Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
FOLLOWING USER TRACES IN URBAN CONTEXT: STIGMERGIC APPROACH AND A MACHINE LEARNING IMPLEMENTATION
Download
10541761.pdf
Date
2023-4-13
Author
Akyürek, Handan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
69
views
1
downloads
Cite This
Designers are responsible for responding to the user’s needs and expectations regarding the design output. Hence, the design feedback mechanism between the user and the designer is crucial to avoid any mismatch between the designer’s decisions and the user’s needs. On the other hand, displaying the user’s engagement with the design output provides a reliable communication ground for both designer and the user. Integrating state-of-art visualization mediums with the recent participatory design methods creates highly sophisticated communication platforms where the users experience the design ideas more immersively, which gives potential data regarding their engagement with the design ideas. However, these data are not authentic enough because they are retrieved from the user’s engagement with the representation of the design outcome, not the real one. In this context, this thesis focuses on the user's physical traces during the post-occupancy phase as the representation of their engagement with the design output. It formulates a feedback mechanism to understand, learn and provide from the user’s preferences to enhance future projects. vi Desired paths in urban contexts were selected to examine the user’s physical traces to represent the user's preferences regarding the designer's design decisions. A stigmergic approach was created to investigate their self-emerging and spatiotemporal characteristics. Finally, the desired paths were represented as environmentally mediated signs and formalized as a design feedback mechanism to utilize a machine learning algorithm to create a prediction tool in the urban design context.
Subject Keywords
User experience, design feedback, desired paths, stigmergy, machine learning
URI
https://hdl.handle.net/11511/103270
Collections
Graduate School of Natural and Applied Sciences, Thesis
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
H. Akyürek, “FOLLOWING USER TRACES IN URBAN CONTEXT: STIGMERGIC APPROACH AND A MACHINE LEARNING IMPLEMENTATION,” M.S. - Master of Science, Middle East Technical University, 2023.