207:
applications) user input. Urban computing can help select better driving routes, which is important for applications like Waze, Google Maps, and trip planning. Wang et al. built a system to get real-time travel time estimates. They solve the problems: one, not all road segments will have data from GPS in the last 30 minutes or ever; two, some paths will be covered by several car records, and it’s necessary to combine those records to create the most accurate estimate of travel time; and three, a city can have tens of thousands of road segments and an infinite amount of paths to be queried, so providing an instantaneous real time estimate must be scalable. They used various techniques and tested it out on 32670 taxis over two months in
Beijing, and accurately estimated travel time to within 25 seconds of error per kilometer.
136:
researchers engaged in ethnography, collective memory, and public history have leveraged urban computing strategies to introduce platforms that enable people to share their interpretation of the urban environment. Examples of such projects include CLIO—an urban computing system that came out of the
Collective City Memory of Oulu study—which "allows people to share personal memories, context annotate them and relate them with city landmarks, thus creating the collective city memory." and the Cleveland Historical project which aims to create a shared history of the city by allowing people to contribute stories through their own digital devices.
145:
vehicles, refueling data from gas stations, and self-reporting online participants. From this, knowledge of the density and speed of traffic traversing a city's road network can be used to suggest cost-efficient driving routes, and identify road segments where gas has been significantly wasted. Information and predictions of pollution density gathered in this way could also be used to generate localized air quality alerts. Additionally, these data could produce estimates of gas stations’ wait times to suggest more efficient stops, as well as give a geographic view of the efficiency of gas station placement.
162:(WHO) have taken to Twitter and other social media platforms, to provide rapid dissemination of disease outbreaks, medical discoveries, and other news. Beyond simply tracking the spread of disease, urban computing can even help predict it. A study by Jeremy Ginsberg et al. discovered that flu-related search queries serve as a reliable indicator of a future outbreak, thus allowing for the tracking of flu outbreaks based on the geographic location of such flu-related searches. This discovery spurred a collaboration between the CDC and Google to create a map of predicted flu outbreaks based on this data.
182:
Familiar
Stranger introduces several categories of interaction ranging from family to strangers and interactions ranging from personal to in passing. Social interactions can be facilitated by purpose-built devices, proximity aware applications, and “participatory” applications. These applications can use a variety techniques for users to identify where they are ranging from “checking in” to proximity detection, to self-identification. Examples of geographically aware applications include
173:(CRF) has shown that air pollution for a large area can be predicted based on the data from a small number of air pollution monitoring stations. These findings can be used to track air pollution and to prevent the adverse health effects in cities already struggling with high pollution. On days when air pollution is especially high, for example, there could be a system in place to alert residents to particularly dangerous areas.
240:
run by their transit authority. Originally, it required users to have a membership. They changed it to not require a membership after a while, and analyzed data of when and where bikes were rented and returned, to see what areas were active and what trends changed. They found that removing membership
257:
There are also attempts to infer the unknown air quality all across the city from just the samples taken at stations, such as by estimating car emissions from floating car data. Zheng et al. built a model using machine learning and data mining called U-Air. It uses historical and real-time air data,
253:
Various ways of adding more sensors to the cityscape have been researched, including
Copenhagen wheels (sensors mounted on bike wheels and powered by the rider) and car-based sensors. While these work for carbon monoxide and carbon dioxide, aerosol measurement stations aren’t portable enough to move
241:
was a good decision that increased weekday commutes somewhat and heavily increased weekend usage. Based on the patterns and characteristics of a bicycle sharing system, the implications for data-driven decision supports have been studied for transforming urban transportation to be more sustainable.
