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Sensors  2013 

The Role of Advanced Sensing in Smart Cities

DOI: 10.3390/s130100393

Keywords: advanced sensing, sensor networks, smart cities, internet of things

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Abstract:

In a world where resources are scarce and urban areas consume the vast majority of these resources, it is vital to make cities greener and more sustainable. Advanced systems to improve and automate processes within a city will play a leading role in smart cities. From smart design of buildings, which capture rain water for later use, to intelligent control systems, which can monitor infrastructures autonomously, the possible improvements enabled by sensing technologies are immense. Ubiquitous sensing poses numerous challenges, which are of a technological or social nature. This paper presents an overview of the state of the art with regards to sensing in smart cities. Topics include sensing applications in smart cities, sensing platforms and technical challenges associated with these technologies. In an effort to provide a holistic view of how sensing technologies play a role in smart cities, a range of applications and technical challenges associated with these applications are discussed. As some of these applications and technologies belong to different disciplines, the material presented in this paper attempts to bridge these to provide a broad overview, which can be of help to researchers and developers in understanding how advanced sensing can play a role in smart cities.

References

[1]  Giffinger, R.; Fertner, C.; Kramar, H.; Kalasek, R. Smart Cities: Ranking of European Medium-Sized Cities; Centre of Regional Science: Vienna, Austria, 2007.
[2]  In Focus: Smart Cities. Available online: http://www.stateofgreen.com/en/InFocus/Smart-Cities/ (accessed on 18 November 2012).
[3]  Intelligent Sensors for the Smart City. Available online: http://www.theengineer.co.uk/in-depth/analysis/intelligent-sensors-for-smart-cities/1012232.article#ixzz2CahFzYwV/ (accessed on 18 November 2012).
[4]  Ueno, K.; Asai, T.; Amemiya, Y. Low-power temperature-to-frequency converter consisting of sub-threshold CMOS circuits for integrated smart temperature sensors. Sens. Actuators A 2011, 165, 132–137.
[5]  Ueno, K.; Hirose, T.; Asai, T.; Amemiya, Y. CMOS Smart Sensor for Monitoring the Quality of Perishables. IEEE J. Solid State Circuits 2007, 2, 798–803.
[6]  Wang, X.; Larsson, O.; Platt, D.; Nordlinder, S.; Engquist, I.; Berggren, M.; Crispin, X. An all-printed wireless humidity sensor label. Sens. Actuators B Chem. 2012, 167, 556–561.
[7]  Girbau, D.; Ramos, A.; Lázaro, A.; Rima, S.; Villarino, R. Passive Wireless Temperature Sensor Based on Time-Coded UWB Chipless RFID Tags. IEEE Trans. Microw. Theory Tech. 2012, 60, 3623–3632.
[8]  Yang, L.; Zhang, R.; Staiculescu, D.; Wong, C.P.; Tentzeris, M. A Novel Conformal RFID-Enabled Module Utilizing Inkjet-Printed Antennas and Carbon Nanotubes for Gas-Detection Applications. IEEE Antennas Wirel. Propag. Lett. 2009, 8, 653–656.
[9]  Oprea, A.; Courbat, J.; Barsan, N.; Briand, D.; Weimar, U.; de Rooij, N. Temperature, humidity and gas sensors integrated on plastic foil for low power applications. Sens. Actuators B Chem. 2009, 140, 227–232.
[10]  Oprea, A.; Courbat, J.; Barsan, N.; Briand, D.; Weimar, U.; de Rooij, N. Multi sensor platform on plastic foil for environmental monitoring. Procedia Chem. 2009, 1, 597–600.
[11]  Hamaguchi, K.; Ma, Y.; Takada, M.; Nishijima, T.; Shimura, T. Telecommunications Systems in Smart Cities. Hitachi Rev. 2012, 61, 152–158.
[12]  Norair, J. Introduction to Dash7 Technologies. Available online: https://dash7.memberclicks.net./PDF/dash7%20wp%20ed1.pdf (accessed on 19 November 2012).
[13]  Sensodine. Available online: http://www.sensinode.com/EN/technology.html/ (accessed on 15 November 2012).
