King’s College London, UK
Ubiquitous smart cities
Your smartphone recharges while you sleep, and tracks your nocturnal shifting and turning in order to let you know, in the morning, whether you’ve had a good night’s sleep or not. As you get up, you catch a glimpse of your glitzy new smart meter, which shows that your ceiling-mounted solar panels are currently feeding energy into the smart grid, lowering your own energy bills in the process. An update about your journey to work arrives on your phone’s touch screen while you have breakfast, enabling you to quickly plan a diversion to avoid a late-running train. To make it on time for an earlier train, you use Über’s taxi app, and a car arrives at your doorstep in four minutes flat. The taxi driver looks pointedly at the car parked in your driveway, but you don’t have time to explain that you’re renting your empty driveway out to a commuter through parkatmyplace.biz, and that therefore the car is not yours. You use a car-sharing club instead, and book the cars through your smartphone. On the drive to the station, you book a plumber to fix your shower through the handy.com application, and then send some work to a remote PA through ODesk.com – which means you are sharing the PA’s services with a number of other individuals and corporations. The PA works eight time zones away from where you live, which means that they work while you sleep, and you have a new batch of completed assignments in your shared Dropbox folder every morning. As you finally walk through the ticket barriers to the platform at the train station, the barrier mechanism records your entry and adds it to a data feed tracking millions of users’ journeys every day of the year. As a result, the train company is investing into the purchase of additional carriages to add capacity on its morning services. When you exit the station at your destination, a smart garbage can displays transport information and advertisements tailored to your contactless payment behavior, which the company operating the garbage cans knows about because it buys access to purchasing behavior data streams aggregated through shops that use contactless payment terminals. A day in the morning of a contemporary smart citizen?
Calls for building and establishing ‘smart cities’ are all the rage today, and not just in the city management and urban policy context. Scholars and urban theorists, technologists, and engineers are involved in a wide variety of contemporary debates on various aspects of what it means for the city to be ‘smart’: from debates over smart grids, ubiquitous digital networks, and the management of ‘Big Data’ – to research, development and discussion over mobility-focused applications, smart materials (such as smart glass), and the integration of the digital world with existing infrastructures. In short, the ‘smart’ concept has pervaded urban thinking, to the extent that scholars such as Sofia Shwayri, of Seoul National University, has termed the smart city the ‘ubiquitous city’ (Shwayri, 2013), because of the ‘invisible’ yet pervasive presence and delivery of public and private services through digital networks and infrastructures.
Smart approaches to city management have been described as holding promise, in the context of the digital economy, for enabling cities and urban systems (from transport networks, to air quality) to be monitored and managed in real time (Shapiro, 2006). Many national and city governments – from London and Dublin to Hong Kong and Shanghai – have started to invest in such systems, and there has been massive investment in new-build smart city projects, such as Cyberjaya, Malaysia (Brooker, 2012), and Songdo, Republic of Korea (Shwayri, 2013).
Take the UK policy context as an example: in 2013 the Department for Business, Innovation and Skills (BIS) identified smart cities and their associated technologies and applications as a major business opportunity for the country (2013). Significantly, BIS estimated that the global market for smart city technologies will exceed €400 billion by 2020. This figure is a recognition that smart urban technologies are not just reducible to digital networks or sensor systems, but have the potential to be both innovative and disruptive to existing infrastructures and systems of regulation and management: commercial products, such as the multiplying array of smartphone-based apps, point towards the kinds of flexibility that a ‘smarter’ infrastructure can offer. Some commentators have been quick to point out how smart systems and technologies can also be seen as having potential in terms of environmental monitoring, enabling more efficient use and management of resources, and integrating cleaner and greener technologies into the urban fabric.