261:
Chet et al. developed a system to monitor air quality indoors, which were deployed internally by
Microsoft in China. The system is based in the building’s HVAC (heating, ventilation, air conditioning) units. Since HVACs filter the air of PM 2.5, but don’t check if its necessary, the new system can
249:
Urban computing has a lot of potential to improve urban quality of life by improving the environment people live in, such as by raising air quality and reducing noise pollution. Many chemicals that are undesirable or poisonous are polluting the air, such as PM 2.5, PM 10, and carbon monoxide. Many
228:
Uber is an on-demand taxi-like service where users can request rides with their smartphone. By using the data of the active riders and drivers, Uber can price discriminate based on the current rider/driver ratio. This lets them earn more money than they would without “surge pricing,” and helps get
181:
Mobile computing platforms can be used to facilitate social interaction. In the context of urban computing, the ability to place proximity beacons in the environment, the density of population, and infrastructure available enables digitally facilitated interaction. Paulos and
Goodman's paper The
144:
Energy consumption and pollution throughout the world is heavily impacted by urban transportation. In an effort to better utilize and update current infrastructures, researchers have used urban computing to better understand gas emissions by conducting field studies using GPS data from a sample of
119:
Urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human, to tackle the major issues that cities face. Urban computing connects unobtrusive and
232:
Urban computing can also improve public transportation cheaply. A University of
Washington group developed OneBusAway, which uses public bus GPS data to provide real-time bus information to riders. Placing displays at bus stops to give information is expensive, but developing several interfaces
206:
One of the major application areas of urban computing is to improve private and public transportation in a city. The primary sources of data are floating car data (data about where cars are at a given moment). This includes individual GPS’s, taxi GPS’s, WiFI signals, loop sensors, and (for some
85:
for people affected by cities. What further differentiates urban computing from traditional remote sensing networks is the variety of devices, inputs, and human interaction involved. In traditional sensor networks, devices are often purposefully built and specifically deployed for monitoring
135:
Cities are more than a collection of places and people - places are continually reinvented and re-imagined by the people occupying them. As such, the prevalence of computing in urban spaces leads people to supplement their physical reality with what is virtually available. Toward this end,
258:
meteorology, traffic flow, human mobility, road networks, and points of interest, which are fed to artificial neural networks and conditional random fields to be processed. Their model is a significant improvement over previous models of citywide air quality.
250:
cities measure air quality by setting up a few measurement stations across the city, but these stations are too expensive to cover the entire city. Because air quality is complex, it’s difficult to infer the quality of air in between two measurement stations.
120:
ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods, to create win-win-win solutions that improve urban environment, human life quality, and city operation systems.
153:
Smart phones, tablets, smart watches, and other mobile computing devices can provide information beyond simple communication and entertainment. In regards to public and personal health, organizations like the
638:
Kukka, Hannu; Luusua, Anna; Ylipulli, Johanna; Suopajärvi, Tiina; Kostakos, Vassilis; Ojala, Timo (2014). "From cyberpunk to calm urban computing: Exploring the role of technology in the future cityscape".
1194:
Xie, Xiao-Feng; Wang, Zunjing (2018). "Examining travel patterns and characteristics in a bikesharing network and implications for data-driven decision supports: Case study in the
Washington DC area".
233:(apps, website, phone response, SMS) to OneBusAway was comparatively cheap. Among surveyed OneBusAway users, 92% were more satisfied, 91% waited less, and 30% took more trips.
561:. Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational (NordiCHI '14). New York, New York, USA: ACM Press. pp. 658–667.
1251:. UbiComp '14: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, New York, USA: ACM Press. pp. 471–475.
928:. KDD '13: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. New York, New York, USA: ACM Press. pp. 1436–1444.
804:. KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. New York, New York, USA: ACM Press. pp. 1027–1036.
768:. UbiComp '13: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. New York, New York, USA: ACM Press. pp. 13–22.
1038:
958:
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such as temperature, noise, and light. As an interdisciplinary field, urban computing also has practitioners and applications in fields including
46:
at the 2004 UbiComp conference and in his paper The
Familiar Stranger co-authored with Elizabeth Goodman. Although closely tied to the field of
1122:. CHI '10: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, New York, USA: ACM Press. pp. 1807–1816.
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400:
355:
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Quercia, Daniele; Schifanella, Rossano; Aiello, Luca Maria; Kate, McLean (2015). "Smelly maps: the digital life of urban smellscapes".
1151:
Lathia, Neal; Ahmed, Saniul; Capra, Licia (2012). "Measuring the impact of opening the London shared bicycle scheme to casual users".
35:, computational power, and data to improve the quality of densely populated areas. Urban computing is the technological framework for
461:
448:. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, New York, USA: ACM Press. pp. 223–230.
