In late November, the crowdsourced smartphone app Waze released a stunning visualization that showed the traffic flowing through New York City on a recent September day. Resembling blood flow though a body, cars move through the arteries and veins of city streets and highways, slowed by both collisions and general congestion. Waze collects data via smartphone owners that allow their location (and speed and direction) to be captured and aggregated, providing real-time information on traffic in a city. When using Waze, drivers can be alerted to new incidents like accidents and police on the road, and the app can even suggest new routes for a faster ride.
Crowdsourcing apps like Waze, ridesharing apps like Ridejoy, and home control apps like Nest may also be a boon to some of the smart city initiatives being developed and planned worldwide. Numerous cities in the world are adapting IT for their infrastructure and streamlining operations for their departments. Navigant Research’s report Navigant Research Leaderboard Report: Smart City Suppliers identifies the promising companies that have demonstrated advanced approaches and penetration in this sector. Most smart city initiatives begin with public transportation and traffic monitoring, as they are critical services for citizens, and promote commerce as well.
Short on Cash
There’s a basic challenge for cities that want to pursue programs like these, though: limited municipal funding. In the first world, or in a few examples in the developing world, cities have signed multimillion-dollar contracts, paying large IT and equipment companies for equipment and consulting services for smart city initiatives. These large price tags limit the adoption of (large) smart city programs in the developing world and in smaller cities and towns. Crowdsource apps could provide a solution.
If the data from crowdsourced apps like Waze could be shared with municipal agencies, data limitations would virtually disappear. Instead of paying millions for a full service solution, a city could hire a cadre of data analysts to examine the trends in traffic, identify collision hot spots, and use the aggregated data for long-term traffic planning, supplanting expensive traffic studies. One example of an interesting use of this kind of data is New York University’s (NYU’s) visualization of taxi rides in New York City.
Using data from the Taxi and Limousine Commission, NYU researchers created a rich queryable database where taxi demand is revealed visually, and the impact of major disruptive events like Hurricanes Sandy and Irene on taxi rides can be understood (namely, that few taxis ventured into the power-less regions of lower Manhattan). MIT has, in turn, developed an interactive website using the taxi data to demonstrate the value of ridesharing. The academic insight has yet to be used for city policy, but as the analysis improves, such applications will surely follow.
Certainly, there are obstacles with this approach. The first is privacy. Aggregated urban mobility data can be anonymized. Yet, the idea of governments gaining access to individual citizens’ whereabouts, regardless of the source of the data, may make a fair number of people uncomfortable. Open questions prevail: Could mobility data be used for forensic purposes? Since Waze is owned by Google, what other information could be associated and shared? These questions and many others will have to be addressed through real deployment. As has been seen through companies like Uber, which is now causing taxi medallion prices to fall, disruptive technologies can shake up the status quo. City governments have not traditionally been the locus of innovation, but the smartphone in your pocket may change that in the near future.
Tags: Clean Transportation, Information Technology, Mobile & Wireless, Smart Buildings Program, Smart Cities
| No Comments »