CORPORATE CITY Commercial Urbanism Urban Perspectives Lifestyle in Urban Space Washing Away Our Responsibilities
PROGRESS OR FASHION?
DIGITAL CITY
SmartScapes Big Data and Urban Informaticsfor Performative Cities Achilleas Psyllidis
The distribution of sensor networks throughout the contemporary urban environment together with advances in mobile and web-related technologies, create new opportunities for practice and research in Urbanism. Digitally-driven systems and devices provide immense amounts of real-time data streams, which reflect city dynamics. In turn, this increasing availability of real-time information is capable of providing the urban designers/ planners with a highly detailed and dynamic picture of the urban fabric. Part and parcel to this new dimension of reality, the discourse surrounding Smart Cities is gaining in popularity recently. Yet, digital ubiquity - as a 'by-product' of the post-industrial age - is not the sole motivating factor. There are also global phenomena, fueled by the increasing urban populations, along with the socio-economical and environmental repercussions they bring about, that instigate it. 21
I DIGITAL CITY | article
Background
To better understand the contenaporary global urban context, we first need to contextualize it within the forces that are currently driving a paradigm shift in the domain of urbanism. Specifically, the world has experienced radical changes over the past five years in both technology and physical space. The changes that mark this transition are summarized in three major milestones. Firstly, at a spatial level, the acceleration of urbanization processes worldwide has led to a tip in the ratio of urban-to-rural global population. I n 2009, for the first time in human history, the total amount of people living in cities exceeded that of people living in the countryside. Assuming that the urban agglomerations will continue to increase their numbers at the current rate, the U N predicts that by 2050 more than 70% of the world's population will be clustered in cities (UNFPA, 2007). As a result, humans are already - and progressively evolving into an "urban species" (Moere & H i l l , 2012). Secondly, contemporary societies in both developed and developing countries have shifted from an economy based on industry, to one that is driven by (digital) information and service provision e. Foth, 2009; A . Townsend, 2009). This transition has set the stage for the two remaining milestones both of which relate to technological advancements. The first refers to the prevalence of wireless connections over cable-dependent technologies, meaning that people tend to communicate and connect to the Internet via mobile devices (smartphones) to a greater extent than wired connections. Such an increasing detachment from cables fuels the rapid growth and subsequent pervasiveness of wireless technologies. The other, constituting the third major milestone, comes as a direct repercussion
of the aforementioned devices and their subsequent global distribution in associative networks. I t can be detected in what has been coined "the Internet of Things" (loT); a merger between people and technologicallyaugmented systems. The turning point in this case is that the l o T has become so pervasive so as to almost reach ubiquity (A. M . Townsend, 2013). To put it in simple terms, as this article is being written, more devices/objects are connected to the Internet than there are people who currently exist on this planet. And in the coming years these systems are expected to double. Such an excessive fusion of computational devices in the natural environments, gradually leads towards the implementation of Mark Weiser's concept of ubiquitous computing, which he perceived of as "the availability of computers throughout the physical environment, virtually, i f not effectively, invisible to the user" (Weiser, 1991). Taken together, these three milestones act to establish the present-day context and not a futuristic scenario or vision. They incite profound changes to various behavioural and operational aspects implicated in our surrounding urban environments, which, in turn, form complex configurations of both physical and digital networks. Embedded in this framework, the urban designer/planner is faced with a paradigm shift in the profession. I n particular, (s)he has to actively tackle issues relating to this emergent hybridity by taking into account and balancing both the physical and digital aspects of the city throughout the design process. This entails a new approach to design that requires an augmented set of tools and methods in comparison to the ones currently in use. Undoubtedly, the complexity of the profession will graduate to a new level, requiring a broad new spectrum of practical and research perspectives. O f
particular interest is potential poised in the collection of multiple real-time data streams of varying types that, could address strategic sectors of the city. Among other things, these relate to mobility, environmental conditions, and communal issues, as well as waste and water management. Big Data and Urban Sensing All the aforementioned streams of information constitute part of what has come to be called Big Data. Every short message service (SiVIS) sent via our mobile phones, every email, and each seemingly insignificant daily transaction we make, collectively contribute single pieces of information to an immense global data cloud. I n an attempt to aptly describe this wealth of data, Richard S. Wurman uses the example of the New York Times newspaper in which it appears that an average weekday edition contains more information than a 17th century person was hkely to come across in an entire lifetime (Wurman, 1989). Yet, the problem of too much data but insufficient co-evolving knowledge remains present, i f not intensified. For data to become more meaningful - and specifically in the domain of urbanism, to constitute integral elements of the design process - we have to extract the patterns from them to gradually deploy a story about particular issues. And in order to do so, especially as designers, we not only need to devise meticulous methods to mine the information streams serving our specific research and design questions. We also have to aptly parse, analyze, interpret and - most importandy - feed these refined data sets back to the environment and correlate them in a meaningful way, for people to become more aware and actively engaged in the process (Psyllidis & Biloria, 2013b).