[14]  Ni, L.; Zhang, D.; Souryal, M. RFID-based localization and tracking technologies. IEEE Wirel. Commun. 2011, 18, 45–51.
[15]  Yao, W.; Chu, C.; Li, Z. The Adoption and Implementation of RFID Technologies in Healthcare: A Literature Review. J. Med. Syst. 2012, 36, 3507–3525.
[16]  Vo, C.; Chilamkurti, N.; Loke, S.; Torabi, T. RADIO-MAMA: An RFID based business process framework for asset management. J. Netw. Comput. Appl. 2011, 34, 990–997.
[17]  Chang, Y.; Chang, C.; Hung, Y.; Tsai, C. NCASH: NFC Phone-Enabled Personalized Context Awareness Smart-Home Environment. Cybern. Syst. Int. J. 2010, 41, 123–145.
[18]  Balan, R.; Ramasubbu, N.; Prakobphol, K.; Christin, N.; Hong, J. mFerio: The design and evaluation of a peer-to-peer mobile payment system. Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services (MobiSys ′09), Krakow, Poland, 22–25 June 2009; pp. 291–304.
[19]  Sánchez, I.; Riekki, J.; Rousu, J.; Pirttikangas, S. Touch & Share: RFID based ubiquitous file containers. Proceedings of the 7th International Conference on Mobile and Ubiquitous Multimedia (MUM ′08), Umea, Sweden, 3–5 December 2008; pp. 57–63.
[20]  Chinese City to Get NFC Smart Meters. Available online: http://www.nfcworld.com/2012/06/20/316338/chinese-city-get-nfc-smart-meters/ (accessed on 19 November 2012).
[21]  Opperman, C.; Hancke, G.P. Using NFC-enabled Phones for Remote Data Acquisition and Digital Control. Proceedings of IEEE AFRICON 2011, Livingstone, Zambia, 13–15 September 2011; pp. 1–6.
[22]  Opperman, C.; Hancke, G.P. Smartphones as a Platform for Advanced Measurement and Processing. Proceedings of 2012 IEEE Instrumentation and Measurement Technology Conference (I2MTC), Graz, Austria, 13–16 May 2012; pp. 703–706.
[23]  Jaraba, F.; Ruiz, I.; Nieto, M. A NFC-based pervasive solution for city touristic surfing. Pers. Ubiquitous Comput. 2011, 15, 731–742.
[24]  Benelli, G. An automated payment system for car parks based on Near Field Communication technology. Proceedings of International Conference for Internet Technology and Secured Transactions (ICITST), London, UK, 8–11 November 2010; pp. 1–6.
[25]  Galloway, B.; Hancke, G.P. Introduction to Industrial Control Networks. IEEE Commun. Surv. Tutorials 2012. accepted for Publication.
[26]  Warneke, B.; Scott, M.; Leibowitz, B.; Zhou, L.; Bellew, C.; Chediak, J.; Kahn, J.; Boser, B.; Pister, K. An autonomous 16 mm3 solar-powered node for distributed wireless sensor networks. Proceedings of 1st International Conference on IEEE Sensors, Orlando, FL, USA, 12–14 June 2002; pp. 1510–1515.
[27]  Sihori, J.; Mahadik, R. Piezoeletric wind energy harvester for low-power sensors. J. Intell. Mater. Syst. Struct. 2011, 22, 2215–2228.
[28]  Ramasur, D.; Hancke, G.P. A wind energy harvester for low power wireless sensor networks. Proceedings of 2012 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Graz, Austria, 13–16 May 2012; pp. 2623–2627.
[29]  Ajmal, T.; Jazani, D.; Allen, D. Design of a compact RF energy harvester for wireless sensor networks. Proceedings of IET Conference on Wireless Sensor Systems (WSS), London, UK, 18–19 June 2012; pp. 1–5.
[30]  Chang, K.; Kang, S.; Park, K.; Shin, S.; Kim, H.S.; Kim, H. Electric Field Harvesting Powered Wireless Sensors for Smart Grid. J. Elect. Eng. Technol. 2012, 7, 75–80.
[31]  Van Schalkwyk, J.; Hancke, G.P. Energy Harvesting for Wireless Sensors from Electromagnetic Fields around Overhead Power Lines. Proceedings of IEEE International Symposium on Industrial Electronics (ISIE), Hangzhou, China, 28–31 May 2012; pp. 1128–1135.
