Rio Innovation Hub launches new Design Challenge on “Sensing and the City”

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Rio Innovation Hub launches new Design Challenge on “Sensing and the City”

March 23, 2016

Another Design Challenge was launched in the scope of the Columbia Innovation Hub in collaboration with the Federal University of Rio de Janeiro (UFRJ). On March 21st, Dean Mary Bounce (Fu Foundation School of Engineering and Applied Sciences, Columbia University), Professor Fred Jiang (SEAS, Columbia University), and Professor Romildo Filho (COPPE, UFRJ) officially launched the second design challenge focused around bringing innovative engineering, sensing technologies, Internet-of-Things, and big data analytics to the multi-faceted challenges of smart cities. Students convened in Rio de Janeiro, and at Columbia University, in New York, to present remote sensing innovative solutions to the multi-faceted challenges of Rio de Janeiro.

In 2015, the Hub launched its first international collaboration creating the Center COPPE-Columbia for Urban Solutions, located in Rio de Janeiro, at Ilha do Fundao. “Sensing and the City” is the second challenge of this project, and supports the development of interdisciplinary technology-driven solutions in areas such as urban environment, transportation, energy efficiency, public health and renewable energy.

“Sensing and the City” kicks off

The Challenge’s kick-off brought together Columbia faculty in New York and specialists from Rio through live streaming. Each of the academics and specialists presented their projects within their fields of work and research. Pedro Arias, from Rio’s City Hall, presented how PENSA, Rio’s Big Data unit, cross-analyzes available data and come up with solutions for the city’s everyday operational problems.  Fred Jiang, Assistant Professor at SEAS (Columbia), who developed a project on enhancing the campus’ energy efficiency, argued that “calculating one’s average energy consumption by one’s footprint could enable, in the future, the collection according to the amount of energy one spends on campus. And that is one of the project’s motivation: to hold people accountable for their actions.” Romildo Filho, Professor at COPPE, UFRJ, presented the positive impacts from Fundo Verde, a fund created by State of Rio’s government that foments data collection on sustainability and supports projects focused on improving mobility, clean energy sources and optimizing water consumption.

The kick-off meeting was followed by a team forming session, which defined the candidate groups to be in the competition. On the next day (22), teams presented their ideas on a pitch session, where a jury commission, composed by Thomas Trebat, Professor Fred Jiang, Professor Fernando Rochinha (COPPE, UFRJ), Professor Andrew Smyth (SEAS), Professor David Benjamin (Graduate School of Architecture, Planning and Preservation), Professor Andrew Rundle (Mailman School of Public Health) and Professor Svebor Karaman (SEAS) selected the best projects to be part of the second Design Challenge.

Next phase: presenting the prototypes

Nine teams were selected to the next phase of the challenge.  The selected projects, besides covering a diversity of themes, brought original and creative proposals addressing the smart cities biggest challenges. Students presented a diverse range of ideas, such as solutions to monitor weather trough sensors installed on public buses, and a thermal energy harvesting system pilot in the concrete used to build bike lanes. All nine finalists will present their final prototype on April 20. 2016.

 

List of teams advancing to the second phase of Sensing and the City Design Challenge:

 

  1. Wearable/intelligent vest for prolonged sun exposure

  2. Microclimatic changes related to bus traffic

  3. Zika breeding ground mapping drone

  4. Energy harvesting concrete from bike lanes

  5. Individual monitoring device with air quality sensors

  6. Solar lighting system for smart building

  7. Weather conditions monitoring through a bus sensor network

  8. Novel vibration sensor for low-power landslide detection

  9. Partition-based cooling using human-centric tracking