The real-time city? Big data and smart
urbanism
For the past two decades urban analysts have been charting
the evolution of cities during an era where information and communication
technologies have been rapidly increasing. Wired cities are cities who have
embraced this technology change and are using it to benefit their city, they
are also labelled as cyber cities, digital cites. These cities fall under the
category of smart cities, a term which describes cities in which smart devices
are built into the fabric of the urban environment around it. These can be
things like wireless technology, digitally controlled utility services and
transport infrastructure etc. These smart cities have a rich stream of data
that can be used to analyse people movements, popular places and more
importantly be used to create a better urban lifestyle for the residents who
live there. It can also be used to improve the delivery of public services and
creating a more efficient city.
Smart cities are becoming increasingly common, with greater
access to technology and cheaper prices, cities can now afford to make a switch
to becoming a smart city. Big data is seen as providing objective, neutral
measures that are free of political ideology as to what is occurring in a city.
However, the enormous, varied, dynamic and interconnected datasets are
vulnerable to a range of different issues, already taking place in areas such
as Israel.
In this reading, the data explosion that has occurred over
the past decade, the role of cities as key sites in the production of such
data, and how these data are being used to re-imagine and regulate the urban
life are examined. In particular, the analysis concentrates on the new
phenomena of ‘big data’ and the generation of enormous, varied, dynamic, and
interconnected datasets that hold the promise of what some see as a truly smart
city.
Based on the reading
‘The real-time city? Big data and smart urbanism’ by Rob Kitchin, we will be
outlining what big data is, real-time analytics and identifying five
characteristics of a smart city.
Big data and cities:
There has been long production of very large datasets, like
census and government records. These data sets provide information about these
cities and also the people that live in the cities.
Businesses have also collected data to analyse what the
operations, markets and consumers they are dealing with. These data sets rely
on samples and are non-continuous. Meaning that large data sets need to be
accompanied with small data sets, e.g. surveys questionnaires.
This capturing a tightly focused sample for more specific
results.
The hype and hope of big city data transformation thorough
the creation of a data deluge will create a much more sophisticated wider
scale, finer grained, real time understanding and controlled urbanity.
There is no academic or industrial definition of big city
data but surveys that have been done give a number of key features:
·
Huge in volume
·
Huge in velocity
·
Diverse in variety
·
Exhaustive in scope
·
Fine grained in resolution
·
Flexible
There has been a transformation since the early 2000’s with
the volume of data generated. With consumers, produces now being able to store
data on disk drives, laptops etc.
Based on the review of data volume growth, many projected a
growth of 40% of data generated per year globally.
Such data growth is due to new technology, new
infrastructure etc.
Technology getting better has allowed people to access
records and evaluate data easily.
Sources of big data: divided into
three sections:
Directed- traditional forms of surveillance, cameras etc. it
is based on a person or a place and operated by a human
Automated- Inherited automatic data, the data is generated
as an inherent, automatic function of the devise or system
Volunteered- data is gifted by uses, these include things
like interactions across social media, observations and the uploading of photos
and videos.
Directed and volunteered data can be useful for planning
urban cities it is automated data that has the biggest impact. It can record
for longer and doesn’t need any assistance from humans
Urban places are also now full of automated machines and
objects. These include automatic doors, security alarms, and Wi-Fi routers.
These devices also transmit data between each other.
The data collections can be generated by local governments
and state agencies, and some by private companies and they are not all open in
nature.
These data collections provide an abundant, systemic,
dynamic way of providing real time analysis for governance.
The Real Time City
Many city Governments use real-time analytics to manage
aspects of how a city functions and is regulated. This is the use of, or the
capacity to use all available enterprise data and resources when they are
needed. An example of real-time analytics relates to the movement of vehicles
around a transportation network. As this image shows, data from a network of
cameras and transponders are fed back to a central control hub to monitor the
flow of traffic and to adjust traffic light sequences and speed limits. They
are also used to automatically administer penalties for traffic violations.
Data relating to environmental conditions might be collected
from a sensor network distributed throughout the city. Examples of
environmental data include air pollution, water levels and seismic activity.
Similarly, the police may monitor a group of cameras and live incidents logs to
direct appropriate resources to particular areas. Local governments often use
management systems to analyse public engagement with the services that they
provide and monitor whether things need to be adjusted or implemented. There
has recently been an attempt to draw all of these kinds of surveillance and
analytics into one single hub, supplemented by broader public and open data
analytics. For example, a partnership between the city government and IBM in
Rio, Brazil, has developed a city wide instrumented system that draws together
data streams from 30 agencies. This includes traffic and transport, municipal
and utility services, emergency services, weather feeds and information sent in
by employees and the public via phones and radio.
A team of analysts then process, visualise, analyse and
monitor the data, then investigate different aspects of city life that change
over time and build productive models with respect to city development and
management of disaster situations. This is then complemented by a virtual
operations platform that enables city officials to log-in from the field to
access the real time information. For example, police at an accident scene can
use the platform to see how many ambulances have been dispatched and when to
upload additional information. The overall aim of this platform was to knock
down the silos between departments and combine each ones data to help the whole
enterprise.
The Office of Policy and Strategic Planning in New York have
taken this initiative even further by making their data available in open form,
enabling developers to build apps that take the data and rework and repackage
it for daily consumption by city dwellers.
Likewise, an initiative called DubLinked, provides
operational data from Dublin’s four local authorities in an open format. This
is an ideas and information sharing network which connects these authorities
with universities, companies and entrepreneurs. The initiative was launched in
October 2011, bringing people together to test new ideas using live city data
and to develop new products and services using the city as a testing ground.