957:
Zheng, Yu; Chen, Xuxu; Jin, Qiwei; Chen, Yubiao; Qu, Xiangyun; Liu, Xin; Chang, Eric; Ma, Wei-Ying; Rui, Yong; Sun, Weiwei (2014).
236:
Making decisions on transportation policy can also be aided with urban computing. London’s Cycle Hire system is a heavily used
70:
265:
Another source of data is social media data. In particular, geo-referenced picture tags have been successfully used to infer
747:
54:
by saying that urban computing, urban technology, and urban infrastructure focus more on technological dimensions whereas
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Urban computing can also be used to track and predict pollution in certain areas. Research involving the use of
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977:
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335:
805:
521:
512:
Akyildiz, I.F.; Su, W.; Sankarasubramaniam, Y.; Cayirci, E. (2002). "Wireless sensor networks: a survey".
315:
237:
379:
Kamilaris, Andreas; Pitsillides, Andreas; Prenafeta-Bold, Francesc X.; Ali, Muhammad
Intizar (May 2017).
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in that collections of devices are used to gather data about the urban environment to help improve the
1377:
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Jabeur, Nafaâ; Zeadally, Sherali; Sayed, Biju (2013-03-01). "Mobile social networking applications".
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810:
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66:
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186:, an application that facilitates anonymous social interaction based on proximity of other users,
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Chen, Xuxu; Zheng, Yu; Chen, Yubiao; Jin, Qiwei; Sun, Weiwei; Chang, Eric; Ma, Wei-Ying (2014).
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Handbook of Research on Urban Informatics: The Practice and Promise of the Real-Time City
194:
game to encourage users to interact with the area around them as well as each other, and
1381:
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430:(workshop). Sixth International Conference on Ubiquitous Computing. Nottingham, England.
198:, which provides recommendations about services to users based on a specified location.
1398:
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222:
187:
107:
99:
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Aiello, Luca Maria; Schifanella, Rossano; Quercia, Daniele; Aletta, Francesco (2016).
535:
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1103:
730:"Greenhouse Gas Emissions: Transportation Sector Emissions - Climate Change - US EPA"
624:
365:
1233:
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OneBusAway: results from providing real-time arrival information for public transit
1023:
652:
595:
Zheng, Yu; Capra, Licia; Wolfson, Ouri; Yang, Hai (2014-09-18). "Urban Computing".
543:
95:
959:"A Cloud-Based Knowledge Discovery System for Monitoring Fine-Grained Air Quality"
886:
347:
900:
273:
266:
103:
43:
381:"A Web of Things based eco-system for urban computing - towards smarter cities"
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Inferring gas consumption and pollution emission of vehicles throughout a city
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36:
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1356:"Chatty maps: constructing sound maps of urban areas from social media data"
1256:
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24:
1407:
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65:, urban computing draws from the domains of wireless and sensor networks,
74:
1389:
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683:
707:
674:
Christopoulou, Eleni; Ringas, Dimitrios; Stefanidakis, Michail (2012).
218:
183:
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Shang, Jingbo; Zheng, Yu; Tong, Wenzhu; Chang, Eric; Yu, Yong (2014).
58:
focuses on the social and human implications of technology in cities.
557:
Kukka, Hannu; Ylipulli, Johanna; Luusua, Anna; Dey, Anind K. (2014).
32:
678:. 16th Panhellenic Conference on Informatics (PCI). IEEE. pp.56,61.
608:
424:
Paulos, Eric; Anderson, Ken; Townsend, Anthony (September 7, 2004).
1372:
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Quercia, Daniele; Schifanella, Rossano; Aiello, Luca Maria (2016).
1294:
1208:
478:
446:
The familiar stranger: anxiety, comfort, and play in public places
336:"Urban Computing: The Technological Framework for Smart Cities"
262:
save energy by preventing HVACs from running when unnecessary.
845:"Detecting influenza epidemics using search engine query data"
385:
2017 24th International Conference on Telecommunications (ICT)
764:
Zhang, Fuzheng; Wilkie, David; Zheng, Yu; Xie, Xing (2013).
676:
Experiences from the Urban Computing Impact on Urban Culture
229:
more drivers out on the street in unpopular working hours.
1249:
Indoor air quality monitoring system for smart buildings
736:. 2012-03-16. Archived from the original on 2014-07-04.
