survey

Mobility Increases Localizability: A Survey on Wireless Indoor Localization using Inertial Sensors

Authors:

Yunhao LiuAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 47, Issue 3

Article No.: 54, Pages 1 - 34

https://doi.org/10.1145/2676430

Published: 01 April 2015 Publication History

Abstract

Wireless indoor positioning has been extensively studied for the past 2 decades and continuously attracted growing research efforts in mobile computing context. As the integration of multiple inertial sensors (e.g., accelerometer, gyroscope, and magnetometer) to nowadays smartphones in recent years, human-centric mobility sensing is emerging and coming into vogue. Mobility information, as a new dimension in addition to wireless signals, can benefit localization in a number of ways, since location and mobility are by nature related in the physical world. In this article, we survey this new trend of mobility enhancing smartphone-based indoor localization. Specifically, we first study how to measure human mobility: what types of sensors we can use and what types of mobility information we can acquire. Next, we discuss how mobility assists localization with respect to enhancing location accuracy, decreasing deployment cost, and enriching location context. Moreover, considering the quality and cost of smartphone built-in sensors, handling measurement errors is essential and accordingly investigated. Combining existing work and our own working experiences, we emphasize the principles and conduct comparative study of the mainstream technologies. Finally, we conclude this survey by addressing future research directions and opportunities in this new and largely open area.

References

[1]

Gregory D. Abowd, Maria Ebling, G. Hung, Hui Lei, and Hans-Werner Gellersen. 2002. Context-aware computing. IEEE Pervasive Comput. 1, 3 (2002), 22--23.

Digital Library

[2]

M. H. Afzal, V. Renaudin, and G. Lachapelle. 2001. Assessment of indoor magnetic field anomalies using multiple magnetometers. In Proceedings of ION International Technical Meeting of The Satellite Division of the Institute of Navigation (GNSS).

[3]

Moustafa Alzantot and Moustafa Youssef. 2012. CrowdInside: Automatic construction of indoor floorplans. In Proceedings of ACM International Conference on Advances in Geographic Information Systems (GIS).

Digital Library

[4]

M. Angermann and P. Robertson. 2012. FootSLAM: Pedestrian simultaneous localization and mapping without exteroceptive sensors hitchhiking on human perception and cognition. Proc. IEEE 100, Special Centennial Issue (2012), 1840--1848.

[5]

Shahid Ayub, Xiaowei Zhou, Soroush Honary, Alireza Bahraminasab, and Bahram Honary. 2012. Indoor pedestrian displacement estimation using smart phone inertial sensors. Int. J. Innovative Comput. Appl. 4, 1 (2012), 35--42.

Digital Library

[6]

Martin Azizyan, Ionut Constandache, and Romit Roy Choudhury. 2009. SurroundSense: Mobile phone localization via ambience fingerprinting. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[7]

P. Bahl and V. N. Padmanabhan. 2000. RADAR: An In-building RF-based user location and tracking system. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM).

[8]

Ling Bao and Stephen S. Intille. 2004. Activity recognition from user-annotated acceleration data. In Pervasive Computing. Lecture Notes in Computer Science, Vol. 3001. Springer, Berlin, 1--17.

[9]

P. Barralon, N. Vuillerme, and N. Noury. 2006. Walk detection with a kinematic sensor: Frequency and wavelet comparison. In Proceedings of IEEE International Conference of Engineering in Medicine and Biology Society (EMBS).

[10]

John E. A. Bertram and Andy Ruina. 2001. Multiple walking speed--frequency relations are predicted by constrained optimization. Elsevier J. Theor. Biol. 209, 4 (2001), 445--453.

[11]

Agata Brajdic and Robert Harle. 2013. Walk detection and step counting on unconstrained smartphones. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[12]

Yiqiang Chen, Qiang Yang, Jie Yin, and Xiaoyong Chai. 2006. Power-efficient access-point selection for indoor location estimation. IEEE Trans. Knowl. Data Eng. 18, 7 (Jul 2006), 877--888.