[32]  Wischke, M.; Masur, M.; Kroner, M.; Woias, P. Vibration harvesting in traffic tunnels to power wireless sensor nodes. Smart Mater. Struct. 2011, 20, 1–8.
[33]  Brunelli, D.; Moser, C.; Thiele, L.; Benini, L. Design of a solar-harvesting circuit for battery-less embedded systems. IEEE Trans. Circuits Syst. 2009, 56, 2519–2528.
[34]  Tan, Y.; Panda, S. A Novel Piezoelectric based Wind energy Harvester for Low-power Autonomous Wind Speed Sensor. Proceedings of IEEE Industrial Electronics Conference (IECON) 2007, Taipei, Taiwan, 5–8 November 2007; pp. 2157–2180.
[35]  Thingspeak. Available online: https://www.thingspeak.com/ (accessed on 15 November 2012).
[36]  iObridge. Available online: http://www.iobridge.com/ (accessed on 15 November 2012).
[37]  HPCense. Available online: http://postscapes.com/hp-cense-platform/ (accessed on 15 November 2012).
[38]  IBM Smarter Planet. Available online: http://www.ibm.com/smarterplanet/us/en/?ca=v_smarterplanet/ (accessed on 15 November 2012).
[39]  Mitton, N.; Papavassiliou, S.; Puliafito, A.; Trivedi, K. Combining Cloud and sensors in a smart city environment. EURASIP J. Wirel. Commun. Netw. 2012, 247, 1–20.
[40]  Costantino, L.; Buonaccorsi, N.; Cicconetti, C.; Mambrini, R. Performance analysis of an LTE gateway for the IoT. Proceedings of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), San Francisco, CA, USA, 25–28 June 2012; pp. 1–6.
[41]  Br?ring, A.; Echterhoff, J.; Jirka, S.; Simonis, I.; Everding, T. New generation Sensor Web Enablement. Sensors 2011, 11, 2652–2699.
[42]  Tamayo, A.; Granell, C.; Huerta, J. Using SWE Standards for Ubiquitous Environmental Sensing: A Performance Analysis. Sensors 2012, 12, 12026–12051.
[43]  Fazio, M.; Paone, M.; Puliafito, A.; Villari, M. Huge Amount of Heterogeneous Sensed Data Needs the Cloud. Proceedings of International IEEE Multi-Conference on Systems, Signals and Devices (SSD), Chemnitz, Germany, 20–23 March 2012; pp. 1–5.
[44]  Metje, N.; Chapman, D.; Cheneler, D.; Ward, M.; Thomas, A. Smart Pipes—Instrumented Water Pipes, Can this be made a reality? Sensors 2011, 11, 7455–7475.
[45]  Min, L.; Yan, W.; Wassell, I. Wireless sensor network: Water distribution monitoring system. Proceedings of IEEE Radio and Wireless Symposium, Orlando, FL, USA, 22–24 January 2008; pp. 775–778.
[46]  Stoianov, I.; Nachman, L.; Madden, S.; Tokmouline, T. PIPENET: A wireless sensor network for pipeline monitoring. Proceedings of the 6th International Conference on Information Processing in Sensor Networks (IPSN ′07), Cambridge, MA, USA, 25–27 April 2007; pp. 264–273.
[47]  Metje, N.; Chapman, D.; Walton, R.; Sadeghioon, A.; Ward, M. Real time condition of buried water pipes. Tunneling Undergr. Space Technol. 2012, 28, 315–320.
[48]  Gungor, V.; Lu, B.; Hancke, G.P. Opportunities and Challenges of Wireless Sensor Networks in Smart Grid. IEEE Trans. Ind. Electr. 2010, 57, 3557–3564.
[49]  Klein, K.; Springer, P.; Black, W. Real-Time Ampacity and Ground Clearance Software for Integration into Smart Grid Technology. IEEE Trans. Power Deliv. 2010, 25, 1768–1777.
[50]  Parker, D.; McCollough, N. Medium-voltage sensors for the smart grid: Lessons learned. Proceedings of IEEE Power and Energy Society General Meeting, Detroit, MI, USA, 24–28 July 2011; pp. 1–7.
