Date of Award
6-12-2023
Document Type
Thesis
Publisher
Santa Clara : Santa Clara University, 2023.
Department
Computer Science and Engineering
First Advisor
Silvia Figueira
Abstract
The WhetherWeather project is a comprehensive weather and traffic forecasting system that provides real-time insights and predictions. It utilizes Python programming language and various data sources, including Inrix data for traffic information and weather data from Meteostat. The system employs machine learning techniques, specifically XGBoost, to train models on historical data. Once trained, the models can accurately forecast traffic conditions based on weather data. To visualize the results, a Flask API is available, allowing users to access the system's functionalities through a web interface. For more information and to access the WhetherWeather website, visit WhetherWeather.org.
Recommended Citation
Voron, Lucas; Purvis, Graham; Weaver, Malcolm; and Kelleran, Josh, "Whether-Weather" (2023). Computer Science and Engineering Senior Theses. 267.
https://scholarcommons.scu.edu/cseng_senior/267