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Dr. Rajesh Bhaskar Survase is an Associate Professor in the Department of Geography (Earth Science) at Eknath Sitaram Divekar College, affiliated with Savitribai Phule Pune University, Maharashtra, India. His research interests include Geospatial Technologies, Climate Studies, Environmental Monitoring, Remote Sensing, and Weather Analytics.
Precise weather forecasting is essential for contemporary agriculture, as climatic conditions directly affect crop development, irrigation strategies, insect control, and overall farm efficiency. Conventional weather forecasting systems frequently encounter difficulties in delivering localised, real-time, and actionable information to farmers. Cloud-integrated weather prediction systems utilise cloud computing, artificial intelligence, machine learning, Internet of Things (IoT) devices, and big data analytics to gather, process, and analyse extensive meteorological and agricultural data. These advanced systems provide real-time meteorological observation, predictive analysis, and decision-making support for precision agriculture. This chapter examines the architecture, technology, methodology, applications, problems, and future trends of cloud-integrated weather prediction systems in agriculture. It emphasises the capacity of cloud-based forecasting tools to enhance crop management, mitigate climate-related risks, and promote sustainable agriculture practices.