[51]  Moghe, R.; Lambert, F.; Divan, D. A novel low-cost smart current sensor for utility conductors. IEEE Trans. Smart Grid 2012, 3, 653–663.
[52]  Froehlich, J.; Larson, E.; Gupta, S.; Cohn, G.; Reynolds, M.; Patel, S. Disaggregated End-Use Energy Sensing for the Smart Grid. IEEE Pervasive Comput. 2011, 10, 28–39.
[53]  Hernández, L.; Baladrón, C.; Aguiar, J.M.; Calavia, L.; Carro, B.; Sánchez-Esguevillas, A.; Cook, D.; Chinarro, D.; Gómez, J. A Study of the Relationship between Weather Variables and Electric Power Demand inside a Smart Grid/Smart World Framework. Sensors 2012, 12, 11571–11591.
[54]  Zhenyu, H.; Gao, R.; Zhaoyan, F. Occupancy and indoor environment quality sensing for smart buildings. Proceedings of 2012 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Graz, Austria, 13–16 May 2012; pp. 882–887.
[55]  Nguyen, D.; Huynh, L.; Dinh, T.; Dinh, T. Video Monitoring System: Counting People by Tracking. Proceedings of IEEE International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future, Ho Chi Minh, Vietnam, 27 February–1 March 2012; pp. 1–4.
[56]  Weng, T.; Agarwal, Y. From Buildings to Smart Buildings—Sensing and Actuation to Improve Energy Efficiency. IEEE Des. Test Comput. 2012, 29, 36–44.
[57]  Benezeth, Y.; Laurent, H.; Emile, B.; Rosenberger, C. Towards a sensor for detecting human presence and characterizing activity. Energy Buildings 2011, 43, 305–314.
[58]  Gao, G.; Whitehouse, K. The self-programming thermostat: optimizing setback schedules based on home occupancy patterns. Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings (BuildSys ′09), Berkeley, CA, USA, 4–6 November 2009; pp. 74–72.
[59]  Whitehouse, K.; Ranjan, J.; Lu, J.; Sookoor, T.; Saadat, M.; Burke, C.; Staengle, G.; Canfora, A.; Haj-Hariri, H. Towards Occupancy-Driven Heating and Cooling. IEEE Des. Test Comput. 2012, 29, 17–25.
[60]  Yun, J.; Won, K.-H. Building Environment Analysis Based on Temperature and Humidity for Smart Energy Systems. Sensors 2012, 12, 13458–13470.
[61]  Lloret, J.; Macías, E.; Suárez, A.; Lacuesta, R. Ubiquitous Monitoring of Electrical Household Appliances. Sensors 2012, 12, 15159–15191.
[62]  Kruger, C.; Hancke, G.P.; Bhatt, D. Wireless sensor network for building evacuation. Proceedings of 2012 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Graz, Austria, 13–16 May 2012; pp. 2572–2577.
[63]  Willingen, W.; Neef, R.; Lieburg, A.; Schut, M.C. WILLEM: A Wireless Intelligent Evacuation Method. Proceedings of 3rd International Conference on Sensor Technologies and Applications (SENSORCOMM ′09), Athens, Greece, 18–23 June 2009; pp. 382–387.
[64]  Higuera, J.; Cobo, L.; Incera, A.; Cobo, A. Fiber Optic Sensors in Structural Health Monitoring. J. Lightwave Technol. 2011, 29, 587–608.
[65]  Bao, X.; Chen, L. Recent Progress in Distributed Fiber Optic Sensors. Sensors 2012, 12, 8601–8639.
[66]  Afzal, M.; Kabir, S.; Sidek, O. An in-depth review: Structural health monitoring using fiber optic sensor. IETE Tech. Rev. 2012, 29, 105–113.
[67]  Kim, S.; Pakzad, S.; Culler, D.; Demmel, J.; Fenves, G.; Glaser, S.; Turon, M. Health monitoring of civil infrastructures using wireless sensor networks. Proceedings of the 6th International Conference on Information Processing in Sensor Networks (IPSN ′07), Cambridge, MA, USA, 25–27 April 2007; pp. 254–263.
