Measuring Public Space Engagement

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Photo of AGILE Parklet on 5th Avenue , Nashville, TN in front of Frothy Monkey Restaurant Coffeehouse during Park(ing) Day 2015

The AGILE Parklet joined the diverse array of parklets on Park(ing) Day 2015 as they popped up in parking spaces all across the country. While it was set up in the heart of Downtown Nashville adjacent to a local restaurant and coffeehouse, sensors embedded in the parklet’s chairs successfully gathered over six hours of data about the parklet’s use. This automated data collection effort was a continuation of the experimentation The AGILE Landscape Project has been conducting since publishing The Future of Public Space Analytics earlier this year. The post made the case why automated data collection through embedded sensors could provide unique and valuable insight into the use of public space. The AGILE Parklet has been deployed during events and self initiated pop-ups to demonstrate the real world application and potential of this approach. This initial proof-of-concept has focused on collecting information about the number of people sitting in the parklet, the utilization of its capacity, and the length of stay of individual visitors.  These metrics and the ability to efficiently capture them over extended periods of time have shown great promise for developing public space analytics that enable designers and managers to make more informed decisions rather than anecdotal observations and/or assumptions. What follows is an examination of the data collected during Park(ing) Day and and exploration of its application.

Why focus on the seating? Seating is a key component of successful public spaces and the act of sitting represents a relevant and measurable means of quantifying users engagement with a space. In addition, this action can be accurately, and anonymously captured to create long-term longitudinal datasets. By capturing the total number of people sitting in chairs and how long they stay, one can quickly surmise a level of engagement, the capacity of the seating utilized, and turnover of users within the space. This information offers meaningful metrics that provide new insights into the dynamics of a space’s use. A device embedded in each of the AGILE Parklet’s chairs enables them to easily capture this data and transmit it wirelessly to an on-line database for analysis. The captured data is simultaneously plotted in real-time on a companion website.

The current analysis of the collected data and the development of tools to facilitate the application of it has centered around the following three metrics; Total Visits, Utilized Capacity, and Median Length of Stay.

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Documenting Use of Public Space in Real-time

Video Clip from MIT’s Sense and The City Project (2012)  Source: MIT Senseable City Lab

Capturing the movement, location, and activities of pedestrians can be helpful when assessing the effectiveness of public space and facilitate the management of it. William Whyte’s Street Life Project, one of the most influential public life studies, is a great example of the insight that can be achieved when this type of data is gathered and analyzed. It also illustrates the tedious and time consuming nature of the work. This laborious effort is the main reason most design professionals and managers of public spaces rarely have the luxury of conducting comprehensive post occupancy surveys of their work and/or spaces they manage. Too often our understanding of these places is comprised of ad hoc observations and long-term trial and error. As result, existing and future spaces needlessly can suffer from uninformed design decisions.

Pedestrian data is the foundation of public life studies. Various technologies are making is easier to capture this type of data and in many cases in real-time. These include digital video, wireless networks, mobile phone networks, and  infrared cameras. When considering these technologies pedestrian privacy is important. Like in previous public life studies, all data gathered should be anonymized in order to maintain an individual’s privacy. This can be done while maintaining the usefulness of the data captured.

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