Nonetheless, the smart city is an example of a further technologization of the city. Smart city ideals are based on the key role of digital networks, data, and technical experts in recasting the urban environment in the key of enhanced efficiency, information, and knowledge about how, why and when the city functions. In this light, there has been the emergence of a set of critiques focused on critically interrogating the smart city and its myriad iterations. This article is rooted in this critical literature, and acknowledges its importance: below is a summary of some of the main ways in which smart city ideals have been critiqued thus far. However, the article also takes an approach rooted in the recognition that technology is a social tool, and as such it can be used for positive outcomes in the contemporary city. The second part of the article therefore focuses on some of the ways in which smart city technologies and systems can be deployed as a way of enabling the emergence of more sustainable (in the broadest possible sense) urban environments.
The definitional critique: smart and empty?
A key set of smart city critiques has focused around its definitional boundaries: basically, what is it that comprises a ‘smart’ city (Hollands, 2008)? What is the difference between a smart city and a ‘digital city’? And what – if any – should be the performance targets, characteristics, and indicators through which the claims of smart cities can be assessed and evaluated? Definitional critiques are nothing new, of course, but they are crucial if the ‘smart’ concept is to be considered as anything more than a useful envelope, or container, of a range of shiny, new and highly marketable technologies which enable both technocrats and gadget-lovers to salivate over the latest release in hardware or software.
Above all, it seems crucial to ensure that discussions over ‘smart’ urbanism do not become rooted in a vague idea that ‘smart’ cities are by necessity positive developments in the urban realm. It is important for key concepts such as ‘smart’ not to be simply ‘empty’ signifiers (Davidson, 2010), and to question and debate what is ‘smart’ in a way which enables urban politics to thrive, and not to be removed from citizens and relegated to the realm of technocrats and large engineering corporations which have a stake in making sure the ‘smart’ city happens – but from a product placement point of view, which is not necessarily politically or socioeconomically progressive.
The governance critique
The tension between the distributed modes of self-organization enabled by digital networks and the more centralized control systems typically enacted in urban environments means that, from a city governance perspective, a key question remains as to the potential of, and barriers to, city governance through smart technologies and systems. Key to the integration of smart city technologies and systems within urban governance frameworks is the ability for smart systems to, firstly, sense, measure and transmit data in real time. As global engineering and design firm Arup stated in its 2011 evaluation of the smart city technology market, ‘if you can’t measure it, you can’t manage it’ (Arup, 2011: 4). Thus, indicator and sensor systems – from GPS units on municipal buses, to air pollution sensors, to individual citizens’ own smartphones and mobile devices – are crucial components of any smart system.
However, the data generated through smart systems means that a large volume of real-time data is received by municipal authorities. Thus, a key question for smart city governance is the effective integration of these large data streams into governance frameworks. While this has so far been achieved through recourse to features such as ‘urban control rooms’ (such as the smart control center recently opened in Glasgow, UK, and similar facilities in operation in cities such as Rio de Janeiro), recent attempts at data-governance integration have largely tended to be based on the notion of the city as a machine, governable at a distance from one location. This works well when the influx of data is directly relatable to a specific governance response – for example, when a traffic sensor is used to affect the timing of traffic lights. It is less useful when the complex interaction of various systems – say, between transport systems, emissions data, and economic performance – is concerned. In more complex scenarios involving multiple variables – for example, using smartphone data to analyze urban citizens’ health, or even using such aggregate analysis to feed back to individual citizens – then more top-down, smart city management approaches potentially work less well. Thus, there is a need – not just a technological need, but a political and governance need – to analyze current smart urban management practices and ideas, and to study how to integrate smart systems into a framework of urban governance understood not simply as urban management, but as a system of governmentality. The emergence of a ‘smartmentality’, based on the definition of the role of the ‘smart citizen (Vanolo, 2013), formed part of the discussion at the recent UGEC conference in Taipei, November 2014.