Digital Library

[13]

Krishna Chintalapudi, Anand Padmanabha Iyer, and Venkata N. Padmanabhan. 2010. Indoor localization without the pain. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[14]

Dae-Ki Cho, Min Mun, Uichin Lee, W. J. Kaiser, and M. Gerla. 2010. AutoGait: A mobile platform that accurately estimates the distance walked. In Proceedings of IEEE International Conference on Pervasive Computing and Communications (PerCom).

[15]

Yohan Chon, Nicholas D. Lane, Fan Li, Hojung Cha, and Feng Zhao. 2012. Automatically characterizing places with opportunistic crowdsensing using smartphones. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[16]

Ionut Constandache, Xuan Bao, Martin Azizyan, and Romit Roy Choudhury. 2010a. Did you see bob&quest;: Human localization using mobile phones. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[17]

I. Constandache, R. R. Choudhury, and I. Rhee. 2010b. Towards mobile phone localization without war-driving. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM).

Digital Library

[18]

Richard Dixon. 2012. 2012 a breakthrough year for motion combo sensors in consumer and mobile applications. IHS iSuppli Microelectromechanical Systems (MEMS) Market Brief (2012).

[19]

Shih-Hau Fang and Tsung-Nan Lin. 2012. Principal component localization in indoor WLAN environments. IEEE Trans. Mobile Comput. 11, 1 (Jan 2012), 100--110.

Digital Library

[20]

Ngewi Fet, Marcus Handte, and Pedro José Marrón. 2013. A model for WLAN signal attenuation of the human body. In Proceedings of ACM UbiComp. 499--508.

Digital Library

[21]

Dieter Fox, Sebastian Thrun, Wolfram Burgard, and Frank Dellaert. 2001. Particle filters for mobile robot localization. In Sequential Monte Carlo Methods in Practice. Springer, 401--428.

[22]

P. Goyal, V. J. Ribeiro, H. Saran, and A. Kumar. 2011. Strap-down pedestrian dead-reckoning system. In Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[23]

Dominik Gusenbauer, Carsten Isert, and J. Krosche. 2010. Self-contained indoor positioning on off-the-shelf mobile devices. In Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[24]

R. Harle. 2013. A survey of indoor inertial positioning systems for pedestrians. IEEE Commun. Surv. Tutorials 15, 3 (2013), 1281--1293.

[25]

Samuli Hemminki, Petteri Nurmi, and Sasu Tarkoma. 2013. Accelerometer-based transportation mode detection on smartphones. In Proceedings of ACM Conference on Embedded Networked Sensor Systems (SenSys).

Digital Library

[26]

Sebastian Hilsenbeck, Dmytro Bobkov, Georg Schroth, Robert Huitl, and Eckehard Steinbach. 2014. Graph-based data fusion of pedometer and WiFi measurements for mobile indoor positioning. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[27]

Jian hua Wang, Jian-Jiun Ding, Yu Chen, and Hsin-Hui Chen. 2012. Real time accelerometer-based gait recognition using adaptive windowed wavelet transforms. In Proceedings of IEEE Asia Pacific Conference on Circuits and Systems (APCCAS).

[28]

InvenSense. 2013. MPU-6500 Six-Axis (Gyro + Accelerometer) MEMS MotionTracking Devices for Smart Phones, Tablets, Wearable Sensors, Remotes, Pedestrian Navigation, and Sports & Fitness Tracking. Retrieved from http://www.invensense.com/mems/gyro/mpu6500.html.

[29]

Toshiki Iso and Kenichi Yamazaki. 2006. Gait analyzer based on a cell phone with a single three-axis accelerometer. In Proceedings of ACM Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI).

Digital Library

[30]

Yifei Jiang, Yun Xiang, Xin Pan, Kun Li, Qin Lv, Robert P. Dick, Li Shang, and Michael Hannigan. 2013a. Hallway based automatic indoor floorplan construction using room fingerprints. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[31]

Zhiping Jiang, Wei Xi, Xiang-yang Li, Shaojie Tang, Jizhong Zhao, Jin-Song Han, Kun Zhao, Zhi Wang, and Bo Xiao. 2014. Communicating is crowdsourcing: Wi-Fi indoor localization with CSI-based speed estimation. Journal of Computer Science and Technology 29, 4 (2014), 589--604.

