Abstract
Today's societies are enveloped in an ever-growing telecommunication infrastructure. This infrastructure offers important opportunities for sensing and recording a multitude of human behaviors. Human mobility patterns are a prominent example of such a behavior which has been studied based on cell phone towers, Bluetooth beacons, and WiFi networks as proxies for location. While mobility is an important aspect of human behavior, it is also crucial to study physical interactions among individuals. Sensing proximity that enables social interactions on a large scale is a technical challenge and many commonly used approaches—including RFID badges or Bluetooth scanning—offer only limited scalability. Here we show that it is possible, in a scalable and robust way, to accurately infer person-to-person physical proximity from the lists of WiFi access points measured by smartphones carried by the two individuals. Based on a longitudinal dataset of approximately 800 participants with ground-truth Bluetooth proximity collected over a year, we show that our model performs better than the current state-of-the-art. Our results demonstrate the value of WiFi signals as a tool for social sensing and show how collections of WiFi data pose a potential threat to privacy.
- Lada A Adamic and Eytan Adar. 2003. Friends and neighbors on the web. Social networks 25, 3 (2003), 211--230.Google Scholar
- Nadav Aharony, Wei Pan, Cory Ip, Inas Khayal, and Alex Pentland. 2011. Social fMRI: Investigating and shaping social mechanisms in the real world. Pervasive and Mobile Computing 7, 6 (2011), 643--659. Google ScholarDigital Library
- Giuseppe Anastasi, Renata Bandelloni, Marco Conti, Franca Delmastro, Enrico Gregori, and Giovanni Mainetto. 2003. Experimenting an indoor bluetooth-based positioning service. In Distributed Computing Systems Workshops, 2003. Proceedings. 23rd International Conference on. IEEE, 480--483. Google ScholarDigital Library
- Paramvir Bahl and Venkata N Padmanabhan. 2000. RADAR: An in-building RF-based user location and tracking system. In INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, Vol. 2. Ieee, 775--784.Google ScholarCross Ref
- Darcy Bullock, Ross Haseman, Jason Wasson, and Robert Spitler. 2010. Automated measurement of wait times at airport security: deployment at Indianapolis international airport, Indiana. Transportation Research Record: Journal of the Transportation Research Board 2177 (2010), 60--68.Google ScholarCross Ref
- Alessandro Carlotto, Matteo Parodi, Carlo Bonamico, Fabio Lavagetto, and Massimo Valla. 2008. Proximity Classification for Mobile Devices Using Wi-fi Environment Similarity. In Proceedings of the First ACM International Workshop on Mobile Entity Localization and Tracking in GPS-less Environments (MELT ‘08). ACM, New York, NY, USA, 43--48. Google ScholarDigital Library
- Iacopo Carreras, Aleksandar Matic, Piret Saar, and Venet Osmani. 2012. Comm2Sense: Detecting proximity through smartphones. In Pervasive Computing and Communications Workshops (PERCOM Workshops), 2012 IEEE International Conference on. IEEE, 253--258.Google ScholarCross Ref
- Yu-Chung Cheng, Yatin Chawathe, Anthony LaMarca, and John Krumm. 2005. Accuracy Characterization for Metropolitan-scale Wi-Fi Localization. In Proceedings of the 3rd International Conference on Mobile Systems, Applications, and Services (MobiSys ‘05). ACM, New York, NY, USA, 233--245. Google ScholarDigital Library
- Eunjoon Cho, Seth A Myers, and Jure Leskovec. 2011. Friendship and mobility: user movement in location-based social networks. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1082--1090. Google ScholarDigital Library
- Siraj Datoo. 2013. High street shops are studying shopper behaviour by tracking their smartphones or movement. http://goo.gl/vGg8k8. (2013). Accessed: 2017-01-13.Google Scholar
- Romain Dillet. 2014. Happn Is A Dating App Powered By Real Life Interactions. http://goo.gl/0nHyIr. (2014). Accessed: 2017-01-13.Google Scholar
- Nathan Eagle and Alex Pentland. 2006. Reality mining: sensing complex social systems. Personal and ubiquitous computing 10, 4 (2006), 255--268. Google ScholarDigital Library
- Nathan Eagle, Alex Sandy Pentland, and David Lazer. 2009. Inferring friendship network structure by using mobile phone data. Proceedings of the National Academy of Sciences 106, 36 (2009), 15274--15278.Google ScholarCross Ref