[68]  Myung, H.; Lee, S.; Lee, B. Structural health monitoring robot using paired structured light. Proceedings of IEEE International Symposium on Industrial Electronics (ISIE), Seoul, Korea, 5–8 July 2009; pp. 396–401.
[69]  Mohammad, R.; Jahanshahi, S.; Masri, F. Adaptive vision-based crack detection using 3D scene reconstruction for condition assessment of structures. Autom. Constr. 2012, 22, 567–576.
[70]  Yoon, S.; Ghazanfari, E.; Cheng, L.; Pamukcu, S.; Suleiman, M.T. Subsurface Event Detection and Classification Using Wireless Signal Networks. Sensors 2012, 12, 14862–14886.
[71]  Sagl, G.; Blaschke, T.; Beinat, E.; Resch, B. Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics. Sensors 2012, 12, 9800–9822.
[72]  Park, C.; Lee, J. Intelligent Traffic Control Based on IEEE 802.11 DCF/PCF Mechanisms at Intersections. Proceedings of IEEE Conference on Vehicular Technology(VTC 2010), San Francisco, CA, USA, 5–8 September 2011; pp. 1–4.
[73]  Kowshik, H.; Caveney, D.; Kumar, P.R. Provable System-wide Safety in Intelligent Intersections. IEEE Trans. Vehicular Technol. 2011, 60, 804–818.
[74]  Pérez, J.; Seco, F.; Milanés, V.; Jiménez, A.; Díaz, J.; Pedro, T. An RFID-Based Intelligent Vehicle Speed Controller Using Active Traffic Signals. Sensors 2010, 10, 5872–5887.
[75]  Yannis, G.; Antoniou, C. Integration of weigh-in-motion technologies in road infrastructure management. ITE J. 2005, 75, 39–43.
[76]  Semertzidis, T.; Dimitropoulos, K.; Koutsia, A.; Grammalidis, N. Video sensor network for real-time traffic monitoring and surveillance. IET Intell. Transp. Syst. 2010, 4, 103–112.
[77]  Chen, Y.; Wu, B.; Fan, C. Real-time vision-based multiple vehicle detection and tracking for nighttime traffic surveillance. Proceedings of IEEE International Conference on Systems, Man and Cybernetics (SMC), San Antonio, TX, USA, 11–14 October 2009; pp. 3352–3358.
[78]  Wang, J.; Chen, D.; Chen, H.; Yang, J. On pedestrian detection and tracking in infrared videos. Pattern Recognit. Lett. 2012, 33, 775–785.
[79]  Damen, D.; Hogg, D. Detecting Carried Objects from Sequence of Walking Pedestrians. IEEE Trans. Pattern Anal. Mach. Intell. 2012, 34, 1056–1067.
[80]  Wang, B.; Ye, M.; Li, X.; Zhao, F.; Ding, J. Abnormal crowd behavior detection using high-frequency and spatial-temporal features. Mach. Vis. Appl. 2012, 3, 501–511.
[81]  Calavia, L.; Baladrón, C.; Aguiar, J.; Carro, B.; Esguevillas, A. A Semantic Autonomous Video Surveillance System for Dense Camera Networks in Smart Cities. Sensors 2012, 12, 10407–10429.
[82]  IBM—Intelligent Law Enforcement. Available online: http://www-01.ibm.com/software/industry/intelligent-law-enforcement/ (accessed on 19 November 2012).
[83]  Clemente, A.D.; Dios, J.; Baturone, A. A WSN-Based Tool for Urban and Industrial Fire-Fighting. Sensors 2012, 12, 15009–15035.
[84]  Brown, L.; Grundlehner, B.; van de Molengraft, J.; Penders, J.; Gyselinckx, B. Body area network for monitoring autonomic nervous system responses. Proceedings of 3rd International Conference on Pervasive Computing Technologies for Healthcare, London, UK, 1–3 April 2009; pp. 1–3.
[85]  Sousa, M.; Lopes, W.; Madeiro, F.; Alencar, M. Cognitive LF-Ant: A Novel Protocol for Healthcare Wireless Sensor Networks. Sensors 2012, 12, 10463–10486.