[32]

A. R. Jimenez, F. Seco, C. Prieto, and J. Guevara. 2009. A comparison of pedestrian dead-reckoning algorithms using a low-cost MEMS IMU. In Proceedings of IEEE International Symposium on Intelligent Signal Processing (WISP).

[33]

Junghyun Jun, Yu Gu, Long Cheng, Banghui Lu, Jun Sun, Ting Zhu, and Jianwei Niu. 2013. Social-Loc: Improving indoor localization with social sensing. In Proceedings of ACM Conference on Embedded Networked Sensor Systems (SenSys).

Digital Library

[34]

Donnie H. Kim, Jeffrey Hightower, Ramesh Govindan, and Deborah Estrin. 2009. Discovering semantically meaningful places from pervasive RF-beacons. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[35]

Yungeun Kim, Hyojeong Shin, and Hojung Cha. 2012. Smartphone-based Wi-Fi pedestrian-tracking system tolerating the RSS variance problem. In Proceedings of IEEE Conference on Pervasive Computing and Communications (PerCom).

[36]

M. Klepal, Stephane Beauregard, and others. 2008. A backtracking particle filter for fusing building plans with PDR displacement estimates. In Proceedings of IEEE Workshops on Positioning, Navigation and Communication (WPNC).

[37]

T. Kobayashi, K. Hasida, and N. Otsu. 2011. Rotation invariant feature extraction from 3-D acceleration signals. In Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP).

[38]

Nisarg Kothari, Balajee Kannan, Evan D. Glasgwow, and M. Bernardine Dias. 2012. Robust indoor localization on a commercial smart phone. Procedia Comput. Sci. 10 (2012), 1114--1120.

[39]

Swarun Kumar, Stephanie Gil, Dina Katabi, and Daniela Rus. 2014. Accurate indoor localization with zero start-up cost. In Proceedings of ACM Annual International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[40]

Quentin Ladetto. 2000. On foot navigation: Continuous step calibration using both complementary recursive prediction and adaptive kalman filtering. In Proceedings of ION GPS.

[41]

Kun-Chan Lan and Wen-Yuah Shih. 2013. Using floor plan to calibrate sensor drift error for indoor localization. In Proceedings of the Joint ERCIM eMobility and MobiSense Workshop (ERCIM).

[42]

Fan Li, Chunshui Zhao, Guanzhong Ding, Jian Gong, Chenxing Liu, and Feng Zhao. 2012b. A reliable and accurate indoor localization method using phone inertial sensors. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[43]

Mingmei Li, Kazuyuki Tasaka, and Kiyohito Yoshihara. 2012a. An integrated location method using reference landmarks for dead reckoning system. In Proceedings of International Conference on Networks (ICN).

[44]

Defu Lian and Xing Xie. 2011. Learning location naming from user check-in histories. In Proceedings of ACM International Conference on Advances in Geographic Information Systems (GIS).

Digital Library

[45]

H. Lim, L.-C. Kung, J. C. Hou, and H. Luo. 2006. Zero-configuration, robust indoor localization: Theory and experimentation. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM).

[46]

Hongbo Liu, Yu Gan, Jie Yang, Simon Sidhom, Yan Wang, Yingying Chen, and Fan Ye. 2012. Push the limit of WiFi based localization for smartphones. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[47]

Jingbin Liu, Ruizhi Chen, Ling Pei, Wei Chen, Tomi Tenhunen, Heidi Kuusniemi, Tuomo Kroger, and Yuwei Chen. 2010. Accelerometer assisted robust wireless signal positioning based on a hidden Markov model. In Proceedings of the IEEE/ION Position Location and Navigation Symposium (PLANS).

[48]

Kaikai Liu, Xinxin Liu, and Xiaolin Li. 2013. Guoguo: Enabling fine-grained indoor localization via smartphone. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[49]

A. Mannini and A.M. Sabatini. 2011. A hidden Markov model-based technique for gait segmentation using a foot-mounted gyroscope. In Proceedings of IEEE International Conference of Engineering in Medicine and Biology Society (EMBS).