With regard to the information deluge and potential ways to harness it, specifically within an urban context, three essential urban sensing methodologies can be utilized: ambient sensing, distributed sensor networks (DSN), and crowd sourcing (or participatory sensing). The first approach refers to the analysis of ongoing data streams f r o m cellphone and other pre-existing networks, primarily used for different purposes, yet valuable as information sources on how our cities operate. The second method pertains to the deployment of new sensor networks, comprising distributed sensing agents embedded in the urban fabric, to address specific issues. Finally, the third approach relies on citizen participation in providing data feedback, facilitated by the growing availability of smart mobile devices and the advent of social media. Citizens, in this way, not only act as consumers but also as producers of information. In other words, they collectively establish a sort of human sensor network (Boulos et al., 2011). Consequently, urbanists have at their disposal a wide variety of data mining techniques that incorporate both human and non-human sensing methods to use either partiy or collectively, depending on their specific needs.
(e.g. environmental monitoring, weather forecasting, transport controlling etc.) are domain-specific, subsequently providing segregated data sets. Thus, besides parsing, the correlation between heterogeneous sensor networks appears to be crucial, especially for the assessment of complex systems, such as cities. This can possibly be achieved through the standardization of sensor descriptions and models by utilizing Semantic Sensor Network (SSN) technologies. These particular standards are capable of facilitating data interoperability amongst heterogeneous sensor networks by correlating the physical sensor(s), the measured parameters, and the functional, as
and digital layers of people's networks and urban infrastructures" (M. Foth, Choi, & Satchell, 2011). To put it simply, the statement implies an intersection between human activity, urban contexts, and design media technologies. The field embraces all the aforementioned methodologies to efficiently collect and process multiple data sets of various types stemming from sensor networks, mobile devices, and social media in order to raise awareness for crucial aspects of the city and facilitate the decision-making process. Its rationale deviates from the conventional approaches of urban analysis and morphology, which are largely based on descriptive data of intrinsic city features.
"the problem of too much data but insufficient co-evolving knowledge remains present, if not intensified'' well as processing features. Yet, it is not the intention of this article to go deep into the details of the characteristics and potential offered by these technologies. Urban Informatics
However, as already stated, these elaborate methodologies for collecting real-time information about the city do not surmount the issue of extensive - mono-disciplinary — data sets that could prove meaningless. To overcome the information overload, we need to employ procedures to better refine — or parse, as it is commonly referred to, in data management terminology - available data sets. Further, another essential issue to be tackled pertains to the interoperability of the acquired information. A t present, most of the existing sensor networks
What is most important for us to consider is the emerging research and practice field that specifically engages with the opportunities created by the advent of ubiquitous computing in the urbanism domain. This particular field is called Urban Informatics. According to its very definition, Urban Informatics refers to "the study, design and practice of urban experiences across different urban contexts that are created by new opportunities of real-time, ubiquitous technology and the augmentation that mediates the physical
Instead, it aims for a more dynamic representation, simulation and, eventually, data-driven augmentation of the city through the development of cybernetic mechanisms and actuation systems embedded in the urban fabric.
ARUP, recognizing the significance of this research and practice area to the city, has established a homonymous dedicated department in Australasia. Closer to home, a joint alliance between T U Delft, iVIIT, and Wageningen University has resulted in the creation of the Institute for Advanced Metropolitan Solutions (AMS) in Amsterdam that will focus on technology-driven solutions for the urban environment.
