This project is supported by PI Wangda Zuo at Pennsylvania State University. For more information, please visit the project’s webpage at the PSU’s SBS Laboratory here.

The goal of this project is to develop a new planning framework for smart, connected and sustainable communities that allows meeting such zero energy, zero outage, and zero congestions goals by optimally deciding on how, when, and where to deploy or upgrade a community’s infrastructure. By bringing together interdisciplinary domain experts from data science, electrical engineering, and civil and architectural engineering, this research will yield several innovations:

1. Novel big data techniques for faithfully creating spatiotemporal models for smart communities that integrate data from heterogeneous sources and shed light on the composition and operation of a given smart community;
2. Novel, data driven performance metrics that advance powerful mathematical tools from stochastic geometry to explicitly quantify the health of smart communities via tractable notions of zero energy, zero outage, and zero congestion;
3. Advanced analytical tools that bring forward novel ideas from optimization theory to devise the most effective strategies for deploying, upgrading, and operating various community infrastructure nodes, given the scale, dynamics, and structure of both the data and the community;
4. A virtual smart community testbed that can accurately reconstruct, simulate, and evaluate the theoretical framework by leveraging open nonproprietary real world big data sets.

• Historic Green Village
• Amzur Technologies
• Virginia Tech

U.S. National Science Foundation