[50]

Rodolfo Margaria and R Margaria. 1976. Biomechanics and Energetics of Muscular Exercise. Clarendon Press, Oxford.

[51]

M. Marschollek, Mehmet Goevercin, Klaus-Hendrik Wolf, Bianying Song, M. Gietzelt, R. Haux, and Elisabeth Steinhagen-Thiessen. 2008. A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons. In Proceedings of IEEE International Conference of Engineering in Medicine and Biology Society (EMBS).

[52]

Rainer Mautz and Sebastian Tilch. 2011. Survey of optical indoor positioning systems. In Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[53]

Brian McClendon. 2011. A New Frontier for Google Maps: Mapping the Indoors. Retrieved from http://googleblog.blogspot.hk/2011/11/new-frontier-for-google-maps-mapping.html.

[54]

Emiliano Miluzzo, Nicholas D. Lane, Kristóf Fodor, Ronald Peterson, Hong Lu, Mirco Musolesi, Shane B. Eisenman, Xiao Zheng, and Andrew T. Campbell. 2008. Sensing meets mobile social networks: The design, implementation and evaluation of the cenceme application. In Proceedings of ACM Conference on Embedded Networked Sensor Systems (SenSys).

Digital Library

[55]

Ayman Naguib, Payam Pakzad, Ravi Palanki, Sameera Poduri, and Yin Chen. 2013. Scalable and accurate indoor positioning on mobile devices. In Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[56]

L. M. Ni, Yunhao Liu, Yiu Cho Lau, and A. P. Patil. 2003. LANDMARC: Indoor location sensing using active RFID. In Proceedings of IEEE International Conference on Pervasive Computing and Communications (PerCom).

Digital Library

[57]

Jun-geun Park, Ami Patel, Dorothy Curtis, Seth Teller, and Jonathan Ledlie. 2012. Online pose classification and walking speed estimation using handheld devices. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[58]

Kwanghyo Park, Hyojeong Shin, and Hojung Cha. 2013. Smartphone-based pedestrian tracking in indoor corridor environments. Springer Personal Ubiquitous Comput. 17, 2 (2013), 359--370.

Digital Library

[59]

Neal Patwari and Sneha K. Kasera. 2007. Robust location distinction using temporal link signatures. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[60]

N. B. Priyantha, A. Chakraborty, and H. Balakrishnan. 2000. The cricket location-support system. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[61]

Qifan Pu, Sidhant Gupta, Shyam Gollakota, and Shwetak Patel. 2013. Whole-home gesture recognition using wireless signals. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[62]

Aveek Purohit, Zheng Sun, Shijia Pan, and Pei Zhang. 2013. SugarTrail: Indoor navigation in retail environments without surveys and maps. In Proceedings of IEEE Communications Society Conference on Sensor Mesh and Ad Hoc Communications and Networks (SECON).

[63]

Kiran K. Rachuri, Mirco Musolesi, Cecilia Mascolo, Peter J. Rentfrow, Chris Longworth, and Andrius Aucinas. 2010. EmotionSense: A mobile phones based adaptive platform for experimental social psychology research. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[64]

Valentin Radu and Mahesh K. Marina. 2013. HiMLoc: Indoor smartphone localization via activity aware pedestrian dead reckoning with selective crowdsourced wifi fingerprinting. In Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[65]

Anshul Rai, Krishna Kant Chintalapudi, Venkata N. Padmanabhan, and Rijurekha Sen. 2012. Zee: Zero-effort crowdsourcing for indoor localization. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[66]

Cliff Randell, C. Djiallis, and H. Muller. 2003. Personal position measurement using dead reckoning. In Proceedings of IEEE International Symposium on Wearable Computers (ISWC).

Digital Library

[67]

Nishkam Ravi, Nikhil Dandekar, Preetham Mysore, and Michael L. Littman. 2005. Activity recognition from accelerometer data. In Proceedings of AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI).

Digital Library

[68]

Valérie Renaudin, Melania Susi, and Gérard Lachapelle. 2012. Step length estimation using handheld inertial sensors. Sensors 12, 7 (2012), 8507--8525.

