Tag Archives: tracking

New report: Getting smarter about smart cities: Improving data privacy and data security

report launchAs part of ‘EU Data Protection Day’ a new report – “Getting smarter about smart cities: Improving data privacy and data security” – was launched today by Dara Murphy T.D., Minister for European Affairs and Data Protection.  The report, commissioned by the Data Protection Unit, Department of the Taoiseach (Irish Prime Minister) and written by Rob Kitchin (of The Programmable City project), is the first publication by the new Government Data Forum, a panel of experts drawn from across industry, civil society, academia and the public sector. The Forum advises Government on the opportunities and challenges for society and the economy arising from continued growth in the generation and use of personal data.  The report is available from the Department of the Taoiseach website or click here.

Executive Summary
Many cities around the world are seeking to become a smart city, using networked, digital technologies and urban big data to tackle a range of issues, such as improving governance and service delivery, creating more resilient critical infrastructure, growing the local economy, becoming more sustainable, producing better mobility, gaining transparency and accountability, enhancing quality of life, and increasing safety and security. In short, the desire is to use digital technology to improve the lives of citizens, finesse city management, and create economic development.

In this context, a wide range of smart city technologies are being deployed within urban environments, including city operating systems, centralised control rooms, urban dashboards, intelligent transport systems, integrated travel ticketing, bike share schemes, real-time passenger information displays, logistics management systems, smart energy grids, controllable lighting, smart meters, sensor networks, building management systems, and an array of smartphone apps and sharing economy platforms. All of these technologies generate huge quantities of data, much of them in real-time and at a highly granular scale.

These data about cities and their citizens can be put to many good uses and, if shared, for uses beyond the system and purposes for which they were generated. Collectively, these data create the evidence base to run cities more efficiently, productively, sustainably, transparently and fairly. However, generating, processing, analysing, sharing and storing large amounts of actionable data also raise a number of concerns and challenges.

Key amongst these are the data privacy, data protection, and data security issues that arise from the creation of smart cities. Many smart city technologies capture personally identifiable information (PII) and household level data about citizens – their characteristics, their location and movements, and their activities – link these data together to produce new derived data, and use them to create profiles of people and places and to make decisions about them. As such, there are concerns about what a smart city means for people’s privacy and what privacy harms might arise from the sharing, analysis and misuse of urban big data. In addition, there are questions as to how secure smart city technologies and the data they generate are from hacking and theft and what the implications of a data breach are for citizens. While successful cyberattacks on cities are still relatively rare, it is clear that smart city technologies raise a number of cybersecurity concerns that require attention.

To date, the approach to these issues has been haphazard and uncoordinated due to the ad-hoc manner in which they were developed. However, given the potential harms to citizens and the associated costs that can arise, and the potential benefits at stake, this approach should not be allowed to continue. The challenge is to rollout smart city solutions and gain the benefits of their deployment while maintaining infrastructure and system security and systematically minimising any pernicious effects and harms. This is no easy task, given the many stakeholders and vested interests involved and their differing aims and ambitions, and the diverse set of technologies and their complex arrangement.

This report details the development of smart cities and urban big data, highlights the various privacy and security concerns and harms related to the deployment and use of smart city technologies and initiatives, and makes a number of suggestions for addressing trepidations about and ills arising from data privacy, protection and security issues.

It argues that there is no single solution for ensuring that the benefits of creating smart cities are realised and any negative effects are neutralised. Rather, it advocates a multi-pronged approach that uses a suite of solutions, some of which are market driven, some more technical in nature (privacy enhancement technologies), others more policy, regulatory and legally focused (revised fair information practice principles, privacy by design, security by design, education and training), and some more governance and management orientated (at three levels: vision and strategy – smart city advisory board and smart city strategy; oversight of delivery and compliance – smart city governance, ethics and security oversight committee; and day-to-day delivery – core privacy/security team, smart city privacy/security assessments, and computer emergency response team).

