Enhancing Rainfall Prediction Accuracy Through Fog Computing
P. Umamaheswari, V. Ramaswamy · Advances in systems analysis, software engineering, and high performance computing book series · 2024
Rainfall prediction is a pivotal aspect of climate forecasting, influencing agriculture, water resource management, and disaster preparedness. This comprehensive review explores the integration of advanced algorithms and edge analytics within a fog computing framework to elevate the accuracy of rainfall predictions. The introduction outlines the significance of accurate rainfall predictions, the limitations of traditional methods, and the motivation for embracing fog computing, advanced algorithms, and edge analytics. A detailed examination of fog computing architecture underscores its decentralized nature and proximity to data sources, addressing challenges inherent in centralized models. The integration of edge analytics is discussed in depth, emphasizing its crucial role in preprocessing IMD data at the source. Insights gained from these implementations offer valuable perspectives on the practical implications, successes, and challenges associated with these methodologies.