[69]

Liu Rong, Duan Zhiguo, Zhou Jianzhong, and Liu Ming. 2007. Identification of individual walking patterns using gait acceleration. In Proceedings of International Conference on Bioinformatics and Biomedical Engineering (ICBBE).

[70]

Jessica Rose and James Gibson Gamble. 2006. Human Walking. Lippincott Williams & Wilkins, Philadelphia.

[71]

Nirupam Roy, He Wang, and Romit Roy Choudhury. 2014. I am a smartphone and I can tell my users walking direction. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[72]

Albrecht Schmidt, Michael Beigl, and Hans-W Gellersen. 1999. There is more to context than location. Comput. Graphics 23, 6 (Dec. 1999), 893--901.

[73]

Souvik Sen, Jeongkeun Lee, Kyu-Han Kim, and Paul Congdon. 2013. Back to the basics: Avoiding multipath to revive inbuilding WiFi localization. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[74]

Souvik Sen, Božidar Radunovic, Romit Roy Choudhury, and Tom Minka. 2012. You are facing the Mona Lisa: Spot localization using PHY layer information. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[75]

Guobin Shen, Zhuo Chen, Peichao Zhang, Thomas Moscibroda, and Yongguang Zhang. 2013. Walkie-Markie: Indoor pathway mapping made easy. In Proceedings of USENIX Conference on Networked Systems Design and Implementation (NSDI).

Digital Library

[76]

Pekka Siirtola and Juha Roning. 2012. Recognizing human activities user-independently on smartphones based on accelerometer data. Int. J. Interact. Multimedia Artif. Intell. 1, 5 (2012), 38--45.

[77]

Skyhook. 2013. Homepage. Retrieved from http://www.skyhookwireless.com/.

[78]

Philip Steadman. 2006. Why are most buildings rectangular&quest; Architect. Res. Quart. 10, 2 (2006), 119--130.

[79]

Wei Sun, Junliang Liu, Chenshu Wu, Zheng Yang, Xinglin Zhang, and Yunhao Liu. 2013a. MoLoc: On distinguishing fingerprint twins. In Proceedings of IEEE International Conference on Distributed Computing Systems (ICDCS).

Digital Library

[80]

Zheng Sun, Shijia Pan, Yu-Chi Su, and Pei Zhang. 2013b. Headio: Zero-configured heading acquisition for indoor mobile devices through multimodal context sensing. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[81]

Melania Susi, Valérie Renaudin, and Gérard Lachapelle. 2013. Motion mode recognition and step detection algorithms for mobile phone users. Sensors 13, 2 (2013), 1539--1562.

[82]

Arvind Thiagarajan. 2011. Probabilistic Models for Mobile Phone Trajectory Estimation. Ph.D. Dissertation. Massachusetts Institute of Technology.

Digital Library

[83]

Daniel Turner, Stefan Savage, and Alex C. Snoeren. 2011. On the empirical performance of self-calibrating WiFi location systems. In Proceedings of IEEE Conference on Local Computer Networks (LCN).

Digital Library

[84]

Ubisense. 2013. Homepage. Retrieved from http://www.ubisense.net.

[85]

He Wang, Souvik Sen, Ahmed Elgohary, Moustafa Farid, Moustafa Youssef, and Romit Roy Choudhury. 2012. No need to war-drive: Unsupervised indoor localization. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[86]

He Wang, Zhiyang Wang, Guobin Shen, Fan Li, Song Han, and Feng Zhao. 2013. WheelLoc: Enabling continuous location service on mobile phone for outdoor scenarios. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM).

[87]

Harvey Weinberg. 2002. Using the ADXL202 in pedometer and personal navigation applications. Analog Devices AN-602 Application Note (2002).

[88]

Wikipedia. 2014a. Inertial Measurement Unit. Retrieved from http://en.wikipedia.org/wiki/Inertial_ measurement_unit.

[89]

Wikipedia. 2014b. Dead Reckoning. Retrieved from http://en.wikipedia.org/wiki/Dead_reckoning.

[90]

Wikipedia. 2014c. Accelerometer. Retrieved from http://en.wikipedia.org/wiki/Accelerometer.

