Advertisement

Mobile Networks and Applications

, Volume 24, Issue 3, pp 761–785 | Cite as

A Survey of Localization Systems in Internet of Things

  • Fekher KhelifiEmail author
  • Abbas Bradai
  • Abderrahim Benslimane
  • Priyanka Rawat
  • Mohamed Atri
Article

Abstract

With the rapid development in wireless technologies and the Internet, the Internet of Things (IoT) is envisioned to be an integral part of our daily lives. Localization-based services are among the most attractive applications related to the IoT. They are actually, thanks to the deployment of networks of sensors, able to collect and transmit data in order to determine the targets position. A plethora of localization systems are proposed in the literature. These localization systems are based on different positioning approaches, different techniques and different technologies, making them appropriate for some applications and inappropriate for other applications. This survey provides a general overview of the localization in Wireless Sensor Networks (WSN) and surveys technical details related to approaches and algorithms of various important localization techniques using different technologies. Based on the localization approaches, we propose to classify the localization systems to centralized, distributed and interactive. Considering the techniques of localization, we classify them to distance measurement, angle measurement, arear measurement and hop-count measurement based. Finally, Depending on the manner of the wireless devices interaction with the target, we classify the localization systems to two categories: device-based and device-free systems. In device-based techniques, localization is linked to the target, and localization is determined thanks to the cooperation with other deployed wireless devices. Whereas in the device-free systems, the target does not include any wireless device according to the localization. We compare exhaustively each system in terms of precision, cost, evolution and energy efficiency. Furthermore, we show the importance of localization in modern IoT application such as smart city, smart transportation and mobility. In this concern, we provide an overview of the main challenges of localization in IoT exposed recently in the literature. Finally, we suggest in this paper some future directions in localization studies. This paper intends to help new researchers in the field of localization and IoT by providing a comprehensive survey on recent advances in this field.

Keywords

IoT Localization Survey Smart city 

References

  1. 1.
    Halder S, Ghosal A (2016) A survey on mobility-assisted localization techniques in wireless sensor networks. J Netw Comput Appl 60:82–94CrossRefGoogle Scholar
  2. 2.
    Noel A, Abdaoui A, Badawy A, Elfouly T, Ahmed M, Shehata M (2017). Structural health monitoring using wireless sensor networks: a comprehensive survey. IEEE Commun Surv TutorialsGoogle Scholar
  3. 3.
    Qin J, Sun S, Deng Q, Liu L, Tian Y (2017) Indoor trajectory tracking scheme based on Delaunay triangulation and heuristic information in wireless sensor networks. Sensors 17(6):1275CrossRefGoogle Scholar
  4. 4.
    Li J, Yue X, Chen J, Deng F (2017) A novel robust trilateration method applied to ultra-wide bandwidth location systems. Sensors 17(4):795CrossRefGoogle Scholar
  5. 5.
    Ferreira A, Fernandes D, Catarino A, Monteiro J (2017) Localization and positioning systems for emergency responders: a survey. IEEE Commun Surv TutorialsGoogle Scholar
  6. 6.
    Stoleru R, He T, Stankovic JA (2004) Walking GPS: a practical solution for localization in manually deployed wireless sensor networks. In: Local Computer Networks, 2004. 29th Annual IEEE International Conference on. IEEE, p 480–489Google Scholar
  7. 7.
    Fox D, Burgard W, Dellaert F, Thrun S (1999) Monte Carlo localization: efficient position estimation for mobile robots. AAAI/IAAI 1999(343–349):2–2Google Scholar
  8. 8.
    Chen D, Liu Z, Wang L, Dou M, Chen J, Li H (2013) Natural disaster monitoring with wireless sensor networks: a case study of data-intensive applications upon low-cost scalable systems. Mobile Netw Appl 18(5):651–663CrossRefGoogle Scholar
  9. 9.
    Shang Y, Ruml W, Zhang Y, Fromherz MP (2003) Localization from mere connectivity. In: Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing. ACM, p 201–212Google Scholar
  10. 10.
