It’s safe to say that the term “Smart City” has surpassed its status as a buzzword. Talk of these projects is just about as ubiquitous as the infographics and pictograms that illustrate our conceptions of these intelligent places. However, I’m bothered by the fact that we still have more drawings than examples of successfully implemented projects that empower smart citizens. Perhaps to start, we could begin building Smart City Dashboards to at least connect citizens with the data being collected?
To move beyond the hype, we can start by asking ourselves a few questions:
- What steps can we take to move beyond graphic renderings of the Smart City and all of the associated talk?
- What goals are we trying to achieve by measuring all kinds of data?
- What data will be most useful to citizens?
In addressing these questions first, we will begin to be able to respond to the question, “How can we best harness sensor data and other byproducts of the Smart City?” a key challenge confronting many Smart City projects.
Making Invisible Data Streams Human Friendly
The City Dashboard concept is quite simple. Michael Batty at the University College of London noted that it is meant to display real-time data in a highly accessible manner. He says that they should also have the potential to be customized according to user preferences.
There are even a few examples of early dashboards we can look at for further inspiration:
- London City Dashboard (along with a host of dashboards for other UK cities)
- Madrid Smart CEI Moncloa (by Universidad Politecnicia de Madrid)
- City Dashboard Amsterdam (new version still under construction)
Let’s take a closer look at the London City Dashboard. This resource was built in 2012 by a team from the CASA Research Lab at University College London. Immediately, it makes information available on subjects such as:
- The state of the Underground;
- Current traffic conditions, displaying two live videos at a time from various locations in the city;
- Air pollution data from meters across the city;
- Much more, even including a mood indicator.
This project is quite interesting! It displays information with some degree of organization, and most importantly has real-time streams. This is key, because much of the data being collected is event-related, for example the departure of a subway train, which is relevant in general for a moment. Information like this must be displayed in real-time.
Limitations of Smart City Dashboards
However, there are notable shortcomings. The project directly states that feeds are “expected to break regularly.” Further, there is essentially no context provided with any of the information. Regarding transportation data, for example, there is no information displayed relating to a given stop or geographical point.
- We can see the number of bikes in the city’s bike share available over a 24-hour period; however, we don’t know where these bikes are, nor if a nearby station has available bikes.
- A user can see the number of buses currently in service, thanks to Transport for London’s API, but there is no real-time data on when a bus will arrive at a nearby stop.
- We can see the state of the underground, however we don’t know when trains will arrive at and depart from specific locations relevant to us.
These limitations are common challenges associated with developing Smart City dashboards: making data relevant to the geographic location of a user, the availability of reliable feeds, API documentation, etc.
Transport for London has made it possible to localize their information via the Tfl Unified API, and countless applications have taken advantage of this access. Regardless, the fact remains that the ability to process and reuse an API requires technical expertise and infrastructure that the average person would not have. I personally have no idea how to use an API to find a Tube station on a map, if not using an application. An API on its own is useless to me.
This begs several questions around access to information: as machines produce more data, how do we ensure that it can be readily understood and reused by all audiences, not just those with certain skills? Accessible Open Data can be the answer to that!
Let’s Go Ahead and Build A Better Dashboard
To illustrate what we envision a Smart City dashboard to look like, we went ahead and built one, displaying Transportation information in the Greater Boston area. We wanted to focus on one subject in our example, to keep the dashboard clear and succinct. After all, I do agree with the idea that a city is a complex and dynamic ecosystem whose entirety cannot be represented on a screen. Certain individual topics, however, can be more easily.
The Massachusetts Department of Transportation and the MBTA (the public operator of most subway and commuter routes in Massachusetts) publish information in the form of GTFS data feeds and real-time CSV files. There were not any open datasets to provide a clear view of the information while still in its raw form.
In about an hour, the OpenDataSoft team was able to process these feeds, publish the information as Open Data, and even begin building an Open Data portal with these and other datasets. We then went ahead and built a dashboard containing the following information:
- Next passages of the Red, Orange and Blue lines of the T, the subway system in the Boston Metro Area (there are no real-time data streams for the last line, the Green line);
- The availability of bikes in the city’s bike share program, in real-time;
- The location of Commuter Rail trains and their expected arrival tie at the next station.
We also added a view of the air quality in Boston, using information from Plume Labs, to provide more context. This may even help viewers draw potential correlations between pollution and commuter choices.
Cool Dashboard! . . . But Why Does it Matter?
Displaying such information together in one place is, in particular, relevant to a commuter. This may be a way to use Smart City data to empower people to make more informed and lower-impact decisions. We can imagine these kinds of dashboards being displayed in public spaces: stores, apartment buildings, parks, bus, train, and metro stations. We could even imagine such dashboards being shared and used on popular blogs to communicate the information to people. The same APIs coming from the Open Data could also be plugged into vertical applications for better, lower-impact route planning.
Using data and demonstrating collective impact in a clear and interactive way is one method to harness the power and promises of the Smart City. The Smart City is expected to bring all kinds of productivity boosts and help improve the environment. But it is also up to individual citizen actors to use Smart City information to change their behaviors in order to truly make these changes and impacts occur.
One of the improvements could be in urban air quality. Poor air quality’s impacts on overall public health are quite well-documented. The World Health Organization estimates that in the EU, the cost associated with premature deaths and diseases resulting from poor air quality added up to $1.6 trillion as of 2010.
Automobile use is a large factor in a metropolitan region’s air quality. In showing someone when the next train will arrive and how they can use it to get out of traffic, public transportation suddenly becomes much more appealing. Even better, by showing people in Boston where a bike is and if it’s available, they may be more likely to use this option for shorter distances.
Getting more people out of their cars and taxis and onto bikes, buses, and trains can have wider positive impacts on the larger scale. Better air quality menas more savings in health spending thanks to an overall healthier population. Less cars on the road means less congestion. In the UK, France, Germany and the United States combined, costs associated with traffic measured $200 billion in 2013. There are huge savings potentials and productivity boosts associated with wider use of public transportation.
Empower All The Humans
It has probably been said countless times: people are a city’s smartest asset, no matter how intelligent and connected a place may be. The Smart City has at its disposal the information needed to empower better-informed decisions, but more reliable and people-friendly data hubs are needed to process, visualize, and share the data to ensure that insights can be drawn from these data and acted upon.
This is but one example of a dashboard. Transportation is only one potential piece of a Smart City dashboard. They could be taken even further with pages about energy consumption and water use and quality. If there is a sensor to measure something, there should be data made available.
Dashboards are but one method of putting important information scattered across Open Data portals and feeds around the web into a cohesive and understandable location. They allow the Smart City to become a more tangible concept in a person’s day-to-day life, and can inspire the opening of even more data. Give us all Smart City dashboards!