[91]

Wikipedia. 2014d. Gyroscope. Retrieved from http://en.wikipedia.org/wiki/Gyroscope.

[92]

Wikipedia. 2014e. Magnetometer. Retrieved from http://en.wikipedia.org/wiki/Magnetometer.

[93]

Oliver Woodman and Robert Harle. 2008. Pedestrian localisation for indoor environments. In Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp).

Digital Library

[94]

Chenshu Wu, Zheng Yang, Yunhao Liu, and Wei Xi. 2013a. WILL: Wireless indoor localization without site survey. IEEE Trans. Parallel Distrib. Syst. 24, 4 (2013), 839--848.

Digital Library

[95]

Chenshu Wu, Zheng Yang, Yiyang Zhao, and Yunhao Liu. 2013b. Footprints elicit the truth: Improving global positioning accuracy via local mobility. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM).

[96]

Kaishun Wu, Jiang Xiao, Youwen Yi, Min Gao, and L.M. Ni. 2012. FILA: Fine-grained indoor localization. In Proceedings of the 2012 IEEE International Conference on Computer Communications (INFOCOM). 2210--2218.

[97]

Jie Yang, Simon Sidhom, Gayathri Chandrasekaran, Tam Vu, Hongbo Liu, Nicolae Cecan, Yingying Chen, Marco Gruteser, and Richard P. Martin. 2011. Detecting driver phone use leveraging car speakers. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[98]

Zheng Yang, Longfei Shangguan, Weixi Gu, Zimu Zhou, Chenshu Wu, and Yunhao Liu. 2014. Sherlock: Micro-environment sensing for smartphones. IEEE Trans. Parallel Distrib. Syst. 25, 12 (2014), 3295--3305.

[99]

Zheng Yang, Chenshu Wu, and Yunhao Liu. 2012. Locating in fingerprint space: Wireless indoor localization with little human intervention. In Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom).

Digital Library

[100]

Mao Ye, Dong Shou, Wang-Chien Lee, Peifeng Yin, and Krzysztof Janowicz. 2011. On the semantic annotation of places in location-based social networks. In Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).

Digital Library

[101]

Sungro Yoon, Kyunghan Lee, and Injong Rhee. 2013. FM-based indoor localization via automatic fingerprint DB construction and matching. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[102]

Chuang-Wen You, Nicholas D. Lane, Fanglin Chen, Rui Wang, Zhenyu Chen, Thomas J. Bao, Martha Montes-de Oca, Yuting Cheng, Mu Lin, Lorenzo Torresani, and Andrew T. Campbell. 2013. CarSafe app: Alerting drowsy and distracted drivers using dual cameras on smartphones. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[103]

Moustafa Youssef and Ashok Agrawala. 2005. The horus WLAN location determination system. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[104]

M. Youssef, M. A. Yosef, and M. El-Derini. 2010. GAC: Energy-efficient hybrid GPS-accelerometer-compass GSM localization. In Proceedings of IEEE Global Telecommunications Conference (GLOBECOM).

[105]

Francisco Zampella, R. Jimenez, R. Antonio, and Fernando Seco. 2013. Robust indoor positioning fusing PDR and RF technologies: The RFID and UWB case. In Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[106]

Vladimir M. Zatsiorsky. 1998. Kinematics of Human Motion. Human Kinetics.

[107]

Xinglin Zhang, Zheng Yang, Chenshu Wu, Wei Sun, and Yunhao Liu. 2014. Robust trajectory estimation for crowdsourcing-based mobile applications. IEEE Trans. Parallel Distrib. Syst. 25, 7 (July 2014), 1876--1885.

Digital Library

[108]

Vincent Wenchen Zheng, Evan Wei Xiang, Qiang Yang, and Dou Shen. 2008. Transferring localization models over time. In Proceedings of AAAI National Conference on Artificial Intelligence (AAAI).

Digital Library

[109]

Yu Zheng and Xiaofang Zhou. 2011. Computing with Spatial Trajectories. Springer.