These solutions provide a balanced, pragmatic approach that enable the rollout of smart city technologies and initiatives, but in a way that is not prejudicial to people’s privacy, actively work to minimise privacy harms, curtail data breaches, and tackle cybersecurity issues. They also work across the entire life-cycle (from procurement to decommissioning) and span the whole system ecology (all its stakeholders and components). Collectively they promote fairness and equity, protect citizens and cities from harms, and enable improved governance and economic development. Moreover, they do so using an approach that is not heavy handed in nature and is relatively inexpensive to implement. They are by no means definitive, but build on and extend work to date, advance the debate, and detail a practical route forward.

The report concludes that a core requirement for creating smart cities is the adoption of an ethical, principle-led approach designed to best serve the interests of citizens. In other words, being smart about how we plan and run cities consists of much more than deploying data-driven, networked technologies; it requires a smart approach.

No longer lost in the crowd? How people's location and movement is being tracked

Up until relatively recently tracking the location and movement of individuals was a slow, labour-intensive, partial and difficult process.  The only way to spatially track an individual was to follow them in person and to quiz those with whom they interacted.  As a result, people’s movement was undocumented unless there was a specific reason to focus on them through the deployment of costly resources.  Even if a person was tracked, the records tended to be partial, bulky, difficult to cross-tabulate, aggregate and analyze, and expensive to store.

A range of new technologies has transformed geo-location tracking to a situation where the monitoring of location is pervasive, continuous, automatic and relatively cheap, it is straightforward to process and store data, and easy to build up travel profiles and histories.  This is especially the case in cities, where these technologies are mostly deployed, though some operate pretty much everywhere.  Here are eleven (updated from 7 in original post) examples.

1.  Many cities are saturated with remote controllable digital CCTV cameras that can zoom, move and track individual pedestrians.  In addition, large parts of the road network and the movement of vehicles are surveyed by traffic, red-light, congestion and toll cameras.  Analysis and interpretation of CCTV footage is increasingly aided by facial, gait and automatic number plate recognition (ANPR) using machine vision algorithms.  Several police forces in cities in the UK have rolled out CCTV facial recognition programmes (1,2), as have cities in the U.S., including New York and Chicago (each with over 24,000 cameras) and San Diego (who are also using smartphones with facial recognition installed) (3).  ANPR cameras are installed in many cities for monitoring traffic flow, but also for administrating traffic violations such as the non-payment of road tolls and congestion charging.  There are an estimated 8,300 ANPR cameras across the UK capturing 30 million number plates each day (15).

2.  Smart phones continuously communicate their location to telecommunications providers, either through the cell masts they connect to, or the sending of GPS coordinates, or their connections to wifi hotspots.  Likewise, smart phone apps can access and transfer such information and also share them to third parties.  With respect to the latter Leszczynski’s analysis (14) of the data generated by The Wall Street Journal in 2011 (4) details that 25 out 50 iPhone apps, and 21 of 50 Android apps transmitted location data to a third party other than the app developer.  Of these, 19 of the iPhone apps and 13 of the Android apps did not require locational data as a functional requirement.  Half the iPhone and a third of the Android apps did not request consent for passing on the locational data.  These locational data are shared with advertisers and utilised by data brokers to create user profiles. For example, ‘Verizon have a product called Precision Market Insights that let businesses track cell phone users in particular locations’ (5).  It sells data ‘about its cell phone users’ “age range, gender and zip codes for where they live, work, shop and more” as well as information about mobile-device habits’ including URL visits, app downloads and usage, browsing trends and more’ (5).

3.  In a number of cities sensor networks have been deployed across street infrastructure such as bins and lampposts to capture and track phone identifiers such as MAC addresses.  In London, Renew installed such sensors on 200 bins, capturing in a single week in 2014 identifiers from 4,009,676 devices and tracking these as they moved from bin to bin (6).  The company reported that they could measure the proximity, speed, and manufacturer of a device and track the stores individuals visited, how long they stayed there, and how loyal customers are to particular shops, using the information to show contextual adverts on LCD screens installed on the bins (6).  The same technology is also used within malls and shops to track shoppers, sometimes linking with CCTV to capture basic demographic information such as age and gender (7, 8).