    Zhang S, Zhang B, Er MJ, Guan Z (2016) A novel node localization algorithm for anisotropic wireless sensor networks with holes based on MDS-MAP and EKF. In: Region 10 Conference (TENCON), 2016 IEEE. IEEE, p 3022–3025Google Scholar
  11. 11.
    Di Franco C, Melani A, Marinoni M (2015). Solving ambiguities in MDS relative localization. In: Advanced Robotics (ICAR), 2015 International Conference on. IEEE, p 230–236Google Scholar
  12. 12.
    Liu J, Zhang Y, Zhao F (2006) Robust distributed node localization with error management. In: Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing. ACM, p 250–261Google Scholar
  13. 13.
    Maung NAM, Kawai M (2014) Experimental evaluations of RSS threshold-based optimised DV-HOP localisation for wireless ad-hoc networks. Electron Lett 50(17):1246–1248CrossRefGoogle Scholar
  14. 14.
    Wang D, Jia H, Chen F, Wen F, Liu X (2010) An improved DV-Distance localization algorithm for wireless sensor networks. In: Advanced Computer Control (ICACC), 2010 2nd International Conference on (Vol. 5). IEEE, p 472–476Google Scholar
  15. 15.
    Das SK, Wang J, Ghosh RK, Reiger R (2011) Algorithmic aspects of sensor localization. In: Theoretical aspects of distributed computing in sensor networks. Springer, Berlin Heidelberg, p 257–291Google Scholar
  16. 16.
    Xu S, Wang X, Wang Y, Wang J (2010) Iterative cooperation DV-hop localization algorithm in wireless sensor networks. In: Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st. IEEE, p 1–5Google Scholar
  17. 17.
    Mandal A, Lopes CV, Givargis T, Haghighat A, Jurdak R, Baldi P (2005) Beep: 3D indoor positioning using audible sound. In: Consumer communications and networking conference, 2005. CCNC. 2005 Second IEEE. IEEE, p 348–353Google Scholar
  18. 18.
    Harter A, Hopper A, Steggles P, Ward A, Webster P (2002) The anatomy of a context-aware application. Wirel Netw 8(2/3):187–197CrossRefzbMATHGoogle Scholar
  19. 19.
  20. 20.
    Priyantha NB, Chakraborty A, Balakrishnan H (2000) The cricket location-support system. In: Proceedings of the 6th annual international conference on Mobile computing and networking. ACM, p 32–43Google Scholar
  21. 21.
    Luo C, Li W, Yang H, Fan M, Yang X (2014) Mobile target positioning using refining distance measurements with inaccurate anchor nodes in chain-type wireless sensor networks. Mobile Netw Appl 19(3):363–381CrossRefGoogle Scholar
  22. 22.
  23. 23.
    Tsui AW, Chuang YH, Chu HH (2009) Unsupervised learning for solving RSS hardware variance problem in Wi-Fi localization. Mobile Netw Appl 14(5):677–691CrossRefGoogle Scholar
  24. 24.
    Kumarasiri R, Alshamaileh K, Tran NH, Devabhaktuni V (2016) An improved hybrid RSS/TDOA wireless sensors localization technique utilizing Wi-Fi networks. Mobile Netw Appl 21(2):286–295CrossRefGoogle Scholar
  25. 25.
    Benson M (1819) Thoughts on education. Richard BaynesGoogle Scholar
  26. 26.
    Kułakowski P, Vales-Alonso J, Egea-López E, Ludwin W, García-Haro J (2010) Angle-of-arrival localization based on antenna arrays for wireless sensor networks. Comput Electr Eng 36(6):1181–1186CrossRefzbMATHGoogle Scholar
  27. 27.
    Steggles P, Gschwind S (2005) The Ubisense smart space platformGoogle Scholar
  28. 28.
    Zeng Wang J, Jin H (2009) Improvement on APIT localization algorithms for wireless sensor networks. In: Networks Security, Wireless Communications and Trusted Computing, 2009. NSWCTC'09. International Conference on (Vol. 1). IEEE, p 719–723Google Scholar
  29. 29.