The technological fetishism critique
One of the key ways in which smart cities have been critiqued in recent years is as yet another example of high modernist planning, in other words focusing on technology as the solution to the city’s problems. As Batty, Milton and Reades (2013: 31) have argued, ‘Cities in fact are turning into computers with enormous and unprecedented effects on how we behave and function within them.’ Although this view can be seen as yet another evolution of the ‘city as a machine’ metaphor, it is nonetheless an increasingly prevalent and incredibly persistent image of the modern city. This can be seen, for example, in the extent to which smart cities are being conceptualized as machines that can be monitored in real time (Batty, 2015): smart city dashboards and control rooms are examples of this image of the city, which contributes to the notion that cities cannot just be monitored, but also controlled, at the point where various data feeds are interpreted and displayed. And yet, as Kitchin et al. (2015) have pointed out, notions of the smart city as a machine which can be controlled ‘at a distance’, through features such as smart control rooms, are potentially misguided due to: the narrow way(s) in which technology is conceptualized; data’s openness to manipulation by vested interests; and the lack of recognition of the fact that technologies, ways of doing, and urban metrologies are as much socially produced and constructed, as they are purveyors of data about ‘objective’ urban reality. Furthermore, it is crucial to recognize that the fetishization of the smart city also carries with it risks, including around the links between technology corporations and urban government and governance; information security and the threat of hacking; system failures and the implication of reduced urban resilience; and the question of the implications of smart systems and data networks for privacy and individual rights and freedoms in the context of increasingly complex and potentially intrusive urban surveillance systems (Kitchin, 2014a).
Smart cities and urban inequalities
Warning bells are also being sounded about the sorts of urban spaces and populations which smart city technologies and applications are likely to leave behind in their supposedly smooth, frictionless drive towards a shiny techno-future. It is widely recognized that many of the contemporary urban world’s so-called ‘problems’ and inequalities are deeply rooted and complex, and not easily resolvable through single policies or technologies. The question remains, then, as to whether smart cities will enable the bridging of existing inequalities, or simply deepen them. In so doing, do they risk pushing the ‘have not’s’ of today’s urban world deeper into the non-digital darkness? Klauser et al. (2014), for example, have recently called for a need to investigate the ways in which the smart city will potentially feature changed power relations, including a deepening of socio-economic inequalities, especially along trans-generational lines. This is an important question, especially in light of continuing concerns over the widening ‘digital divide’ between the Global North and the Global South, and between wealthy streets and neighborhoods and their not-so-wealthy neighbors. Finally, a question remains to be asked as to whether technology and ‘smart’ systems can really deliver game-changing innovations, or simply incremental improvements in existing, relatively privileged urban contexts. To put it simply, when a significant part of the world’s urban population lacks access to basic sanitation and clean water, what kind of improvement top urban life is a cheaper and more available taxi delivered through your smartphone?
Data, urban health, sustainable transport, and sustainable cities
One of the key benefits of smart city systems is the fact that data streams can be harnessed and analysed. The resulting analysis can then be used to change or influence policies and initiatives aimed at specific groups of citizens – or even the individual urbanite. While the ownership of data generated through smart devices, such as tablets and mobile phones, is an open issue – and a key one in terms of its monetization by corporations, its security and ethical use – there is also clear potential for real-time and long-term monitoring of specific types of data. For example, integrating individual devices with transport journey planning and ticketing has the potential to make journeys far greener and more efficient – but only if sufficient, parallel investment is made into fast, reliable and comfortable public transport and associated infrastructures (Hall, 2010). As someone who has traveled extensively on trains both in the UK and Germany, I can attest to the fact that some countries are leagues ahead of their peers in this regard. A ‘smart’ journey, as presaged by Hall (2010), might include the capacity to ‘program’ a journey using a smartphone, which is then updated in real time as the journey progresses, and which also enables payments and tickets to be collected and used via sensor systems, without the need for physical ticket barriers, lines at ticket machines, paper tickets, or the use of less efficient transport options. Crucially, the utilization of smart technologies for urban transport planning could also enable more journeys to be made on foot – for example, between subway stations, when the speed of the subway is more than offset by the time taken to get to a subway platform, wait for the next train, and then exit the destination station.
With regards to urban health, smart city systems and data streams enable a similar range of potential benefits and improvements to urban life. For example, data sourced from large datasets of urban behavior patterns could assist health officials and policymakers in enabling services and policies that target specific forms of behavior in the population. Smart city applications could also prompt specific behaviors, from promoting walking, to promoting an individual’s next health check-up, to issuing warnings and prompts over the intake of specific ingredients and nutrients. At an individual level, smart applications enable the real-time monitoring of individuals’ health, as well as enabling the tracking of a user’s health over a longer period of time. This information could be very usefully integrated into national health system reporting, and could be used by general practitioners to inform their practice and more usefully target their treatments and recommendations.