[86]  Han, Y.; Han, M.; Lee, S.; Sarkar, A.M.J.; Lee, Y.-K. A Framework for Supervising Lifestyle Diseases Using Long-Term Activity Monitoring. Sensors 2012, 12, 5363–5379.
[87]  Peternel, K.; Poga?nik, M.; Tav?ar, R.; Kos, A. A Presence-Based Context-Aware Chronic Stress Recognition System. Sensors 2012, 12, 15888–15906.
[88]  Kulkarni, K.; Can, M.; Hartmann, B. Collaboratively Crowd-sourcing workflows with turkomatic. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW ′12), Seattle, WA, USA, 11–15 February 2012; pp. 1003–1012.
[89]  Rzeszotarski, J.; Kittur, A. CrowdScape: Interactively visualizing user behavior and output. Proceedings of the 25th Annual ACM symposium on User interface software and technology (UIST'12), Cambridge, MA, USA, 7–10 October 2012; pp. 55–62.
[90]  Mun, M.; Reddy, S.; Shilton, K.; Yau, N.; Burke, J.; Estrin, D.; Hansen, M.; Howard, E.; West, R.; Boda, P. PEIR, the personal environmental impact report, as a platform for participatory sensing systems research. Proceedings of the 7th International Conference on Mobile systems, applications, and services (MobiSys ′09), Krakow, Poland, 22–25 June 2009; pp. 55–68.
[91]  Kanjo, E.; Bacon, J.; Roberts, D.; Landshoff, P. MobSens: Making Smart Phones Smarter. IEEE Pervasive Comput. 2009, 8, 50–57.
[92]  Roitman, H.; Mamou, J.; Mehta, S.; Satt, A.; Subramaniam, L. Harnessing the Crowds for smart city sensing. Proceedings of 1st International Workshop on Multimodal Crowd Sensing (CrowdSens'12), Maui, HI, USA, 29 October–2 November 2012; pp. 17–18.
[93]  Shilton, K. Four Billion Little Brothers? Privacy, mobile phones and ubiquitous data collection. ACM Queue 2009, 7, 1–8.
[94]  Strickland, E. Cisco bets on South Korean smart city: Songdo aims to be the most wired city on Earth. IEEE Spectr. 2011, 48, 11–12.
[95]  Songdo. Available online: http://www.songdo.com/ (accessed on 15 November 2012).
[96]  PlanIT Valley. Available online: http://planitvalley.org/ (accessed on 15 November 2012).
[97]  Fujisawa SST. Available online: http://panasonic.net/es/fujisawasst/ (accessed on 15 November 2012).
[98]  Amsterdam Smart City. Available online: http://amsterdamsmartcity.com/ (accessed 15 November 2012).
[99]  Smart Cities Pilot—Public Transport Planner—Groningen. Available online: http://www.smartcities.info/smart-cities-pilot-public-transport-planner-groningen/ (accessed on 14 December 2012).
[100]  Smart Cities Pilot—Norfolk Customer Insight—Norfolk County Council. Available online: http://www.smartcities.info/smart-cities-pilot-norfolk-customer-insight-norfolk-county-council/ (accessed on 14 December 2012).
[101]  Santander Summary. Available online: http://smartsantander.eu/wiki/index.php/Testbeds/Santander/ (accessed on 14 December 2012).
[102]  Sanroma, M. Barcelona Smart City. Available online: http://www.majorcities.eu/workshops/2012-helsinki/helsinki2012_barcelona.pdf (accessed on 14 December 2012).
[103]  Malaga Living Lab. Available online: http://www.openlivinglabs.eu/livinglab/m%C3%A1laga-living-lab/ (accessed on 14 December 2012).
[104]  Smart City Wien. Available online: http://eu-smartcities.eu/blog/project-smart-city-wien/ (accessed on 14 December 2012).
[105]  Hancke, G.P. Practical eavesdropping and skimming attacks on high-frequency RFID tokens. J. Comput. Secur. 2011, 19, 259–288.
[106]  Hancke, G.P.; Markantonakis, K.; Mayes, K. Security Challenges for User-Oriented RFID Applications within the ‘Internet of Things’. J. Internet Technol. 2010, 11, 307–313.

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