Serverless data processing and forecasting system using cloud computing

This paper presents a serverless data processing architecture designed for real-time weather forecasting using Google Cloud Functions, BigQuery, and integrated machine learning models. The system enables scalable ingestion of weather data, efficient storage, and dynamic visualization through an interactive dashboard. In addition to predictive analytics for temperature, AQI, and humidity, the system includes cost opti- mization techniques and real-time alerts. This work highlights the benefits of serverless computing for data-intensive applications and offers a practical, low-latency solution suitable for smart city and environmental monitoring use cases.