Weather Wise AI: An AI-Driven Approach for  Real-Time Weather and Air Quality Forecasting for  Smart Travelling

Author(s)	Ms. Rutuja Rama Patil, Ms. Sakshi Suhas Chougule, Ms. Sakshi Vinod Potdar, Ms. Karishma Tamboli
Country	India
Abstract	Weather Wise AI is a smart weather and travel aid system that combines deep learning and real-time data to offer precise environmental information and customized travel advice. The system employs a hybrid LSTM + Conv1D model for temperature forecasting, which is more accurate and captures trends better than conventional models such as isolated LSTM, GRU, and 1D CNN. For air quality classification, a ResNet-based model is utilized to process sky images, providing higher accuracy compared to MobileNetV2. The app also makes use of APIs like OpenWeatherMap and Gemini to provide real-time forecasts, safety advice, and travel recommendations. Built using Streamlit, the web interface is interactive, lightweight, and easy to use. This single platform allows the user to make weather-informed, informed travel choices, providing a real-world application of AI in environmental surveillance and intelligent tourism.
Keywords	Artificial Intelligence, Weather Forecasting, Air Quality Prediction, Deep Learning, LSTM + Conv1D, ResNet, Travel Recommendation System, Streamlit, Environmental Mon itoring, Smart Tourism, Real-time Data Analysis.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-05-11

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