Final Five

with Conrad Tucker, assistant professor of engineering design and industrial engineering at Penn State

This summer, for his second consecutive year, Conrad Tucker spent eight weeks participating in the U.S. Air Force Summer Faculty Fellowship Program (AF SFFP). He continued his study of social media data while developing a proposal, "Capturing Energy Utilization Patterns by Mining Image Data Streams in Large Scale Social Media Networks." Conrad Tucker 

As an industrial engineer and an academic, what have been the benefits of participating in the AF SFFP?

The AF SFFP provides an excellent venue to engage in theoretical work that addresses real-world problems. As the world shifts toward more digital, data-driven solutions, it is imperative that industrial engineers and academicians evolve accordingly.

The AF SFFP has granted me the unique opportunity of collaborating with researchers with new dimensions of expertise, such as smart meter simulations and energy grid optimization. These collaborative efforts have also impacted students, as they themselves are presented with opportunities to collaborate with other students and expand their network.

Is the most valuable data found in social media hidden or staring us in the face?

"Hidden in plain sight" would be an appropriate response to this question. The challenge is not with the presence of data; it is how to make sense of data. This is a nontrivial problem, as real-world data is messy and constantly evolving. Therefore, novel methods are needed to mine data in order to make informed decisions.

How can we use social media to predict future energy use?

If we already knew the answer to that, then it wouldn't be an exciting problem to work on. That question itself is what motivates this AF SFFP, and we look forward to exploring ways to answer that question. Preliminary research findings during my 2014 SFFP have revealed interesting correlations between social media messages and electricity utilization patterns. Research findings have been published in the 2014 IEEE Big Data Conference, with a journal paper currently under review.

What professions or organizations would best be able to use your findings?

A fundamental understanding of current and future energy demands impacts all facets of society. From the government level, understanding how electricity is utilized on an individual level will help influence the strategic energy investments that are made for the future. For energy enterprises, the ability to model and predict energy demands on an individual level using social media network models would reduce the costs associated with smart plugs or smart meters.

On an individual level, having real-time feedback relating to one’s energy utilization pattern has the potential to influence behavior. It has been shown that individuals change their energy consumption behavior in favor of reducing their carbon footprint when informed about their energy consumption patterns.

Have your students played a role in your analysis of social media data?

Students play a significant role in advancing technologies and shaping research. They are the future! My students, both immediately associated with our research efforts and those that are in my classes, are active participants in the generation of big data from social media networks. The question we should be asking now is: What is the next big thing that will transform our lives and make society more efficient as a whole?

– Interview by David Brandt 

David Brandt is the Web managing editor for IIE.