International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Agriculture is a vital sector that directly influ- ences a country’s economy and food security. Crop pre- diction plays an important role in helping farmers make informed decisions about sowing, irrigation, and harvest- ing. Traditional prediction methods are often inaccurate due to changing weather, soil variations, and pest attacks. Artificial Intelligence (AI) techniques such as Machine Learning (ML) and Deep Learning (DL) provide new ways to analyze complex agricultural data for better yield prediction. This review paper discusses recent research developments in AI-based crop prediction systems, com- monly used algorithms, data sources, methodologies, and challenges. It also highlights the emerging trends such as IoT-based smart farming, real-time data processing, and the integration of AI with remote sensing technologies for more accurate and scalable prediction models

Keywords: Artificial Intelligence (AI), Machine Learning, Deep Learning, Crop Prediction, Precision Agriculture, Re- mote Sensing, IoT Sensors, Weather Data Analysis, Yield Forecasting, Smart Farming.

Downloads: | DOI: 10.17148/IJARCCE.2025.141137