In Acadia National Park, Cadillac Mountain has had problems accommodating the increase in visitors. In 2021, the National Park Service (NPS) implemented a reservation system that would help regulate the flow of visitors. A WPI Data Science Graduate team, in the spring of 2022, created a machine learning model that would predict the length of stay of visitors on the summit based on the weather. From the WPI model's predictions, the NPS could then adjust the number of reservations released for any specific day to optimize the summit parking lot. Examining any discrepancies between our observed dwell times and the model’s predictions would show areas of limitations and need for further improvement.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Martin-Nucatola, Nathalie
• Burns, Aidan
• Guilfoyle, Caitlin
• Reynolds, Matthew

Subject

• Sustainability
• Infrastructure
• Project-Based Learning

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-072822-105514
• 71126

Stichwort

• Machine Learning
• Reservation System
• Acadia
• Big Data
• Cadillac Mountain
• National Parks

Advisor

• Davis, Jason
• Bianchi, Frederick W.

Year

• 2022

Center

• Acadia National Park, Maine Project Center - IQP

Sponsor

• National Park Service

UN Sustainable Development Goals

• 9 - Industry, Innovation and Infrastructure

Date created

• 2022-07-28

Resource type

• Interactive Qualifying Project

Source

• E-project-072822-105514

Rights statement

• In Copyright

Zuletzt geändert

• 2022-12-20