The S m a r t S c a p e s Master C l a s s (Urbanism W e e k 2013)
Embedded in this context, the SmartScapes Master Class - as part of the Urbanism Week 2013 event - focused on the emergent skills that contemporary and future urbanists require in order to tackle actual and projected urgencies of the city (Figure 1). It introduced Urban Informatics 23
I DIGITAL GITY | article
and data-driven design methodologies that addressed strategic urban sectors, such as energy, environment, and mobility. The goal was to develop conceptual prototypes for participatory and replicable frameworks that allow citizens and urban decision-makers to assess key performance indicators (KPIs), in a holistic manner, instantaneously and intuitively.
Ufban Fanning
u n . loca Don padaging
Famvng
/
•=>
LaMDlng
^ LaMHng
TnniponUon
•=>
During the Master Class participants had the opportunity to engage with the notion of the Smart City. They critically analyzed what constitutes a city smart and how this, subsequenriy, implies a change in the urban design/planning profession. A t present, most of the discourse surrounding Smart Cities is centered on infrastructural aspects, proposing policy frameworks that either marginalize the importance of people or perceive them as endusers in a commercial manner. The challenge for the future urbanist is, thus, to establish democratic participatory platforms for collective decision-making via relational ecologies of data sets. For then a city will become "smart", by virtue of the collaborative activity of its citizens and different stakeholders. Altogether, they operate as actors, rather than passive consumers of policy frameworks.
MaiMt
Furthermore, the urban designer/planner is also an information designer, meaning that (s)he needs to be able to deal with extensive amounts of real-time data streams, correlate them, and, subsequently, derive meaningful feedback patterns for the citizens. Thus, the major design focus is not on the end product, but rather on the process of data sets along with the notion of performance. A multi-disciplinary approach is highly encouraged and decision-making processes depart from the conventional topdown model. Instead, urbanism professionals, in close collaboration with stakeholders and citizens, will merge top-down control with bottom-up behavioral aspects, through datadriven procedures (Psyllidis & Biloria, 2013a). /
monitoring/
/ f o o d quality/
FOOD
sensor an ached
distribmion^s^
• food distnbution point
^ '
1 consumer's food| storage
O
/ monitoring / f o o d quality
throw away food
/ /
Besides theoretical frameworks and related examples, participants delivered hands-on exercises based on the given theory. As previously mentioned, the scope of the exercise was to propose conceptual prototypes for embedded interactive systems in the urban fabric. These systems had to comprise a merger of three essential components: distributed network of sensing devices; natural user interfaces (NUIs) embedded in open public spaces and buildings (e.g. media facades, interactive displays etc.); and integrated physical actuation systems within strategic urban locations for real-time augmentation. The NUIs, in particular, aimed at fostering active human engagement that
"As sensor networks seamlessly integrate into the contemporary urban agglomerations, cities are enabled to interact and communicate among themselves by exchanging various data and information in a dynamic global network that merges physical and digital attributes together. "
would allow people to report information back to the system in a continuous cycle. In this way, they would not solely react upon mapped data analysis visualizations, as is the prevailing trend in various relevant contemporary applications. Given the limited amount of time available to us, the chosen methodology for developing the proposals was that of Roleplay Simulation. After dividing into groups, each member was assigned a specific role, either referring to an expert or a stakeholder in the design process (information/data expert, strategist, design manager, municipal decision-maker, citizen) with corresponding responsibilities. Unified Modeling Language (UML) Activity Diagrams and Pseudocodes were utilized as the main tools for the conceptual prototypes to model both computational and organizational processes. With these alternative forms of data flowcharts, participants modeled the information- and workflows in the proposed systems (Figure 2). Interestingly, all groups devised systemic proposals, tackling major issues of contemporary cities while simultaneously linking together parameters of different nature. I n particular, the final interrelated sectors proposed by the three teams were: food supply chain in supermarkets linked up with the environmental footprint of specific products (title of proposal: "Reduce your FOODprint" - Figure 3a); parking allocation and management pertaining to various user types (proposal: "Google Parking" — Figure 3b); and waste management associated with consumers' behavioral data (proposal: "Eat I t - Don't Waste I t " - Figure 3c). The projects sought to raise spatial, temporal, and thematic (STT) awareness about the aforementioned issues and, potentially, lead to respective operational and behavioral impacts (e.g. reduction of energy footprint, efficient mobility, change of habits, attitudes
or behaviors etc.). Further, they ensured that the information flow would be constantly fed back to decision-makers for performance (KPIs) and proposals assessment. However, more progress could be attained in a longer-term workshop or studio that would appropriately address the complexity of the parameters and methods this particular scienüfic field poses.
