IBM Intern on Big Data for Smarter Cities

Name: Vinicius Costa Villas Boas Seguras
School: Pontificia Universidade Catolica do Rio de Janeiro

You’ve been involved with smarter cities projects in Rio de Janeiro. Tell me more about what you’ve been working on for the City.

In Rio de Janeiro, tropical storms are not uncommon, especially during summer. These can greatly impact the city’s day-to-day operations, due to flooding, landslides, mudslides, traffic jams, and so on. IBM has a partnership with Rio de Janeiro’s Center of Operations (COR), a city-wide monitoring center, to monitor weather in real time and help the city prepare in advance for heavy rain.

Recently, we’ve been working with COR’s meteorologists and IBM’s Deep Thunder team to improve assessment of the system’s forecasts. We are therefore proposing new evaluation metrics that better reflects the current COR workflow, so we can improve how PMAR (High Resolution Weather Forecast) is used inside COR. One of our next steps is to develop a new user interface so that the COR’s team can evaluate the forecast in real time and be more effective and efficient in its interpretations.

In 10 years, what do you think will be the key elements of a Smarter City?

Data and making sense of it — I think we will have more and more sensors, generating more and more data. This will enable the creation of a highly detailed, multi-faceted map of the city. This is closely related to IBM’s 5 in 5, predicting a future in which we could think about cars that can “feel” the asphalt and use this information to guide repair services. We could think about cameras that “see” traffic jams and cross this data with those generated by sensors that “smell” CO2 emissions or that “hear” traffic noises, to redirect the traffic accordingly. Of course, all these sensors depend on the “brain” making sense of the data and acting on it.

Another great source of data is people themselves. The internet already allows people to frequently express themselves in many different ways. Waze uses this kind of user-generated information (alongside mobile phone’s sensors) as a community-based traffic information system. Daniel Lemes (last week’s Intern Spotlight) uses Twitter data to capture sentiment regarding Brazil’s soccer team. I think this tendency will not stop — we can expect more social, crowd-sourced applications to generate useful data.

How do you hope to apply your studies at PUC-Rio and IBM experience toward a future career?

I believe that the best way to explore data and extract meaningful lessons from it is not through automatic processing alone. Rather, I feel that the best insights come from the combination of automatic data processing and human analysis capabilities. To me, data visualization lies at this intersection and is crucial to bridge the gap between the two. In addition, it is a powerful communications tool that is essential for the sharing of acquired knowledge. In my work at IBM and studies at PUC-Rio, I focus precisely on data visualization, combining Human Computer Interaction (HCI) with Computer Graphics (CG). I see great potential to continue exploring this field in future IBM Research work.


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