Digital Library

[110]

Pengfei Zhou, Yuanqing Zheng, and Mo Li. 2012a. How long to wait&quest;: Predicting bus arrival time with mobile phone based participatory sensing. In Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys).

Digital Library

[111]

Pengfei Zhou, Yuanqing Zheng, Zhenjiang Li, Mo Li, and Guobin Shen. 2012b. IODetector: A generic service for indoor outdoor detection. In Proceedings of ACM Conference on Embedded Networked Sensor Systems (SenSys).

Digital Library

[112]

Xiaojun Zhu, Qun Li, and Guihai Chen. 2013. APT: Accurate outdoor pedestrian tracking with smartphones. In Proceedings of IEEE International Conference on Computer Communications (INFOCOM).

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Index Terms

Mobility Increases Localizability: A Survey on Wireless Indoor Localization using Inertial Sensors
1. Hardware
  1. Communication hardware, interfaces and storage
2. Networks

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 47, Issue 3

April 2015

602 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/2737799

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering / University of Florida / Gainesville, FL

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Publication History

Published: 01 April 2015

Accepted: 01 October 2014

Revised: 01 July 2014

Received: 01 February 2014

Published in CSUR Volume 47, Issue 3

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Ashraf IZikria YGarg SHur SPark YGuizani M(2024)Enabling Technologies and Techniques for Floor IdentificationACM Computing Surveys10.1145/367887857:1(1-48)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3678878
Zhou HMaekawa T(2024)Predicting Signal Reception Information from GNSS Satellites in Indoor Environments without Site Survey: Towards Opportunistic Indoor Positioning Based on GNSS FingerprintingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785548:3(1-30)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678554
Li DXu JYang ZTang C(2024)Train Once, Locate Anytime for Anyone: Adversarial Learning-based Wireless LocalizationACM Transactions on Sensor Networks10.1145/361409520:2(1-21)Online publication date: 10-Jan-2024
https://dl.acm.org/doi/10.1145/3614095
Tong YWang JZhao ZCui JWu B(2024)Noisy Labels Make Sense: Data-Driven Smartphone Inertial Tracking without Tedious Annotations2024 IEEE 25th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM60985.2024.00061(339-348)Online publication date: 4-Jun-2024
https://doi.org/10.1109/WoWMoM60985.2024.00061
Liu ZLiu JXu XWu K(2024)DeepGPS: Deep Learning Enhanced GPS Positioning in Urban CanyonsIEEE Transactions on Mobile Computing10.1109/TMC.2022.320824023:1(376-392)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMC.2022.3208240
Yang YShen ZDeng QLiu WJiang HXie X(2024)CORAL: Recognition and Locating of Contextual Objects With Unmodulated Acoustic SignalsIEEE Internet of Things Journal10.1109/JIOT.2024.343026211:20(33734-33743)Online publication date: 15-Oct-2024
https://doi.org/10.1109/JIOT.2024.3430262
Seyedkazemi SGursoy MSaygin Y(2024)LuxTrack: Activity Inference Attacks via Smartphone Ambient Light Sensors and CountermeasuresIEEE Internet of Things Journal10.1109/JIOT.2024.340620811:17(28734-28751)Online publication date: 1-Sep-2024
https://doi.org/10.1109/JIOT.2024.3406208
Liu YYang ZLiu YYang Z(2024)Automatic Fingerprint Database UpdateLocation, Localization, and Localizability10.1007/978-981-97-3176-3_9(163-185)Online publication date: 12-Jul-2024
https://doi.org/10.1007/978-981-97-3176-3_9
Liu YYang ZLiu YYang Z(2024)Robust Indoor LocalizationLocation, Localization, and Localizability10.1007/978-981-97-3176-3_8(131-162)Online publication date: 12-Jul-2024
https://doi.org/10.1007/978-981-97-3176-3_8
Caramaschi SBezançon JOlsson CSalvi D(2024)An IoT-Based Method for Collecting Reference Walked Distance for the 6-Minute Walk TestPervasive Computing Technologies for Healthcare10.1007/978-3-031-59717-6_31(478-489)Online publication date: 4-Jun-2024
https://doi.org/10.1007/978-3-031-59717-6_31
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