I'd like to highlight the challenges of Smart Cities, addressed in a panel Monday Morning and a talk by Keith Marzullo on Tuesday afternoon. Roughly a smart city is using technology to improve services, for example, sensors everywhere or preparing cities for autonomous vehicles. The speakers highlighted a number of major challenges.
- There are 382 Metropolitan Statistical Areas in the US from New York to Carson City that totals 84% of the US population and 91% of GDP. Many cities share similar problems but how easy can one port hardware and algorithms from one area to another? How do you scale smart cities without reinventing the wheel each time?
- Who pays for the infrastructure? Sometimes one can get research grants or federal help to start new projects, but these projects need continual maintenance afterwards. Are researchers just in it to start a project, write a paper and get out? How do we keep the advantages going in the long run?
- How do you keep the public's trust that the information collected will help the city and not just keeping track of everyone a la Orwell's 1984?
- How do we make sure we tackle the problems of the general public and not just the researchers and those who help fund? A great quote: We need to make sure we are focused more on mass transit than on how to make parking the Tesla easier.
- If we use big data to predict crime and position police in response, could that cause discrimination and harassment?
- How do we keep our research relevant?
Rural areas got their due as well. Interesting presentations on how farmers can use sensors and machine learning to optimize crops, fertilizer and water to use just the right amount needed for each segment of the farm.
To paraphrase Tip O'Neill, all computing is local, but we face many challenges taking our broad tools of cloud, big data, machine learning, automation and internet of things and apply them in our own neighborhoods.