Intelligent Adaptive Control

The Intelligent Adaptive Control (IAC) concept is a framework for integrating machine learning within both the design process and post-occupancy building system for socio-environmental adaptation.  The IAC links together three parallel design development platforms (physical, simulation, and analysis) to integrate optimal adaptive conditions for environmental and/or social performance criteria into the building facade.  The building envelope is one that is dynamic and adaptive to varying external and internal conditions, with embedded material intelligence as well as integrated sensor networks for distributed control and modulation.  This framework allows for a variety of socio-environmental conditions to be simulated both digitally and physically to enable designers to make informed decisions about the building envelope functions in the design process.  The physical test chamber is constructed with two representative volumes of outdoor and indoor conditions, divided by various dynamic building envelope prototypes.  The baseline prototype utilized for calibration of the IAC policy is an electrochromic film that responds to electric charge, which is actuated by an algorithm that integrates photometric sensing data through an Arduino.

Collaborators

Chris Lasch, Pierre Lucas, Clayton Morrison, Kuo Peng, Alice Wilsey, Long Long