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Exploring Big Data Analytics To Plan For Smart Communities Of The Future
February 9, 2017

We already have smartphones, smart clothing, and smart appliances, but emerging “smart cities” are still a concept of our imagined future.

A Virginia Tech team wants those smart cities to feature zero energy, zero outage, and zero congestion. Their tools: big data and interdisciplinary technology.

Walid Saad (right) and Harpreet Dhillon (left), assistant professors of electrical and computer engineering, are co-PI’s on a $1.4 million National Science Foundation grant along with Naren Ramakrishnan, professor in computer science (not pictured). They will be working with Ph.D. candidates Omid Semiari (left), Mohammad Mozaffari (middle) and postdoctoral associate Mehrnaz Afshang (right) to develop a new planning framework for smart, connected, and sustainable communities.

Walid Saad, the Stephen O. Lane Junior Faculty Fellow and assistant professor in electrical and computer engineering; Harpreet Dhillon, assistant professor of electrical and computer engineering; and Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering and director of the Discovery Analytics Center in the Department of Computer Science, are leading a three-year, $1.4 million National Science Foundation (NSF) grant to develop a new planning framework for smart, connected, and sustainable communities.

The project, supported by the NSF’s Critical Techniques, Technologies, and Methodologies for Advancing Foundations and Applications of Big Data Sciences and Engineering program, is entitled “Big data analytics for optimized planning of smart, sustainable, and connected communities.” Virginia Tech is collaborating on this project with a civil and environmental engineer from the University of Miami, who has a $953,000 share.

To meet these zero-energy, zero-outage, and zero-congestion goals, the team is strategizing the best ways to maintain, upgrade, and deploy community infrastructure.

Efficiently managing existing amenities, such as communication networks, transportation systems, and power grids, is a convoluted task. The issues multiply when researchers start juggling how, when, and where to install new infrastructure, such as renewable energy sources, electric vehicles, and advanced wireless communication and sensor systems.

To inform these decisions, the research team is collecting and analyzing massive volumes of community data from many different sources – including real-world big data sets from Virginia Tech, a zero-energy community in Florida, and the U.S. Department of Energy – that will include energy use, traffic patterns, communication demands, and other socio-technological information. Using this data, the team is building an open-access virtual testbed that will give them the ability to create and test simulations of smart communities.

“It’s a big, complicated problem, and we need to rethink the way we process and visualize the data,” Saad said. “We also need to have more flexible metrics that can respond to huge amounts of data in order to monitor the performance of the community infrastructure.”

To tackle this unwieldy problem, which will involve new mathematical techniques and real-world experiments, the research team is tapping into a wide group of thinkers by hosting a smart community big data challenge event. The educational portion of the plan includes new courses on big data, which will draw graduate and undergraduate students to big data and smart communities research.

By bringing together interdisciplinary domain experts from data science, electrical engineering, and civil and architectural engineering, this project aims to develop novel data techniques, models, and performance metrics to shed light on the inner workings of tomorrow’s smart communities.

This story can be found on the Virginia Tech News website.

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