6. Conclusion
The smart city needs to be understood in differentiated ways, and based on more than ICTs alone. Goodspeed (2015) argues for an understanding of the smart city as a “sociotechnical theory of action” (p.3). Elsewhere, scholars have argued a city's ‘smartness’ should be determined by the degree to which it fosters the capacities for learning and innovation. Finally, Hollands (2008) argues that if cities and local governments really want to be considered ‘smart’ that conventional structures of power and decision-making about the built environment needs to be disrupted, and moreover, that they need to take risks, and invest in, emerging technologies. These views implore us to understand city's relationship with ICTs more in relation to interaction, engagement, and practices, and that databases, sensors, and networks become embedded within broader organisational and social contexts in ways that can affect significant change. Yet, design ideas about how to enable and implement this shift in smart thinking and strategisation have, to date, received far less attention.
The Ubiquitous Cities design studio, that is contextualized here in relation to a proxemics-based model for the user-centered design of smart city initiatives, is argued to contribute an alternate approach to smart city thinking by addressing—through design practice—the key question of what kinds of urban experiences smart initiatives can offer? This has involved an approach to designing with, as well as through data, at various scales of design thinking, and in ways that always centralise people and their experience of place. More specifically, this relates to complementing the analysis of material-physical data (measurable or quantifiable features of place and people) with qualitative data from social media sentiment analysis. Equally, this concerns various types of real-time data that can be captured by urban interaction design projects that integrate responsive sensing and actuating technologies in ways that reveal and draw focus to the inherently dynamic nature of the built environment. And by extension, and given their sensor-driven nature, this relates to the capacity for these projects to—in the longer term—aggregate site-specific, yet a-personal data, to feed back into both large-scale smart thinking and smaller-scale examinations of the on-going use and experience of specific places.