50:, Marcus Foth differentiates the two in his preface to
926:
U-Air: when urban air quality inference meets big data
603:(3). Association for Computing Machinery (ACM): 1–55.
597:
ACM Transactions on Intelligent Systems and Technology
1153:
Transportation Research Part C: Emerging Technologies
1319:"The Emotional and Chromatic Layers of Urban Smells"
1118:
Ferris, Brian; Watkins, Kari; Borning, Alan (2010).
1002:(3). Association for Computing Machinery (ACM): 71.
342:. Springer International Publishing. pp. 1–25.
42:The term "urban computing" was first introduced by
27:in urban areas. This involves the application of
924:Zheng, Yu; Liu, Furui; Hsieh, Hsun-Ping (2013).
795:
793:
117:
23:which pertains to the study and application of
483:. Hershey, PA: Information Science Reference.
766:Sensing the pulse of urban refueling behavior
8:
641:Technological Forecasting and Social Change
334:Bouroche, MĂ©lanie; Dusparic, Ivana (2020).
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156:Centers for Disease Control and Prevention
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1371:
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444:Paulos, Eric; Goodman, Elizabeth (2004).
279:(linked to sound quality) at city level.
52:Handbook of Research on Urban Informatics
759:
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1039:"Cycle cities awarded bicycle counters"
326:
125:Yu Zheng, Urban Computing with Big Data
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590:
588:
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559:Urban computing in theory and practice
7:
73:. Urban computing uses many of the
221:at a certain spot in order to help
14:
843:Ginsberg, J; et al. (2009).
1226:10.1016/j.jtrangeo.2018.07.010
1196:Journal of Transport Geography
653:10.1016/j.techfore.2013.07.015
1:
536:10.1016/S1389-1286(01)00302-4
427:UbiComp in the Urban Frontier
348:10.1007/978-3-030-15145-4_5-1
708:"About Cleveland Historical"
272:(linked to air quality) and
110:, and energy, among others.
1074:(in German). Archived from
1037:Magni, Marie (2012-06-06).
1448:
1360:Royal Society Open Science
1043:Cycling Embassy of Denmark
167:artificial neural networks
71:human-computer interaction
1173:10.1016/j.trc.2011.12.004
996:Communications of the ACM
746:: CS1 maint: unfit URL (
171:conditional random fields
160:World Health Organization
114:Applications and examples
393:10.1109/ICT.2017.7998277
340:Handbook of Smart Cities
1257:10.1145/2632048.2632103
1159:. Elsevier BV: 88–102.
1128:10.1145/1753326.1753597
1008:10.1145/2428556.2428573
934:10.1145/2487575.2488188
820:10.1145/2623330.2623653
774:10.1145/2493432.2493448
567:10.1145/2639189.2639250
217:to count the number of
21:interdisciplinary field
710:. Cleveland Historical
316:Human City Interaction
238:bicycle-sharing system
128:
477:Foth, Marcus (2009).
454:10.1145/985692.985721
61:Within the domain of
289:Ubiquitous computing
225:with reliable data.
215:computing technology
79:ubiquitous computing
25:computing technology
1390:10.1098/rsos.150690
1382:2016RSOS....350690A
1341:2016arXiv160506721Q
1304:2015arXiv150506851Q
1218:2018JTGeo..71...84X
1165:2012TRPC...22...88L
1098:"Pricing the surge"
901:"Google Flu Trends"
870:10.1038/nature07634
861:2009Natur.457.1012G
855:(7232): 1012–1014.
684:10.1109/pci.2012.53
67:information science
1068:"Fahrradbarometer"
213:are an example of
177:Social Interaction
140:Energy consumption
131:Cultural archiving
1266:978-1-4503-2968-2
1137:978-1-60558-929-9
1101:. Free exchange.
943:978-1-4503-2174-7
829:978-1-4503-2956-9
783:978-1-4503-1770-2
693:978-1-4673-2720-6
576:978-1-4503-2542-4
514:Computer Networks
490:978-1-60566-152-0
402:978-1-5386-0643-8
357:978-3-030-15145-4
294:Urban informatics
192:augmented reality
92:civil engineering
56:urban informatics
48:urban informatics
29:wireless networks
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1107:. 2014-03-29.
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