1. T h e Internet o f C i t i e s 2.
The
SmartScapes
Master
Class
poster
{Author's own)-. 3. S c h e m a t i c d i a g r a m of t h e workshop's exercise p r o c e d u r e (Author's o w n ) . 4abc.
T h e U M L Activity
developed
proposals
Diagrams
during
of t h e
the
three
SmartScapes
M a s t e r Class.
Conclusions
To conclude, the contemporary urbanist — and architect — is faced with an increasing hybridization of the urban environments. In order to deal with this emergent reality, (s)he must be equipped with an augmented set of tools and methods for design and decisionmaking, starting from the vocabulary itself New terms need to be incorporated and existing terminology reconfigured, so as to better adapt to the current and nearfuture conditions. I f we as architects and planners fail to do so, our role as integral actors and stakeholders in the design and decision-making processes is at risk. The reinvigorated discourse about Smart Cities can, in this case, establish an extensive spectrum of practice and research potential. A t present, large corporate companies, such as I B M and CISCO, are gradually taking the lead in this particular field, mainly approaching it from a business, utilitarian, and often mono-disciplinary perspective. Nevertheless, the new generation of urbanists (provided with the aforementioned tools and methods) can still play an impactful role in this area, in close collaboration with other experts. Collectively, they can leverage the abundance of real-time information to raise awareness and facilitate human participation in providing active feedback for various parameters of the city. As such, the focus will transition to sensitive urban environments that not only perform efficiendy in terms of infrastructure, but also serve to improve social inclusion.
Boulos,
Maged
N,
Crowdsourcing,
Kamel,
Citizen
et
Sensing
al.
(2011).
and
Sensor
W e b Technologies for Public and Environmental Health
Surveillance
Trends,
O G C
Examples.
on
Promise
(ed.).
(2009).
Marcus,
Informatics:
of
Real-Time
the
presented
at
the A C M
of
Practice
City.
Hershey,
Reference. &
Satchell,
Informatics,
2011
Paper
Conference
Cooperative
on
Work,
China.
Andrew
Designing
Vande,
for
the
of
Urban
Visualization
Technology, 19(2), Psyllidis,
Urban
Supported
Hangzhou,
Health
The
C h o i , Jaz H e e - j e o n g ,
(2011).
Moere,
of
Handbook
Urban
Christine.
Computer
Application
Journal
HQ\N Y o r k : I n f o r m a t i o n S c i e n c e Foth,
Management;
and
10(67).
Marcus
Research and
Crisis
International
Geographies, Foth,
and
Standards
Hili,
Dan.
(2012).
Situated
&
and
Public
Data.
Journal
of
Urban
25-46.
Achilleas,
&
Biloria,
Nimish.
The Adaptive City: A Socio-technical
(2013a).
Interaction-
d r i v e n A p p r o a c h Tov^/ards U r b a n S y s t e m s . presented
at
rEvolutions,
the
Hybrid
International
City
2013:
Paper Subtle
Conference,
Athens,
Greece. Psyllidis,
Achilleas,
&
Urban
Media
Geographies:
Ubiquitous Urban
Biloria,
Computing
Space.
Paper
Nimish.
v^'ith
the
presented
(2013b). Interfacing
Physicality at
City 4 : M E D I A CITIES, International
the
of
Media
Conference,
Buffalo NY. Townsend, Foth
Anthony.
(Ed.),
Informatics:
(2009),
Handbook
of
T h e Pi-actice
Real-Time City, N e w York;
Foreword.
Research
In
in
and Promise
M.
Urban of
the
Hershey.
Townsend, Anthony M. ( 2 0 1 3). Smart Cities; Big Data, Civic
Hackers, a n d the Quest
for a N e w
Utopia, N e w York: W . W . Norton & C o m p a n y , UNFPA,
(2007),
State
of
World
Population
2 0 0 7 : Unleasing t h e Potential of U r b a n N e w York: United Nations Population Weiser, 21st
Mark,
Century.
(1991).
The
Scientific
Growth.
Fund.
Computer American,
fot t h e 265(3),
94-104. Wurman,
Richard
Anxiety. N e w York:
Saul.
(1989).
Doubleday.
Information