    Liu J, Wang Z, Yao M, Qiu Z (2016) VN-APIT: virtual nodes-based range-free APIT localization scheme for WSN. Wirel Netw 22(3):867–878CrossRefGoogle Scholar
  30. 30.
    El Assaf A, Zaidi S, Affes S, Kandil N (2013). Hop-count based localization algorithm for wireless sensor networks. In: Microwave Symposium (MMS), 2013 13th Mediterranean. IEEE, p 1–6Google Scholar
  31. 31.
    Tseng CL, Liu FY, Lin CH, Lee CY (2016) A hop-count localization method with boundary improvement for wireless sensor networks. In: Computer, Consumer and Control (IS3C), 2016 International Symposium on. IEEE, p 18–21Google Scholar
  32. 32.
    Ruiz-Ruiz AJ, Canovas O, Lopez-de-Teruel PE (2013) A multisensor architecture providing location-based services for smartphones. Mobile Netw Appl 18(3):310–325CrossRefGoogle Scholar
  33. 33.
    Chen Y, Shu L, Ortiz AM, Crespi N, Lv L (2014) Locating in crowdsourcing-based dataspace: wireless indoor localization without special devices. Mobile Netw Appl 19(4):534–542CrossRefGoogle Scholar
  34. 34.
    Zhuang Y, Syed Z, Georgy J, El-Sheimy N (2015) Autonomous smartphone-based Wi-fi positioning system by using access points localization and crowdsourcing. Pervasive Mob Comput 18:118–136CrossRefGoogle Scholar
  35. 35.
    Jiang P, Zhang Y, Fu W, Liu H, Su X (2015) Indoor mobile localization based on Wi-Fi fingerprint's important access point. Int J Distrib Sens NGoogle Scholar
  36. 36.
    Li WWL, Iltis RA, Win MZ (2013) A smartphone localization algorithm using RSSI and inertial sensor measurement fusion. In: Global Communications Conference (GLOBECOM), 2013 IEEE. IEEE, p 3335–3340Google Scholar
  37. 37.
    Werner M, Kessel M, Marouane C (2011). Indoor positioning using smartphone camera. In Indoor Positioning and Indoor Navigation (IPIN), 2011 International Conference on. IEEE, p 1–6Google Scholar
  38. 38.
    Chen W, Wang W, Li Q, Chang Q, Hou H (2016) A crowd-sourcing indoor localization algorithm via optical camera on a smartphone assisted by wi-fi fingerprint RSSI. Sensors, 16(3):410.Google Scholar
  39. 39.
    Song J, Hur S, Park Y (2015) Fingerprint-based user positioning method using image data of single camera. In: Proceedings of the International Conference on Indoor Positioning and Indoor Navigation, Banff, AB, Canada, p 13–16Google Scholar
  40. 40.
    Lopes SI, Vieira JM, Reis J, Albuquerque D, Carvalho NB (2015) Accurate smartphone indoor positioning using a WSN infrastructure and non-invasive audio for TDoA estimation. PervasiveMob Comput 20:29–46CrossRefGoogle Scholar
  41. 41.
    Liu K, Liu X, Xie L, Li X (2013) Towards accurate acoustic localization on a smartphone. In: INFOCOM, 2013 Proceedings IEEE. IEEE, p 495–499Google Scholar
  42. 42.
    Estel M, Fischer L (2015) Feasibility of bluetooth iBeacons for indoor localization. Digital Enterprise Computing (DEC 2015)-GI-Edition: Lecture Notes in Informatics (LNI). P-244. Bonn: Gesellschaft für Informatik, printed by Köllen Druck+ Verlag GmbH, p 97–108Google Scholar
  43. 43.
    Kriz P, Maly F, Kozel T (2016) Improving indoor localization using bluetooth low energy beacons. Mob Inf SystGoogle Scholar
  44. 44.