- Alan Eustace. 2010. WiFi data collection: An update. http://goo.gl/VFJ9mM. (2010).Google Scholar
- R. Friedman, A. Kogan, and Y. Krivolapov. 2013. On Power and Throughput Tradeoffs of WiFi and Bluetooth in Smartphones. Mobile Computing, IEEE Transactions on 12, 7 (July 2013), 1363--1376. Google ScholarDigital Library
- R. C. Gatej. 2013. An adaptive approach to mobile sampling. Master's thesis. Technical University of Denmark.Google Scholar
- Marta C Gonzalez, Cesar A Hidalgo, and Albert-Laszlo Barabasi. 2008. Understanding individual human mobility patterns. Nature 453, 7196 (2008), 779--782.Google Scholar
- Google. 2017. Enabling discoverability. goo.gl/ExuuVW. (2017). Accessed: 2017-01-13.Google Scholar
- Przemyslaw A Grabowicz, José J Ramasco, Bruno Gonçalves, and Victor M Eguíluz. 2014. Entangling mobility and interactions in social media. PLoS One 9, 3 (2014), e92196.Google ScholarCross Ref
- Andreas Haeberlen, Eliot Flannery, Andrew M. Ladd, Algis Rudys, Dan S. Wallach, and Lydia E. Kavraki. 2004. Practical Robust Localization over Large-scale 802.11 Wireless Networks. In Proceedings of the 10th Annual International Conference on Mobile Computing and Networking (MobiCom ‘04). ACM, New York, NY, USA, 70--84. Google ScholarDigital Library
- Edward Twitchell Hall. 1966. The hidden dimension. (1966).Google Scholar
- Dongsu Han, David G Andersen, Michael Kaminsky, Konstantina Papagiannaki, and Srinivasan Seshan. 2009. Access point localization using local signal strength gradient. In Passive and Active Network Measurement. Springer, 99--108. Google ScholarDigital Library
- Ross Haseman, J Wasson, and D Bullock. 2010. Real time measurement of work zone travel time delay and evaluation metrics using bluetooth probe tracking. Journal of the Transportation Research Board (2010).Google Scholar
- Pan Hui, Augustin Chaintreau, James Scott, Richard Gass, Jon Crowcroft, and Christophe Diot. 2005. Pocket switched networks and human mobility in conference environments. In Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking. ACM, 244--251. Google ScholarDigital Library
- Lorenzo Isella, Juliette Stehlé, Alain Barrat, Ciro Cattuto, Jean-François Pinton, and Wouter Van den Broeck. 2011. What's in a crowd? Analysis of face-to-face behavioral networks. Journal of theoretical biology 271, 1 (2011), 166--180.Google ScholarCross Ref
- Jong Hee Kang, William Welbourne, Benjamin Stewart, and Gaetano Borriello. 2004. Extracting places from traces of locations. In Proceedings of the 2nd ACM international workshop on Wireless mobile applications and services on WLAN hotspots. ACM, 110--118. Google ScholarDigital Library
- Mikkel Baun Kjærgaard and Petteri Nurmi. 2012. Challenges for social sensing using wifi signals. In Proceedings of the 1st ACM workshop on Mobile systems for computational social science. ACM, 17--21. Google ScholarDigital Library
- Vassilis Kostakos, Eamonn O'Neill, Alan Penn, George Roussos, and Dikaios Papadongonas. 2010. Brief encounters: Sensing, modeling and visualizing urban mobility and copresence networks. ACM Transactions on Computer-Human Interaction (TOCHI) 17, 1 (2010), 2. Google ScholarDigital Library
- John Krumm and Ken Hinckley. 2004. The nearme wireless proximity server. In UbiComp 2004: Ubiquitous Computing. Springer, 283--300.Google Scholar
- Jakob Eg Larsen, Piotr Sapiezynski, Arkadiusz Stopczynski, Morten Mørup, and Rasmus Theodorsen. 2013. Crowds, Bluetooth, and Rock'N'Roll: Understanding Music Festival Participant Behavior. In Proceedings of the 1st ACM International Workshop on Personal Data Meets Distributed Multimedia (PDM ‘13). ACM, New York, NY, USA, 11--18. Google ScholarDigital Library
- David Lazer, Alex Sandy Pentland, Lada Adamic, Sinan Aral, Albert Laszlo Barabasi, Devon Brewer, Nicholas Christakis, Noshir Contractor, James Fowler, Myron Gutmann, and others. 2009. Life in the network: the coming age of computational social science. Science (New York, NY) 323, 5915 (2009), 721.Google Scholar
- Jinyang Li, John Jannotti, Douglas S. J. De Couto, David R. Karger, and Robert Morris. 2000. A Scalable Location Service for Geographic Ad Hoc Routing. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking (MobiCom ‘00). ACM, New York, NY, USA, 120--130. Google ScholarDigital Library