Dublin’s brick lanes, lush parks and grey river banks have been linked with
high-tech sensors capable of gathering a range of information. Dublin is a good
‘prototype’ city, being big enough to have complex city systems that could be
scaled internationally but small enough so that big city problems become local and
can be solved.
Over 250 datasets are available for download through the
DubLinked data store, including planning applications, real time traffic
information, environment and emergency services. DubLinked consists of data
that is open to everybody and a research zone where data is shared among
members. The city council hopes the futuristic network will attract interest
from investors and companies looking to innovate the city. They also hope that
tourists will eventually be able to move through the city, guided by an app and
local businesses will be able to send out special offers to passers-by
electronically. Although it has been recognised that there will be ethical and
privacy issues, more than 94% of Dubliners surveyed said that they would like
to see Dublin used as an experimental site for new technologies. In London,
they have also developed a city dashboard, where the public can find
information on the weather, air pollution, the stock market and even London’s
happiness level.
For those developing and using integrated, real time city
data analytics, these centres, apps and dashboards provide a powerful means for
making sense of, managing and living in the city, while envisioning and
predicting future scenarios. The use of large samples and the linking of
diverse forms of data provide a deeper, more holistic and robust analysis.
Politics of big urban data:
Data within smart cities are portrayed as lacking political
ideology. But data is simply data. Cameras or sensors have no political agenda.
Big data presents an image of being politically benign, but it makes a city
safer, more secure, efficient and more productive.
Technocratic governance and city
development
The drive towards managing and regulating the city via
information and analytic systems promotes a technocratic mode of urban
governance which presumes that all aspects of a city can be measured and
monitored and treated as technical problems which can be addressed through
technical solutions. Through the use of real-time data, it is possible to
model, understand, manage and fix a situation as it unfolds. However, it is
suggested that big data urbanism suffers from datafication; the presumption
that all meaningful flows and activities can be measured.
Employing an evidence based, algorithmic processed approach
to city governance may seemingly ensure rational, logical and impartial
decisions. Technocratic governance also provides city managers with a defence
against decisions that raise ethical and accountability concerns by enabling
them to say ‘it’s not me – it’s the data’. Technocratic forms of governance are
highly narrow in scope, based on a limited set of data and failing to take into
account the wider effects of culture, politics, policy, governance and capital
that shape city life and how it unfolds. Technological solutions on their own
are not going to solve the deep rooted structural problems in cities as they do
not address their root causes. Further, control and command systems centralise
power and decision making into a select set of offices, at the same time that
they make elements of the data publicly available.
The corporatisation of city
governance and technological lock-in:
Alongside the critique that smart city governance is a
concern that is being shaped by corporate interests for their own gain.
The smart city agenda and associated technologies are
heavily prompted by a number of large software companies who view city
governance as a long term market potential.
The concern is threefold:
The first is that it actively promotes neo-liberal politics
It creates a technological lock-in
And the third is that it leads to a one size fits all
Buggy, brittle and hackable cities
The embedding and use of computer systems in city
environments is creating city services and spaces that are dependent on
software function. Therefore, if software fails a space may not be produced as
intended as the old analogue system and associated knowledge has been entirely
replaced. For example if the software used to control a subway system crashes,
then the trains do not run. Also, if a supermarkets checkout tills crash,
shoppers can no longer purchase products. As such, while potentially solving a
diverse set of urban problems, the creation of spaces through smart city
projects leaves cities vulnerable to other issues. In particular, it has the
potential to create spaces prone to viruses, glitches, crashes and security
hacks.
As systems become even more complicated, interconnected and
dependent on software, the challenge of producing stable, robust and secure
devices and infrastructure increases. For example, the Israel government
acknowledges that its essential services such as water, electricity, banking
and road infrastructure are the target of numerous cyber hacks, with Israel
Electric Corporation reporting that it receives 6,000 attempted hacks every
second. However, while the deployments of smart technologies have had many
issues, they have been relatively robust despite their vulnerabilities. With
more and more systems being established, the main questions asked have been
‘when will these smart cities fail and how much damage will they cause when
they crash?’
The panoptic city:
Over the last couple of decades with increased surveillance
and automated digital technologies, there has been increasing concern about
this surveillance. Because it is now possible to track and trace any
individual.
This increase in surveillance has been driven by a growing
culture of control, which desires security. Big data control centres that
integrate and combine data streams together are almost raising the spectre of a
big brother society.
Conclusion:The notion of smart cities has gained much traction in recent years as a vision for stimulating and supporting innovation and economic growth, and providing sustainable and efficient urban management and development. One significant aspect of the smart cities concept is the production of sophisticated data analytics for understanding, monitoring, regulating and planning the city. As cities have become increasingly dependent on digital infrastructure and networks, devices and sensors, data available about cities and their citizens has grown exponentially.
For citizens, this data offers insights into city life, aids
everyday living and decision making and empowers alternative visions for city
development. For governments, big data and integrated analysis and control
centres offer more efficient and effective city management and regulation. For
corporations, big data analytics offers new, long term business opportunities
as key players in city governance.
However, there are a number of concerns with the
possibilities of technological lock-in, system vulnerabilities, ethical issues
and concerns relating to data quality, security and the validity of analytics.
There is a pressing need to interrogate the nature and production of urban big
data, the composition and functioning of urban analytics and control centres,
and the implications of technocratic, corporatized and real-time forms of
governance.
