TY - GEN
T1 - A Computational Method for Tracking the Hygroscopic Motion of Wood to develop Adaptive Architectural Skins
AU - Abdelmohsen, Sherif
AU - Massoud, Passaint
AU - El-Dabaa, Rana
AU - Ibrahim, Aly
AU - Mokbel, Tasbeh
N1 - Funding Information:
The authors are grateful for the funding provided to the American University in Cairo by the Bartlett’s Fund for Science and Engineering Research Collaboration.
Publisher Copyright:
© 2018.
PY - 2018
Y1 - 2018
N2 - Low-cost programmable materials such as wood have been utilized to replace mechanical actuators of adaptive architectural skins. Although research investigated ways to understand the hygroscopic response of wood to variations in humidity levels, there are still no clear methods developed to track and analyze such response. This paper introduces a computational method to analyze, track and store the hygroscopic response of wood through image analysis and continuous tracking of angular measurements in relation to time. This is done through a computational closed loop that links the smart material interface (SMI) representing hygroscopic response with a digital and tangible interface comprising a Flex sensor, Arduino kit, and FireFly plugin. Results show no significant difference between the proposed sensing mechanism and conventional image analysis tracking systems. Using the described method, acquiring real-time data can be utilized to develop learning mechanisms and predict the controlled motion of programmable material for adaptive architectural skins.
AB - Low-cost programmable materials such as wood have been utilized to replace mechanical actuators of adaptive architectural skins. Although research investigated ways to understand the hygroscopic response of wood to variations in humidity levels, there are still no clear methods developed to track and analyze such response. This paper introduces a computational method to analyze, track and store the hygroscopic response of wood through image analysis and continuous tracking of angular measurements in relation to time. This is done through a computational closed loop that links the smart material interface (SMI) representing hygroscopic response with a digital and tangible interface comprising a Flex sensor, Arduino kit, and FireFly plugin. Results show no significant difference between the proposed sensing mechanism and conventional image analysis tracking systems. Using the described method, acquiring real-time data can be utilized to develop learning mechanisms and predict the controlled motion of programmable material for adaptive architectural skins.
KW - Adaptive architecture
KW - Hygroscopic properties of wood
KW - Programmable materials
KW - Real-time tracking
UR - http://www.scopus.com/inward/record.url?scp=85114396051&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85114396051
SN - 9789491207167
T3 - Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe
SP - 253
EP - 262
BT - Computing for a better tomorrow
A2 - Kepczynska-Walczak, Anetta
A2 - Bialkowski, Sebastian
PB - Education and research in Computer Aided Architectural Design in Europe
T2 - 36th International Conference on Education and Research in Computer Aided Architectural Design in Europe 2018
Y2 - 19 September 2018 through 21 September 2018
ER -