An efficient data collection tool for crop recommendations model using Robotic Process Automation

Farmers in rural areas make the crop decisions based on the forecasts and collective knowledge transferred over generation within their community. Farmers who rely on their own prediction for farming and other agricultural activities lead farmers to go through huge loss. A farmer take decision on which crop to be grown is mostly based on intuition and other factors like profit based crop and what their ancestors followed on choosing the crop. Due to changes in soil structure and climate condition farmers tend to make wrong decision. Crop recommending models involve huge collection of data's from various sources like soil data, weather data and historical yield data. It involves multiple stages of data collection, processing and analyzing. In this paper we proposed an efficient data collections tool for crop recommendations model using RPA.RPA (Robotic Process Automation) is a tool used for collecting data from various sources by automatically. By implementing RPA for crop recommendation model ensures that data's are to date and accurate. It also saves time and increase efficiency. In this proposal we presented an efficient predictive model that uses Robotic Process Automation (RPA) by developing software robots to automate the repetitive tasks and processes using UiPath tool. RPA is commonly used in healthcare and finance sectors. We found use cases of RPA in agriculture domain as well. On the basic of existing work this paper focus on RPA in Agriculture to automate data collection, processing and analysis. A Challenging work in Crop Recommendation is collecting metrological data and climate data and making connecting between them. This research paper proposes an efficient predictive modelto choose the best crop to grow by integrating RPA into Crop recommendation model. © 2023 IEEE.