A Computational Method for Tracking the Hygroscopic Motion of Wood to develop Adaptive Architectural Skins

Abstract

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.