Smart Cities at the Nexus of Emerging Data Technologies and You

Smart Cities at the Nexus of Emerging Data Technologies and You

Smart Cities at the Nexus of Emerging Data Technologies and You

One of the most significant characteristics of the evolving digital age is the convergence of technologies. That includes information management (databases), data collection (big data), data storage (cloud), data applications (analytics), knowledge discovery (data science), algorithms (machine learning), transparency (open data), computation (distributed computing: e.g., Hadoop), sensors (internet of things: IoT), and API services (microservices, containerization). One more dimension in this pantheon of tech, which is the most important, is the human dimension. We see the human interaction with technology explicitly among the latest developments in digital marketing, behavioral analytics, user experience, customer experience, design thinking, cognitive computing, social analytics, and (last, but not least) citizen science.

Citizen Scientists are trained volunteers who work on authentic science projects with scientific researchers to answer real-world questions and to address real-world challenges (see discussion here). Citizen Science projects are popular in astronomy, medicine, botany, ecology, ocean science, meteorology, zoology, digital humanities, history, and much more. Check out (and participate) in the wonderful universe of projects at the Zooniverse (zooniverse.org) and at scistarter.com.

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In the data science community, we have seen activities and projects that are similar to citizen science in that volunteers step forward to use their skills and knowledge to solve real-world problems and to address real-world challenges. Examples of this include Kaggle.com machine learning competitions and the Data Science Bowl (sponsored each year since 2014 by Booz Allen Hamilton, and hosted by Kaggle). These “citizen science” projects are not just for citizens who are untrained in scientific disciplines, but they are dominated by professional and/or deeply skilled data scientists, who volunteer their time and talents to help solve hard data challenges.

The convergence of data technologies is leading to the development of numerous “smart paradigms”, including smart highways, smart farms, smart grid, and smart cities, just to name a few. By combining this technology convergence (data science, IoT, sensors, services, open data) with a difficult societal challenge (air quality in urban areas) in conjunction with community engagement (volunteer citizen scientists, whether professional or non-professional), the U.S. Environmental Protection Agency (EPA) has knitted the complex fabric of smart people, smart technologies, and smart problems into a significant open competition: the EPA Smart City Air Challenge.

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The EPA Smart City Air Challenge launched on August 30, 2016. The challenge is open for about 8 weeks.

 



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