- Kaisen Lin, Aman Kansal, Dimitrios Lymberopoulos, and Feng Zhao. 2010. Energy-accuracy Trade-off for Continuous Mobile Device Location. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (MobiSys ‘10). ACM, New York, NY, USA, 285--298. Google ScholarDigital Library
- Gilles Louppe. 2013. How are feature importances determined in Random Forest Classifier? http://stackoverflow.com/a/15821880. (2013). Accessed: 2015-10-17.Google Scholar
- Xin Lu, Linus Bengtsson, and Petter Holme. 2012. Predictability of population displacement after the 2010 Haiti earthquake. Proceedings of the National Academy of Sciences (2012).Google ScholarCross Ref
- Marvin McNett and Geoffrey M. Voelker. 2005. Access and Mobility of Wireless PDA Users. SIGMOBILE Mob. Comput. Commun. Rev. 9, 2 (April 2005), 40--55. Google ScholarDigital Library
- Jean-Luc Meunier. 2004. Peer-to-peer determination of proximity using wireless network data. (2004).Google Scholar
- Bruce Meyerson. 2007. AOL introduces location plug-in for instant messaging so users can see where buddies are. http://goo.gl/2W1uYh. (2007).Google Scholar
- Daniel Olguín Olguín, Benjamin N Waber, Taemie Kim, Akshay Mohan, Koji Ara, and Alex Pentland. 2009. Sensible organizations: Technology and methodology for automatically measuring organizational behavior. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 39, 1 (2009), 43--55. Google ScholarDigital Library
- Venet Osmani, Iacopo Carreras, Aleksandar Matic, and Piret Saar. 2014. An analysis of distance estimation to detect proximity in social interactions. Journal of Ambient Intelligence and Humanized Computing 5, 3 (2014), 297--306.Google ScholarCross Ref
- Eamonn OâĂŹNeill, Vassilis Kostakos, Tim Kindberg, Alan Penn, Danaë Stanton Fraser, Tim Jones, and others. 2006. Instrumenting the city: Developing methods for observing and understanding the digital cityscape. In UbiComp 2006: Ubiquitous Computing. Springer, 315--332. Google ScholarDigital Library
- F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. 2011. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research 12 (2011), 2825--2830. Google ScholarDigital Library
- Nissanka B Priyantha, Anit Chakraborty, and Hari Balakrishnan. 2000. The cricket location-support system. In Proceedings of the 6th annual international conference on Mobile computing and networking. ACM, 32--43. Google ScholarDigital Library
- Marcel Salathé, Maria Kazandjieva, Jung Woo Lee, Philip Levis, Marcus W Feldman, and James H Jones. 2010. A high-resolution human contact network for infectious disease transmission. Proceedings of the National Academy of Sciences 107, 51 (2010), 22020--22025.Google ScholarCross Ref
- Piotr Sapiezynski, Radu Gatej, Alan Mislove, and Sune Lehmann. 2015a. Oportunities and Challenges in Crowdsourced Wardriving. In Proceedings of the 15th ACM SIGCOMM conference on Internet measurement. ACM. Google ScholarDigital Library
- Piotr Sapiezynski, Arkadiusz Stopczynski, Radu Gatej, and Sune Lehmann. 2015b. Tracking Human Mobility Using WiFi Signals. PLoS ONE 10, 7 (07 2015), e0130824.Google Scholar
- Karen Scarfone and John Padgette. 2008. Guide to bluetooth security. NIST Special Publication 800 (2008), 121. Google ScholarDigital Library
- Vedran Sekara and Sune Lehmann. 2014. The strength of friendship ties in proximity sensor data. PloS one 9, 7 (2014), e100915.Google ScholarCross Ref
- Vedran Sekara, Arkadiusz Stopczynski, and Sune Lehmann. 2016. Fundamental structures of dynamic social networks. Proceedings of the National Academy of Sciences 113, 36 (2016), 9977--9982.Google ScholarCross Ref
- Chaoming Song, Zehui Qu, Nicholas Blumm, and Albert-László Barabási. 2010. Limits of predictability in human mobility. Science 327, 5968 (2010), 1018--1021.Google Scholar
- Hendrik Stange, Thomas Liebig, Dirk Hecker, Gennady Andrienko, and Natalia Andrienko. 2011. Analytical workflow of monitoring human mobility in big event settings using bluetooth. In Proceedings of the 3rd ACM SIGSPATIAL international workshop on indoor spatial awareness. ACM, 51--58. Google ScholarDigital Library
- Juliette Stehlé, Nicolas Voirin, Alain Barrat, Ciro Cattuto, Lorenzo Isella, Jean-François Pinton, Marco Quaggiotto, Wouter Van den Broeck, Corinne Regis, Bruno Lina, and others. 2011. High-resolution measurements of face-to-face contact patterns in a primary school. PloS one 6, 8 (2011), e23176.Google ScholarCross Ref
