Here’s the scenario: Your city determines to improve or change some aspect of one of its neighborhoods and after months of outreach, planning, and building, Street X has, say, wider sidewalks, speed bumps and some benches and trees. The budget’s been used up, the community is generally pleased with the improvements, and the planning department re-assigns the project team to new tasks. If the project’s goals were to improve walkability and calm traffic, it might be difficult to tell how much of an impact was actually made without an in-depth assessment phase. But even if the goals of the project have clearly been realized to everyone’s satisfaction, there’s still value in taking a closer look – maybe if you studied 20 similar projects you’d learn that one of these improvements actually contributes most to the positive outcome, or that two of these improvements work better in concert than they do individually, or that there’s a set of pre-existing conditions that need to be present for a site to see benefits from one intervention or another.
The difficulty that planning agencies run into is that a thorough investigation using traditional research methods requires boots on the ground counting pedestrians, taking notes on clipboards, etc. This demands staff that aren’t always available, and the results might be skewed by any number of chance factors in play during the observation periods – If the weather is unusually nice, or if the use profile is very different on weekends than on weekdays (when most of the observations are made), or if the World Cup is on TV and everyone’s inside glued to their couch, then the hours of observations can still really only paint a partial picture of the new space’s performance. To fill in all the gaps and complete the picture would require staffing the site 24/7 so that observations can be made continuously.
Outside of the City Planning sector, the need for more efficient monitoring and data-collection has led to a greater dependence on sensor technologies. Smart meters that communicate directly with energy providers are supplanting human meter readers; the Golden Gate Bridge no longer staffs its tollbooths now that everyone has a FasTrak device. These and other more-efficient systems streamline what used to be resource- and time-intensive processes, and can also establish a constant stream of data for those organizations to learn from and respond to. In the context of planning or evaluating a public-domain project, I don’t think that sensors could ever fully replace the role of an experienced researcher who can notice subtle behaviors and reactions to the city-scape, but what sensors are really good at, and what they could help with are all of the necessarily time-consuming and repetitive (but in the end very valuable!) tasks like counting and taking measurements. Your one researcher standing on a corner can log this type of data for a few hours at that location and maybe come back and do the same thing a few more times over the following weeks. A sensor can monitor the same factors continuously over months, freeing up the staffed researcher to move through the space, ask questions, take notes, photo-document their time on-site, etc. That’s what humans are really good at, so using people and technology together seems like a perfect match for the evaluation process of public projects. The test is whether a sensor (or sensors) can accurately capture the key performance data points that tell the story of how a space is being used when a researcher isn’t present.
To explore that question and get involved with a very neat local project, MKThink partnered with the Exploratorium and the SF Planning Department on the former’s first ‘Living Innovation Zone’ (LIZ) at Yerba Buena Lane. If you’ve walked down Market Street lately you’ve probably seen it – it’s a circle of benches backed with slatted windbreaks, and there are interactive exhibits to try out as you sit and eat/talk/relax. People speed-walking down the sidewalk can weave through or around it, but the idea is to slow them down or tempt them to pause and “spend time observing their urban environment —and each other— more closely.” (https://www.indiegogo.com/projects/exploratorium-living-innovation-zone)
MKThink’s role in the partnership was to monitor the installation and consider ways to share that information back to pedestrians as an exhibit in a future LIZ. We conducted some of that old-fashioned in-person observation, but we were most interested in testing out a network of sensors that counts up how many wi-fi devices (as a proxy for foot traffic) pass through the study area and measures how long they tend to stay in the space.
This was conceived as a test of the technology, and there were some challenges with getting access to power and network (but thanks to nearby building owners we were eventually able to!), so we didn’t establish a baseline of data from before the LIZ was constructed. This limited our findings somewhat, but our monitoring system was in-place for 4 months and we have readings that describe the fluctuations in foot traffic and length of stay – our performance criteria – over that entire time. We can tell that the LIZ experienced its heaviest use on Monday, November 18th, and that visitors on Sundays stay significantly longer in the adjacent plaza than those on Saturdays, and a dozen other anomalies and patterns that lend context to the observations we were making throughout the study. The challenge at this point is that even with our mountain of data, it’s difficult to tell which among all of the factors that make up a complex system like Market Street contribute to the spikes and trends in our data. To understand what happens in and around the LIZ on that level we’d need to take into account a whole range of other factors that influence public space, and probably rely more heavily on human-led research than sensors.
So what is a focused application for sensors in city planning and urban design today? Fitting them into a routine evaluation process for public projects is one possibility. The Exploratorium’s idea to make data visible and interactive to get people engaging with their surroundings is a completely different angle. A counterpoint? The city of Chicago has a new program they call the Array of Things, which just started collecting a whole bunch of city data, and at the moment is simply storing it all for ongoing study. (http://www.chicagomag.com/city-life/June-2014/What-Chicagos-Array-of-Things-Will-Actually-Do/)