Research on a Real-Time Monitoring and Early Warning System for Abnormal Fluctuations in Agricultural Product Prices

Abstract

This study addresses the critical issue of price volatility in agricultural markets, which poses significant risks to food security, farmer incomes, and economic stability. The primary objective of this research is to design and evaluate a real-time monitoring and early warning system capable of detecting abnormal price fluctuations in agricultural products. The proposed system integrates big data analytics, machine learning algorithms, and cloud computing technologies to process real-time market data, including historical prices, supply chain information, and external factors such as weather conditions and policy changes. Key findings demonstrate that the system achieves high accuracy in identifying abnormal price trends and provides timely alerts, enabling stakeholders to take proactive measures. The implementation of this system holds substantial practical significance, as it supports policymakers, farmers, and traders in mitigating risks associated with price instability and fostering a more resilient agricultural market.