Artificial Intelligence in Crop Management: Predictive Analytics for Soil Health and Weather Patterns

Khushboo Choubey; Mallika Dwivedi; Zeba Vishwakarma

doi:10.15680/IJIRCCE.2023.1103117

Khushboo Choubey Department of Computer Science and Engineering, Baderia Global Institute of Engineering and Management, Jabalpur, Madhya Pradesh, India
Mallika Dwivedi Department of Computer Science and Engineering, Baderia Global Institute of Engineering and Management, Jabalpur, Madhya Pradesh, India
Zeba Vishwakarma Department of Computer Science and Engineering, Baderia Global Institute of Engineering and Management, Jabalpur, Madhya Pradesh, India

DOI: https://doi.org/10.15680/IJIRCCE.2023.1103117

Keywords: Artificial Intelligence in Agriculture, Predictive Analytics, Soil Health Monitoring, Weather Pattern Prediction, Crop Management, Machine Learning in Farming, Precision Agriculture.

Abstract

The global demand for food is escalating at an unprecedented rate, driven by population growth, urbanization, and changing dietary preferences. Traditional agricultural practices, although effective to a certain extent, are increasingly unable to meet this rising demand. In this context, the integration of advanced technologies such as artificial intelligence (AI) into agriculture presents a promising solution. AI has the potential to revolutionize crop production by enhancing yield, optimizing resource use, and mitigating the impacts of climate change. This research paper explores the current state of AI applications in agriculture, focusing on their impact on crop growth. The proposed method utilizes machine learning algorithms to analyze various parameters influencing crop growth. The results demonstrate a high degree of accuracy, with an accuracy rate of 97.6%. The mean absolute error (MAE) is 0.403, and the root mean square error (RMSE) is 0.203, indicating the model's robustness and reliability. Through case studies and empirical data, this paper aims to provide a comprehensive overview of how AI can transform crop production and contribute to global food security.