Intelligent Weather Forecasting System based on Internet of Things for Smart Cities

Accurate weather prediction is essential for guiding decisions in fields such as farming, transport, and disaster response. Traditional forecasting methods, although useful, face significant limitations in accuracy and responsiveness, especially in rapidly changing urban environments. This article examines the pairing of Artificial Intelligence (AI) and the Internet of Things (IoT) as an innovative strategy to improve predicting abilities in smart cities. AI methods, such as deep learning and machine learning, are capable of analyzing complex weather patterns, while IoT networks provide real-time environmental data through distributed sensor networks. The study reviews recent literature and highlights key benefits such as improved prediction accuracy and early warning systems. It also discusses challenges including data quality, computational demands, and model transparency. Finally, emerging trends such as explainable AI and crowdsourced sensing are examined as pathways to more adaptive and intelligent forecasting systems. The findings suggest that AI-IoT integration offers a promising framework for next-generation weather prediction in smart urban environments.

• Publication year

  2025

• Venue

  2025 5th International Conference on Applied Automation and Industrial Diagnostics (ICAAID)

• Publication date

  2025-11-18

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICAAID68975.2025.11358251
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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