop Yield

Abstract

Effective Cultivation and yield of a crop depend on the type of soil, crop selection, water availability, and weather condition. Farmers face many challenges to identify the crop that best suits their land. In this paper, we propose AgriBot, a farmer's assistant that captures various dependent factors of the agricultural land and predicts the best-suited crop that maximizes the yield. AgriBot moves along the field to capture all the parameters that impact cultivation. The exact location of the bot is known using Geotagging. It uses various sensors to capture temperature, humidity, pH, moisture level in the soil and uses image processing to identify the type of soil (black soil, red soil, etc). On the captured data, predictive analytics is applied using Artificial intelligence to suggest the crops that could be grown and their ideal conditions. AgriBot’s web app uses the Government's API to display various agricultural schemes, daily prices of agricultural commodities in different markets, etc.