| Sumario: | The advancements and availability of low-cost, low-energy sensors have improved energy and environmental sensing exponentially. Besides the millions of sensors used for monitoring, the improved accuracy of these sensors offer greater resolution for modeling 'what-if' scenarios in near real-time harnessing the vast computational power. Similarly, big data analysis has enabled city-scale modeling of energy and environmental impact using, among others, energy-efficient 'smaller' machine learning algorithms and/or physics-based modeling approaches. Coupled with interactive data visualization including Virtual Reality (VR), urban-scale energy and environmental systems modeling has become an exciting niche at the intersection of computer science and urban / architecture / mechanical engineering disciplines. The 1st International Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization (UrbSys) Workshop intends to capture recent exciting work by research experts, from U.S. universities and U.S. national laboratories, at this nexus that supports sustainable urban systems' design and engineering through state-of-the-art sensing, controls, modeling, and visualization.
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