    Garrigós J, Molina JM, Alarcón M, Chazarra J, Ruiz-Canales A, Martínez JJ (2017) Platform for the management of hydraulic chambers based on mobile devices and Bluetooth low-energy motes. Agric Water Manag 183:169–176CrossRefGoogle Scholar
  45. 45.
    Yan W, Jing Z, Nailong Z (2015) The designing of indoor localization system based on self-organized WSN using PulsON UWB sensors. In: Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on. IEEE, p 965–969Google Scholar
  46. 46.
    Zhang C, Kuhn MJ, Merkl BC, Fathy AE, Mahfouz MR (2010) Real-time noncoherent UWB positioning radar with millimeter range accuracy: theory and experiment. IEEE Trans Microwave Theory Tech 58(1):9–20CrossRefGoogle Scholar
  47. 47.
    Yang D, Li H, Zhang Z, Peterson GD (2013) Compressive sensing based sub-mm accuracy UWB positioning systems: a space–time approach. Digital Signal Process 23(1):340–354MathSciNetCrossRefGoogle Scholar
  48. 48.
    Itagaki Y, Suzuki A, Iyota T (2012) Indoor positioning for moving objects using a hardware device with spread spectrum ultrasonic waves. In Indoor Positioning and Indoor Navigation (IPIN), 2012 International Conference on. IEEE, p 1–6Google Scholar
  49. 49.
    Li J, Han G, Zhu C, Sun G (2016) An indoor ultrasonic positioning system based on TOA for internet of things. Mob Inf SystGoogle Scholar
  50. 50.
    De Angelis A, Moschitta A, Carbone P, Calderini M, Neri S, Borgna R, Peppucci M (2015) Design and characterization of a portable ultrasonic indoor 3-D positioning system. IEEE Trans Instrum Meas 64(10):2616–2625CrossRefGoogle Scholar
  51. 51.
    Brandl M, Posnicek T, Kellner K (2016) Position estimation of RFID-based sensors using SAW compressive receivers. Sensors Actuators A Phys 244:277–284CrossRefGoogle Scholar
  52. 52.
    Son Y, Joung M, Lee YW, Kwon OH, Song HJ (2016) Tag localization in a two-dimensional RFID tag matrix. Futur Gener Comput SystGoogle Scholar
  53. 53.
    Saab SS, Nakad ZS (2011) A standalone RFID indoor positioning system using passive tags. IEEE Trans Ind Electron 58(5):1961–1970CrossRefGoogle Scholar
  54. 54.
    Gao Z, Ma Y, Liu K, Miao X, Zhao Y (2017) An indoor multi-tag cooperative localization algorithm based on NMDS for RFID. IEEE Sensors J 17(7):2120–2128CrossRefGoogle Scholar
  55. 55.
    Nakamura Y, Namimatsu Y, Miyazaki N, Matsuo Y, Nishimura T (2007) A method for estimating position and orientation with a topological approach using multiple infrared tags. In: Networked Sensing Systems, 2007. INSS'07. Fourth International Conference on. IEEE, p 187–195Google Scholar
  56. 56.
    Want R, Hopper A, Falcao V, Gibbons J (1992) The active badge location system. ACM Trans Inf Syst 10(1):91–102CrossRefGoogle Scholar
  57. 57.
    Yang B, Wei Q, Zhang M (2017) Multiple human location in a distributed binary pyroelectric infrared sensor network. Infrared Phys TechnolGoogle Scholar
  58. 58.
    Tao S, Kudo M, Pei BN, Nonaka H, Toyama J (2015) Multiperson locating and their soft tracking in a binary infrared sensor network. IEEE Trans Hum-Mach Syst 45(5):550–561CrossRefGoogle Scholar
  59. 59.
