AI Explainable for Forecasting Crop Production Affected by Weather
Soumik Chakraborty, Sheetesh Kumar, Bharat Tripathi, Madan Lal Saini
Abstract
This paper explores the field of Crop prediction technology, looking at its uses and underlying principles. The work of crop prediction is recommending the best crops to cultivate depending on a number of variables, such as cost, upkeep, weather predictions, and available land space. The concept of ”Growing Tomorrow's Harvest Today” is presented as a way to help people and farmers maximize their approaches to crop growth. This method maximizes agricultural productivity while limiting resource use by providing customized crop suggestions via the use of sophisticated algorithms and real-time data analysis. Unpredictable weather patterns, environmental concerns, and the requirement for sustainable farming techniques define the modern agricultural landscape. In order to solve these issues, our project provides an approachable instrument for making knowledgeable decisions in agriculture. The paper is organized to give a thorough overview of the Crop Prediction System, its relevance, and its potential to transform the fields of agriculture and resource management. It explains the project's goals, tasks, and timeframe.