AI for Predictive Analytics in Retail: Enhancing Inventory Management and Customer Engagement
Authors:-Nanjunda. M
Abstract- The increasing frequency and intensity of extreme weather events caused by climate change pose significant threats to global ecosystems, economies, and human lives. Traditional climate monitoring and forecasting systems, while valuable, often struggle to provide accurate, timely, and localized predictions. Artificial Intelligence (AI) has emerged as a powerful tool to enhance early warning systems by leveraging vast amounts of environmental, geospatial, and meteorological data. This paper explores how AI-based early warning systems can predict climate change-related phenomena and extreme weather events more effectively. It examines the integration of machine learning, deep learning, and data analytics in forecasting models, highlights real-world applications, and discusses the role of AI in disaster preparedness and climate resilience planning. The paper also addresses challenges such as data availability, model bias, and the need for transparent and ethical AI use. By improving accuracy and lead time in predictions, AI holds the potential to save lives, protect infrastructure, and inform policy decisions in an era of accelerating climate risks.