4.  Similarly, some cities have installed a wifi mesh, either to provide public wifi or to create a privileged emergency response and relief communication system in the event of an urban disaster or for general surveillance.  In the case of public wifi the IDs of the devices which access the networked are captured and can be tracked between wifi points.  In the case of an emergency/police mesh access might not be granted to the network, however each network access point can capture the device IDs, device type, apps installed, as well as the locational history (9). Such a wifi mesh, with 160 nodes, was installed by the Seattle Police Department in 2013 (9).  The locational history of previous wifi access points is revealed because a wifi-enabled device broadcasts the name of every network it has connected to previously in order to try and find one it can connect to automatically.  Such data reveals the movement of device owners between locations, revealing the sites of popular spots such as home, work, and where they shop.  Beyond a wifi-mesh, anyone with a wi-fi adapter in monitor mode and a packet capture utility can capture such data (12).

5.  Many buildings use smart card tracking, with unique identifiers installed either through barcodes or embedded RFID chips.  Cards are used for access control to different parts of the building and to register attendance, but can also be used as an electronic purse to pay for items within the facility.  Smart card tracking is becoming increasingly common in many schools to track and trace student movements, activities and food consumption (10).  Smart cards are also used to access and pay for public transport, such as the Leapcard in Dublin or the Oyster Card in London. Each reading of the card adds to the database of movement within a campus or across a city.

6.  New vehicles are routinely fitted with GPS that enables the on-board computers to track location, movement, and speed.  These devices can be passive and store data locally to be downloaded for analysis at a latter point, or be active, communicating in real-time via cellular or satellite networks to another device or data centre.  Active GPS tracking is commonly used in fleet management to track goods vehicles, public transport and hire cars, or to monitor cars on a payment plan to ensure that it can be traced and recovered in cases of default, or in private cars as a means of theft recovery.   Moreover, cars are increasingly being fitted with unique ID transponders that are used for the automated operation and payment of road tolls and car parking.  Again, each use of the transponder is logged, creating a movement data trail, though with a larger spatial and temporal granularity (at selected locations).

7.  There are also many other staging points where we might leave an occasional trace of our movement and activities, such as using ATMs, or a credit card in a store, or checking a book out of a library.

UPDATE: I’ve had three further ways of tracking people pointed out to me (thanks Linda, Stephen, Jim) and I also thought of one more.  Plus I’ve updated method 4 (thanks Paul-Olivier).

8.  Selected populations — such as people on probation, prisoners on home leave, people with dementia, children — are being electronically tagged to enable tracking.  Typically this done using a GPS-enabled bracelet that periodically transmits location and status information via a wireless telephone network to a monitoring system.  In other cases, it is possible to install tracker apps onto a phone (of say children) so the phone location can be tracked, or to buy a family tracking service from telecoms providers (11)

9. Another form of staging point is the use of the Internet, such as browsing or sending email, where the IP address of the computer reveals the approximate location from which it is connected.  Typically this does not have a fine spatial resolution (mile to city or region scale), but does show sizable shifts of location between places.

10.  Another set of staging points can be revealed from the geotagging (using the device GPS) and time/date stamping of photos and social media posted on the internet and recorded in their associated metadata.  This has more spatial resolution than IP addresses and is also accompanied with other contextual information such as the content of the photo/post.  Such data can be used in interesting ways such as tackling cyber-bullying by revealing the location of posters (13).

11.  Location and movement can also be voluntarily shared by individuals through online calenders, most of which are private but nonetheless stored in the cloud, and some of which are shared openly or with colleagues.

