Thesis Proposal for the Topic "A Quiet Museum? Prediction of Visitor Density at Staatliches Naturkundemuseum Karlsruhe"

Topic Description

For disabled people, visitor density at a museum is an access
concern. However, although museums do collect visitor numbers, it is often
not processed for public information, and cannot be used for visit planning.
This work is in collaboration with the Staatliches Naturkundemuseum Karlsruhe,
and aims to provide information about visitor density to inform potential
visitors about the anticipated business on a given day. The main goal of this thesis
is twofold: (1) It aims to develop aMachine Learning (ML) model that predicts
numbers of visitors for a given day at the Naturkundemuseum Karlsruhe. The underlying
ML model will be based on on historic data of ticket sales in conjunction
with other data such as weather information, past experiences of museum staff,
or concurrent events. (2) The thesis will visualize the data in an accessible way,
and one that adequately communicates uncertainty and ensures the prediction
is explainable.
This thesis is expected to contribute to the understanding of accessibility of
public spaces, and to improve access to leisure for disabled people. It is part of
the Real-World Lab Accessibility, also see http://www.accessibility.kit.edu.

Task Summary

1. Requirements Analysis
   Understand
   visitor density, accessibility,
   and the state of the art in prediction
   and visualization thereof.
2. ML Model Development
   Data
   analysis and model development to
   predicts visitor figures.
3. Frontend + Backend Development
   Implement a web application
   that displays predictions of visitor
   density at the museum.
4. Evaluation
   Evaluation of the prediction
   quality. Optional: Evaluation
   of the website with users (e.g., museum
   visitors and staff).

Requirements

• Programming
• Data Analysis
• Machine Learning
• Web
• HCI