    Djuric PM, Vemula M, Bugallo MF (2008) Target tracking by particle filtering in binary sensor networks. IEEE Trans Signal Process 56(6):2229–2238MathSciNetCrossRefzbMATHGoogle Scholar
  60. 60.
    de Miguel-Bilbao S, Roldan J, Garcia J, Lopez F, Garcia-Sagredo P, Ramos V (2013) Comparative analysis of indoor location technologies for monitoring of elderly. In: e-Health Networking, Applications & Services (Healthcom), 2013 IEEE 15th International Conference on. IEEE, p 320–323Google Scholar
  61. 61.
    Sobhani B, Mazzotti M, Paolini E, Giorgetti A, Chiani M (2013) Effect of state space partitioning on Bayesian tracking for UWB radar sensor networks. In: Ultra-Wideband (ICUWB), 2013 IEEE International Conference on. IEEE, p 120–125Google Scholar
  62. 62.
    Mrazovac B, Bjelica MZ, Kukolj D, Todorovic BM, Samardzija D (2012) A human detection method for residential smart energy systems based on ZigBee RSSI changes. IEEE Trans Consum Electron 58(3)Google Scholar
  63. 63.
    Caicedo D, Pandharipande A (2014) Distributed ultrasonic zoned presence sensing system. IEEE Sensors J 14(1):234–243CrossRefGoogle Scholar
  64. 64.
    Mokhtari G, Zhang Q, Nourbakhsh G, Ball S, Karunanithi M (2017) BLUESOUND: a new resident identification sensor—using ultrasound Array and BLE Technology for Smart Home Platform. IEEE Sensors J 17(5):1503–1512CrossRefGoogle Scholar
  65. 65.
    Hnat TW, Griffiths E, Dawson R, Whitehouse K (2012) Doorjamb: unobtrusive room-level tracking of people in homes using doorway sensors. In: Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems. ACM, p 309–322Google Scholar
  66. 66.
    Shu Y, Huang Y, Zhang J, Coué P, Cheng P, Chen J, Shin KG (2016) Gradient-based fingerprinting for indoor localization and tracking. IEEE Trans Ind Electron 63(4):2424–2433CrossRefGoogle Scholar
  67. 67.
    Gong L, Yang W, Xiang C, Man D, Yu M, Yin Z (2016) WiSal: Ubiquitous Wi-Fi-Based Device-Free Passive Subarea Localization without Intensive Site-Survey. In: Trustcom/BigDataSE/I SPA, 2016 IEEE. IEEE, p 1129–1136Google Scholar
  68. 68.
    Pirzada N, Nayan MY, Hassan MF, Subhan F, Sakidin H (2016). WLAN location fingerprinting technique for device-free indoor localization system. In: Computer and Information Sciences (ICCOINS), 2016 3rd International Conference on (pp. 650–655). IEEEGoogle Scholar
  69. 69.
    Xiao J, Wu K, Yi Y, Wang L, Ni LM (2013) Pilot: passive device-free indoor localization using channel state information. In: Distributed computing systems (ICDCS), 2013 IEEE 33rd international conference on. IEEE, p 236–245Google Scholar
  70. 70.
    Yang L, Lin Q, Li X, Liu T, Liu Y (2015) See through walls with cots rfid system!. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking. ACM, p 487–499Google Scholar
  71. 71.
    Wagner B, Timmermann D (2013) Approaches for device-free multi-user localization with passive RFID. In: Indoor Positioning and Indoor Navigation (IPIN), 2013 International Conference on. IEEE, p 1–6Google Scholar
  72. 72.
    Ruan W, Sheng QZ, Yao L, Gu T, Ruta M, Shangguan L (2016) Device-free indoor localization and tracking through human-object interactions. In: World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2016 IEEE 17th International Symposium on A. IEEE, p 1–9Google Scholar
  73. 73.
    Sun Z, Wang P, Vuran MC, Al-Rodhaan MA, Al-Dhelaan AM, Akyildiz IF (2011) MISE-PIPE: magnetic induction-based wireless sensor networks for underground pipeline monitoring. Ad Hoc Netw 9(3):218–227CrossRefGoogle Scholar
  74. 74.
    Haverinen J, Kemppainen A (2009) Global indoor self-localization based on the ambient magnetic field. Robot Auton Syst 57(10):1028–1035CrossRefGoogle Scholar
  75. 75.