As these examples demonstrate, those companies and agencies who run these technologies possess a vast quantity of highly detailed spatial behaviour data from which lots of other insights can be inferred (such as mode of travel, activity, and lifestyle).  These data can also be shared between data brokers and third parties and combined with other personal and contextual information.  For example, Angwin (5) has identified 58 data brokers in the mobile and location tracking business in the US, only 11 of which offered opt-outs (in total she found 212 data brokers operating in the US that consolidated and traded data about people, only 92 of which allowed opt-outs – 65 of which required handing over additional data to secure the opt-out).  Moreover, these data can be accessed by the police and security forces through warrants or more surreptitiously.  The consequence is that individuals are no longer lost in the crowd, but rather they are being tracked and traced at different scales of spatial and temporal resolution, and are increasingly becoming open to geo-targeted profiling for advertising and social sorting.

If you can think of other ways location/mobility is being tracked, please leave a comment – thanks.

Rob Kitchin

(1)  Graham, S. (2011) Cities Under Siege: The New Military Urbanism.  Verso, London.
(2)  Gardham, M. (2015) Controversial face recognition software is being used by Police Scotland, the force confirms. Herald Scotland, 26th May http://www.heraldscotland.com/news/13215304.Controversial_face_recognition_software_is_being_used_by_Police_Scotland__the_force_confirms/
(3)  Wellman, T. (2015) Facial Recognition Software Moves From Overseas Wars to Local Police. New York Times, 12th August. http://www.nytimes.com/2015/08/13/us/facial-recognition-software-moves-from-overseas-wars-to-local-police.html
(4)  http://blogs.wsj.com/wtk-mobile/
(5)  Angwin, J. (2014) Dragnet Nation. St Martin’s Press, New York
(6)  Vincent, J. (2014) London’s bins are tracking your smartphone. The Independent. June 10th http://www.independent.co.uk/life-style/gadgets-and-tech/news/updated-londons-bins-are-tracking-your-smartphone-8754924.html
(7)  Kopytoff, V. (2013) Stores Sniff Out Smartphones to Follow Shoppers, Technology Review, Nov 12th http://www.technologyreview.com/news/520811/stores-sniff-out-smartphones-to-follow-shoppers/
(8)  Henry, A. (2013) How Retail Stores Track You Using Your Smartphone (and How to Stop It). Lifehacker, 19 July, http://lifehacker.com/how-retail-stores-track-you-using-your-smartphone-and-827512308
(9)  Hamm, D. (2013) Seattle police have a wireless network that can track your every move. Kirotv.com, 23 November. http://www.kirotv.com/news/news/seattle-police-have-wireless-network-can-track-you/nbmHW/ cited in Leszczynski, A. (forthcoming) Geoprivacy.  In Kitchin, R., Lauriault, T. And Wilson, M. (eds) Understanding Spatial Media. Sage, London.
(10) Goodman, M. (2015) Future Crimes: A Journey to the Dark Side of Technology – and How to Survive It.  Bantam Press, New York.
(11) see http://gizmodo.com/how-to-stalk-a-cheater-using-satellites-and-cell-phones-1546627447
(12) Gallagher, S. (2014) Where’ve you been? Your smartphone’s Wi-Fi is telling everyone. Ars Technica, Nov 5th, http://arstechnica.com/information-technology/2014/11/where-have-you-been-your-smartphones-wi-fi-is-telling-everyone/
(13) Riotta, C. (2015) How Facebook and Twitter Geotagging Is Exposing Racist Trolls in Real Life.  Tech.mic, Dec 2nd, http://mic.com/articles/129506/how-facebook-and-twitter-geotagging-is-exposing-racist-trolls-in-real-life
(14) Leszczynski, A. (forthcoming) Geoprivacy.  In Kitchin, R., Lauriault, T. And Wilson, M. (eds) Understanding Spatial Media. Sage, London.
(15) Weaver, M. (2015) Warning of backlash over car number plate camera network. The Guardian, 27 Nov. http://www.theguardian.com/uk-news/2015/nov/26/warning-of-outcry-over-car-numberplate-camera-network