Finally, smart city indicator systems focused on issues such as urban emissions could be useful not only in tracking an individual city’s performance, but in potentially enabling the comparison of environmental data across urban areas within and across jurisdictions. This could be used as a tool in the environmental management of both the city and the economy, although it also opens up difficult questions around how environmental performance data is used to inform and shape policy and economic behavior. Any question over environmental behavior and performance is, however, by necessity a political question, and should be treated as such, and not simply as a technical concern devoid of any political or social content.
Smart cities and the asset-sharing economy
One of the key sustainability concerns in any urban agglomeration is the issue of waste, broadly defined. This includes waste streams, from municipal to commercial waste, to the associated infrastructural concerns of whether to use landfill, incineration, recycling, or whether to export the materials that the city produces as part of its metabolic functioning. However, waste can also be understood in terms of the inefficiencies of the ways in which resources are left unused in the city. This stretches from automobiles left parked on the street for days at a time, to unused driveways and garage spaces, to facilities (such as municipal and private car parks) that are overused at certain times, and idle at others. Smart technologies, with their focus on efficiency and on matching demand with supply in real time, are a source not only of potential disruptive innovations, but of ways in which the city can self-organize more efficiently for the benefit of its citizens.
One of the ways in which the smart city is providing solutions to questions of waste and efficiency is through the so-called ‘asset-sharing economy’. The concept encapsulates the idea of an economy in which less is potentially owned, but in which more is shared, and which therefore promotes a higher usage rate for those assets that are shared. This is the case with applications such as parkatmyplace.com, which lets individuals monetize their empty parking spaces and driveways. The same could be said about car-sharing clubs, which enable members to use a car for a set time. Users are then charged for the cost of the car’s use (usually a combination of mileage, running and insurance costs, rolled into one price).
The example of car-sharing has a direct, knock-on effect on urban sustainability: many car-sharing clubs focus on making available low-emission vehicles, and membership of a car-sharing club potentially means that those who would otherwise only have needed a car for short urban journeys no longer need to own an automobile.
These types of asset-sharing applications are also examples of bottom-up economic and cultural changes in the ways in which products and services are consumed. They are, by and large, not top-down initiatives led by ‘smart governance’ systems – although local city governments may choose to back or support certain systems. Thus, the asset-sharing economy sidesteps the critique that smart cities are simply sinister attempts to micro-manage the city and its residents – although questions about the role of corporate actors in this new economy still remain.
Bridging the ‘divide’ between informatics, engineering and social science
As Greenfield and Shepard (2007) have noted, current debates over the increasing imbrication of digital networks in the city opens up opportunities for involving architects, planners and, I would add, a much wider range of ‘social’ science practitioners and scholars in debates about the shape and trajectory of the smart city. Thus, while a key role for social science is a continued focus on critiquing smart city ideals, and while social scientists do and should continue to critically scrutinize plans for shiny new ‘smart’ projects, there is also a more progressive role open for social scientists, planners and architects. This role is rooted in critique, but not limited by, or to it. Rather, it encourages a recognition that with the rise of smart cities there is also the chance of a simultaneous engagement with the processes of debate, contestation and discussion that critical social scientists and urban theorists argue is the quintessential characteristic of democratic urban politics (Evans-Cowley, 2010). The result, of ‘learning and critically reflect[ing] by doing’ (Kitchin, 2014b: 5), is a step forwards from learning and simply critiquing. As Rydin (2007) argues, while the sort of ‘control at a distance’ enabled by smart indicator systems can be critically questioned, nonetheless it is important to pay attention to the actual engagement, in specific cases, of policy and government actors with new technologies, and to avoid leaping to negative conclusions from the imbrication of new technologies with the realm of urban politics.
Header Image: Kuala Lumpur, Malaysia. Credit: joyfull/Shutterstock.com