- Arkadiusz Stopczynski, Alex Sandy Pentland, and Sune Lehmann. 2015. Physical Proximity and Spreading in Dynamic Social Networks. arXiv preprint arXiv:1509.06530 (2015).Google Scholar
- Arkadiusz Stopczynski, Riccardo Pietri, Alex Pentland, David Lazer, and Sune Lehmann. 2014. Privacy in Sensor-Driven Human Data Collection: A Guide for Practitioners. CoRR abs/1403.5299 (2014). http://arxiv.org/abs/1403.5299Google Scholar
- Arkadiusz Stopczynski, Piotr Sapiezynski, Sune Lehmann, and others. 2015. Temporal fidelity in dynamic social networks. The European Physical Journal B 88, 10 (2015), 1--6.Google ScholarCross Ref
- Arkadiusz Stopczynski, Vedran Sekara, Piotr Sapiezynski, Andrea Cuttone, Mette My Madsen, Jakob Eg Larsen, and Sune Lehmann. 2014. Measuring Large-Scale Social Networks with High Resolution. PLoS ONE 9, 4 (04 2014), e95978.Google Scholar
- Aaron Striegel, Shu Liu, Lei Meng, Christian Poellabauer, David Hachen, and Omar Lizardo. 2013. Lessons Learned from the Netsense Smartphone Study. In Proceedings of the 5th ACM Workshop on HotPlanet (HotPlanet ‘13). ACM, New York, NY, USA, 51--56. Google ScholarDigital Library
- Jameson L Toole, Carlos Herrera-Yaqüe, Christian M Schneider, and Marta C Gonzalez. 2015. Coupling human mobility and social ties. Journal of The Royal Society Interface 12, 105 (2015), 20141128.Google ScholarCross Ref
- Olga Troyanskaya, Michael Cantor, Gavin Sherlock, Pat Brown, Trevor Hastie, Robert Tibshirani, David Botstein, and Russ B Altman. 2001. Missing value estimation methods for DNA microarrays. Bioinformatics 17, 6 (2001), 520--525.Google ScholarCross Ref
- Hao Wang, Daqing Zhang, Junyi Ma, Yasha Wang, Yuxiang Wang, Dan Wu, Tao Gu, and Bing Xie. 2016b. Human Respiration Detection with Commodity Wifi Devices: Do User Location and Body Orientation Matter?. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ‘16). ACM, New York, NY, USA, 25--36. Google ScholarDigital Library
- Wei Wang, Alex X. Liu, and Muhammad Shahzad. 2016a. Gait Recognition Using Wifi Signals. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ‘16). ACM, New York, NY, USA, 363--373. Google ScholarDigital Library
- Jens Weppner and Paul Lukowicz. 2013. Bluetooth based collaborative crowd density estimation with mobile phones. In Pervasive computing and communications (PerCom), 2013 IEEE international conference on. IEEE, 193--200.Google Scholar
- David Kofoed Wind, Piotr Sapiezynski, Magdalena Anna Furman, and Sune Lehmann. 2016. Inferring Stop-Locations from WiFi. PloS one 11, 2 (2016), e0149105.Google ScholarCross Ref
- Ford-Long Wong and Frank Stajano. 2005. Location Privacy in Bluetooth. In Security and Privacy in Ad-hoc and Sensor Networks, Refik Molva, Gene Tsudik, and Dirk Westhoff (Eds.). Lecture Notes in Computer Science, Vol. 3813. Springer Berlin Heidelberg, 176--188. Google ScholarDigital Library
- Zheng Yang, Zimu Zhou, and Yunhao Liu. 2013. From RSSI to CSI: Indoor Localization via Channel Response. ACM Comput. Surv. 46, 2, Article 25 (Dec. 2013), 32 pages. Google ScholarDigital Library
Index Terms
- Inferring Person-to-person Proximity Using WiFi Signals
Recommendations
Citywide mobile internet access using dense urban WiFi coverage
UrbaNe '12: Proceedings of the first workshop on Urban networkingWe investigate if it is feasible to use the WiFi coverage in urban areas for mobile Internet access and which type of applications can benefit from the Internet access provided by the already deployed WiFi Access Points (APs). Nowadays, most smartphones ...
Energy-efficient network selection with mobility pattern awareness in an integrated WiMAX and WiFi network
To provide wireless Internet access, WiFi networks have been deployed in many regions such as buildings and campuses. However, WiFi networks are still insufficient to support ubiquitous wireless service due to their narrow coverage. One possibility to ...
A Seamless Handover Based MIH-Assisted PMIPV6 in Heterogeneous Network(LTE-WIFI)
BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and ApplicationsWe consider the user equipment (UE) velocity as a vital trend in association problem in heterogeneous networks (HetNets), since there is a considerable relation between the velocity and the handover failure (HOF) as well as the probability of ...
Comments