    Suksakulchai S, Thongchai S, Wilkes DM, Kawamura K (2000) Mobile robot localization using an electronic compass for corridor environment. In: Systems, Man, and Cybernetics, 2000 IEEE International Conference on (Vol. 5). IEEE, p 3354–3359Google Scholar
  76. 76.
    Sun Y, Meng W, Li C, Zhao N, Zhao K, Zhang N (2017) Human localization using multi-source heterogeneous data in indoor environments. IEEE Access 5:812–822CrossRefGoogle Scholar
  77. 77.
    Sun Y, Zhao K, Wang J, Li W, Bai G, Zhang N (2016) Device-free human localization using panoramic camera and indoor map. In: Consumer Electronics-China (ICCE-China), 2016 IEEE International Conference on. IEEE, p 1–5Google Scholar
  78. 78.
    Liu S, Yin L, Ho WK, Ling KV, Schiavon S (2017) A tracking cooling fan using geofence and camera-based indoor localization. Build Environ 114:36–44CrossRefGoogle Scholar
  79. 79.
    Books, Internet of Things (IOT) and Its Applications in Electrical Power Industry, July 4th, 2017 https://www.electricaltechnology.org/2016/07/internet-of-things-iot-and-its-applications-in-electrical-power-industry.html
  80. 80.
    Hui TK, Sherratt RS, Sánchez DD (2016). Major requirements for building Smart Homes in Smart Cities based on Internet of Things technologies. Futur Gener Comput SystGoogle Scholar
  81. 81.
    Schiller J, Voisard A (eds) (2004) Location-based services. ElsevierGoogle Scholar
  82. 82.
    Čelan V, Stančić I, Musić J (2016). Cleaning up smart cities—localization of semi-autonomous floor scrubber. In: Computer and Energy Science (SpliTech), International Multidisciplinary Conference on. IEEE, p 1–6Google Scholar
  83. 83.
    Zhabelova G, Vyatkin V (2012) Multiagent smart grid automation architecture based on IEC 61850/61499 intelligent logical nodes. IEEE Trans Ind Electron 59(5):2351–2362CrossRefGoogle Scholar
  84. 84.
    Holenderski M, Verhoeven R, Ozcelebi T, Lukkien JJ (2014) Light pole localization in a smart city. In: Emerging Technology and Factory Automation (ETFA), 2014 IEEE. IEEE, p 1–4Google Scholar
  85. 85.
    Wu FJ, Luo T (2015) Infrastructureless signal source localization using crowdsourced data for smart-city applications. In: Communications (ICC), 2015 IEEE International Conference on. IEEE, p 586–591Google Scholar
  86. 86.
    Chen M, Yang J, Zhu X, Wang X, Liu M, Song J (2017) Smart home 2.0: innovative smart home system powered by botanical IoT and emotion detection. Mobile Networks and Applications, p 1–11Google Scholar
  87. 87.
    Jeong JP, Yeon S, Kim T, Lee H, Kim SM, Kim SC SALA: Smartphone-Assisted Localization Algorithm for Positioning Indoor IoT devices. Wireless Netw 1–21Google Scholar
  88. 88.
    Mohammadi M, Al-Fuqaha A, Guizani M, Oh JS (2017) Semi-supervised deep reinforcement learning in support of IoT and smart city services. IEEE Internet of Things JournalGoogle Scholar
  89. 89.
    Baek SH, Choi EC, Huh JD, Park KR (2007) Sensor information management mechanism for context-aware service in ubiquitous home. IEEE Trans Consum Electron 53(4)Google Scholar
  90. 90.
    Yang Q, He Z, Zhao K, Gao T (2016) A time localization system in smart home using hierarchical structure and dynamic frequency. In: High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2016 IEEE 18th International Conference on. IEEE, p 831–838Google Scholar
  91. 91.
    Gu Y, Ren F (2015) Energy-efficient indoor localization of smart hand-held devices using Bluetooth. IEEE Access 3:1450–1461CrossRefGoogle Scholar
  92. 92.
