iEnEx.io is framework/tool for assessing integrated energy and exposure to ambient pollution addressing climate, health, and social inequity as interconnected problems within the built environment. iEnEx.io captures spatial disparities of interlinked households' energy burden* and their exposure** to airborne fine particulate matters (PM2.5 concentrations) in supporting cooling energy-efficiency goals of cities. iEnEx.io is developed upon a five-step workflow that brings array of big data sources to develop the energy-exposure model for cities.

* Energy affordability of households for paying energy costs** Exposure to intra-urban PM2.5 concentrations is calculated through development of spatiotemporal Land Use Regression (LUR) modeling approach enhanced by machine earning techniques.
iEnEx.io: Integrated Energy and Exposure to Ambient Pollution Assessment Publication Link
Team: Mehdi Ashayeri, Ph.D. Assistant Professor of Architecture. Urban Intelligence and Integrity Lab (URBiiLAB), Southern Illinois University (SIU)Narjes Abbasabadi, Ph.D. Assistant Professor of Architecture. Sustainable Intelligence Lab (SILab), University of Washington (UW)