The real-time city? Big data and smart urbanism

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.

 Five concerns about a real time city:

 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.