    Wan J, Tang S, Shu Z, Li D, Wang S, Imran M, Vasilakos AV (2016) Software-defined industrial internet of things in the context of industry 4.0. IEEE Sensors J 16(20):7373–7380CrossRefGoogle Scholar
  93. 93.
    Lin K, Wang W, Bi Y, Qiu M, Hassan MM (2016) Human localization based on inertial sensors and fingerprints in the industrial internet of things. Comput Netw 101:113–126CrossRefGoogle Scholar
  94. 94.
    Zhai C, Zou Z, Zhou Q, Mao J, Chen Q, Tenhunen H et al (2017) A 2.4-GHz ISM RF and UWB hybrid RFID real-time locating system for industrial enterprise internet of things. Enterprise. Inf Syst 11(6):909–926Google Scholar
  95. 95.
    Zuehlke D (2010) Smart factory towards a factory-of-things. Annu Rev Control 34(1):129–138CrossRefGoogle Scholar
  96. 96.
    Görlich D, Stephan P, Quadflieg J (2007) Demonstrating remote operation of industrial devices using mobile phones. In: Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology. ACM, p 474–477Google Scholar
  97. 97.
    Ha YG, Byun YC (2012). A ubiquitous homecare service system using a wearable user interface device. In: Computer and Information Science (ICIS), 2012 IEEE/ACIS 11th International Conference on. IEEE, p 649–650Google Scholar
  98. 98.
    Rahman T, Adams AT, Zhang M, Cherry E, Choudhury T (2015) BodyBeat: eavesdropping on our body using a wearable microphone. GetMobile: Mobile Computing and Communications 19(1):14–17CrossRefGoogle Scholar
  99. 99.
    Calderoni L, Ferrara M, Franco A, Maio D (2015) Indoor localization in a hospital environment using random forest classifiers. Expert Syst Appl 42(1):125–134CrossRefGoogle Scholar
  100. 100.
    Belhajem I, Maissa YB, Tamtaoui A (2017) Improving vehicle localization in a Smart City with low cost sensor networks and support vector machines. Mobile Netw Appl 1–10Google Scholar
  101. 101.
    Lee EK, Gerla M, Pau G, Lee U, Lim JH (2016) Internet of vehicles: from intelligent grid to autonomous cars and vehicular fogs. Int J Distrib Sens Netw 12(9):1550147716665500CrossRefGoogle Scholar
  102. 102.
    Chen KW, Tsai HM, Hsieh CH, Lin SD, Wang CC, Yang SW, … Lee YJ (2014). Connected vehicle safety science, system, and framework. In Internet of Things (WF-IoT), 2014 IEEE World Forum on. IEEE, p 235–240Google Scholar
  103. 103.
    Llorca DF, Quintero R, Parra I, Sotelo MA (2017) Recognizing individuals in groups in outdoor environments combining stereo vision, RFID and BLE. Clust Comput 20(1):769–779CrossRefGoogle Scholar
  104. 104.
  105. 105.
    Building S (2014) Real time monitoring and control Maximizing the added value of lot. http://www.wi4b.it/smart_building.php. Accessed 5 June 2017
  106. 106.
    Chester D (2016) Embracing automation: getting behind the future of transport. https://infrastructuremagazine.com.au/2016/10/31/embracing-automation-getting-behind-the-futureof-transport/ Accessed 5 June 2017

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Fekher Khelifi
    • 1
    Email author
  • Abbas Bradai
    • 2
  • Abderrahim Benslimane
    • 3
  • Priyanka Rawat
    • 3
  • Mohamed Atri
    • 1
  1. 1.Laboratory of Electronics and Microelectronics (EμE), Faculty of SciencesUniversity of Monastir (UM)MonastirTunisia
  2. 2.XLIM InstituteUniversity of PoitiersPoitiersFrance
  3. 3.University of Avignon, LIA – CERIAvignonFrance

Personalised recommendations