College
Buchtel College of Arts and Sciences
Date of Last Revision
2026-05-28 08:01:31
Major
Computer Science
Honors Course
CPSC 498
Number of Credits
2
Degree Name
Bachelor of Science
Date of Expected Graduation
Spring 2026
Abstract
Air quality impacts public health, environmental sustainability, and quality of life. However, accurate and easily accessible short-term air quality forecasting is challenging to find. This project, Clear Skies, presents a machine learning–based system for forecasting next-day Air Quality Index (AQI) levels across regions in Ohio. By using historical pollutant data with variables such as temperature, humidity, wind speed, and atmospheric pressure, the system finds relationships that traditional statistical models often don’t show.
Machine learning models are evaluated alongside AI techniques to find the environmental factors that influence AQI predictions. This helps reduce the “black box” nature of many AI systems and improves trust and usability for non-expert audiences. Additionally, the project considers sustainability by using efficient models with lower computational cost.
Forecast results are presented through an interactive dashboard hoping to make air quality information accessible to the public. Clear Skies hopes to demonstrates AI can support environmental awareness, public health decision-making, and community engagement.
Research Sponsor
John Hoag
First Reader
Philip Marcin
Second Reader
Ronald Gelleny
Honors Faculty Advisor
Brian Bagotto
Proprietary and/or Confidential Information
No
Community Engaged Scholarship
No
Recommended Citation
Munn, Avery C., "Clear Skies" (2026). Williams Honors College, Honors Research Projects. 2238.
https://ideaexchange.uakron.edu/honors_research_projects/2238
Included in
Computational Engineering Commons, Computer and Systems Architecture Commons, Data Storage Systems Commons, Outdoor Education Commons