The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Recent Advances in Wireless Indoor Localization Techniques and System
Open accessAbstract
The advances in localization based technologies and the increasing importance of ubiquitous computing and context-dependent information have led to a growing business interest in location-based applications and services. Today, most application requirements are locating or real-time tracking of physical belongings inside buildings accurately; thus, the demand for indoor localization services has become a key prerequisite in some markets. Moreover, indoor localization technologies address the inadequacy of global positioning system inside a closed environment, like buildings. Based on this, though, this paper aims to provide the reader with a review of the recent advances in wireless indoor localization techniques and system to deliver a better understanding of state-of-the-art technologies and motivate new research efforts in this promising field. For this purpose, existing wireless localization position system and location estimation schemes are reviewed, as we also compare the related techniques and systems along with a conclusion and future trends.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“RFID tags have some benefits: their signals can penetrate walls and obstacles, which cover a wide area, and reuse existing infrastructures, resulting in cost reduction [90].”
From Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies (2019) · cites this paper as [90]
Citations
Cites
RADAR: an in-building RF-based user location and tracking system
Bahl, P., & Padmanabhan, V. N. (2002) · Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064) · doi:10.1109/infcom.2000.832252 · Cited by 8,380
Survey of Wireless Indoor Positioning Techniques and Systems
Liu, H., Darabi, H., Banerjee, P. P., & Liu, J. (2007) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2007.905750 · Cited by 4,184
A survey of indoor positioning systems for wireless personal networks
Gu, Y., Lo, A., & Niemegeers, I. G. M. M. (2009) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2009.090103 · Cited by 1,564
WLAN location determination via clustering and probability distributions
Youssef, M. A., Agrawala, A. K., & Shankar, A. U. (2004) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2003.1192736 · Cited by 925
Yang, Z., Wu, C., & Liu, Y. (2012) · ACM Annual International Conference on Mobile Computing and Networking (MobiCom) · doi:10.1145/2348543.2348578 · Cited by 741
A Survey on Wireless Position Estimation
Gezici, S. (2007) · Wireless Personal Communications · doi:10.1007/s11277-007-9375-z · Cited by 555
Location, Localization, and Localizability
Liu, Y., Yang, Z., Wang, X., & Jian, L. (2010) · Journal of Computer Science and Technology · doi:10.1007/s11390-010-9324-2 · Cited by 313
FIFS: Fine-Grained Indoor Fingerprinting System
Xiao, J., Wu, K., Yi, Y., & Ni, L. M.-S. (2012) · International Conference on Computer Communications and Networks (ICCCN) · doi:10.1109/icccn.2012.6289200 · Cited by 298
Localization Technologies for Indoor Human Tracking
Zhang, D., Xia, F., Yang, Z., Yao, L., & Zhao, W. (2010) · International Conference on Future Information Technology · doi:10.1109/futuretech.2010.5482731 · Cited by 272
A survey of mathematical methods for indoor localization
Seco, F. A., Jiménez, A. R., Prieto, C., Roa, J. O., & Koutsou, K. (2009) · IEEE International Symposium on Intelligent Signal Processing, · doi:10.1109/wisp.2009.5286582 · Cited by 209
Flagged first, then by citations
Research works printed but not linked: 1
- 2011, Archives of Photogrammetry, Cartography and Remote Sensing, 22, 39
Cited by
Sorted by citations
Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications
Yassin, A., Nasser, Y., Awad, M., Al‐Dubai, A., Liu, R., Yuen, C., Raulefs, R., & Aboutanios, E. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2632427 · Cited by 919
RSSI-Based Indoor Localization With the Internet of Things
Sadowski, S., & Spachos, P. (2018) · IEEE Access · doi:10.1109/access.2018.2843325 · Cited by 558
A Survey on Indoor Positioning Systems for IoT-Based Applications
Farahsari, P. S., Farahzadi, A., Rezazadeh, J., & Bagheri, A. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3149048 · Cited by 546
A Review of Indoor Localization Techniques and Wireless Technologies
Obeidat, H., Shuaieb, W. S., Obeidat, O. A., & Abd‐Alhameed, R. A. (2021) · Wireless Personal Communications · doi:10.1007/s11277-021-08209-5 · Cited by 424
Indoor positioning and wayfinding systems: a survey
Kunhoth, J., Karkar, A., Al-Maadeed, S. A., & Al-Ali, A. K. (2020) · Human-centric Computing and Information Sciences · doi:10.1186/s13673-020-00222-0 · Cited by 302
Indoor Fingerprint Positioning Based on Wi-Fi: An Overview
Xia, S., Liu, Y., Yuan, G., Zhu, M., & Wang, Z. (2017) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi6050135 · Cited by 254
Indoor Intelligent Fingerprint-Based Localization: Principles, Approaches and Challenges
Zhu, X., Qu, W., Qiu, T., Zhao, L., Atiquzzaman, M., & Wu, D. O. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3014304 · Cited by 246
Wireless RSSI fingerprinting localization
Yiu, S., Dashti, M., Claußen, H., & Pérez‐Cruz, F. (2016) · Signal Processing · doi:10.1016/j.sigpro.2016.07.005 · Cited by 228
Spectrum Occupancy Measurements: A Survey and Use of Interference Maps
Höyhtyä, M., Mämmelä, A., Eskola, M., Matinmikko‐Blue, M., Kalliovaara, J., Ojaniemi, J., Suutala, J., Ekman, R., Bacchus, R. B., & Roberson, D. A. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2559525 · Cited by 225
WiFi Vision: Sensing, Recognition, and Detection With Commodity MIMO-OFDM WiFi
He, Y., Chen, Y., Hu, Y., & Zeng, B. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2989426 · Cited by 198
Precise Indoor Positioning Using UWB: A Review of Methods, Algorithms and Implementations
Mazhar, F., Khan, M. G., & Sällberg, B. (2017) · Wireless Personal Communications · doi:10.1007/s11277-017-4734-x · Cited by 205
A State-of-the-Art Survey of Indoor Positioning and Navigation Systems and Technologies
Sakpere, W., Oshin, M. A., & Mlitwa, N. (2017) · South African Computer Journal · doi:10.18489/sacj.v29i3.452 · Cited by 196
Localization and Positioning Systems for Emergency Responders: A Survey
Ferreira, A. G., Fernandes, D., Catarino, A. P., & Monteiro, J. L. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2703620 · Cited by 189
Review on UHF RFID Localization Methods
Li, C., Mo, L., & Zhang, D. (2019) · IEEE Journal of Radio Frequency Identification · doi:10.1109/jrfid.2019.2924346 · Cited by 173
Comparative Survey of Indoor Positioning Technologies, Techniques, and Algorithms
Al-Ammar, M., Al-Hadhrami, S. A., Al‐Salman, A. S., Alarifi, A., Al-Khalifa, H. S., Alnafessah, A., & Alsaleh, M. (2014) · International Conference on Cyberworlds (CW) · doi:10.1109/cw.2014.41 · Cited by 171
A Survey of Recent Indoor Localization Scenarios and Methodologies
Yang, T. C., Cabani, A., & Chafouk, H. (2021) · Sensors · doi:10.3390/s21238086 · Cited by 167
RSSI-Based Distributed Self-Localization for Wireless Sensor Networks Used in Precision Agriculture
Abouzar, P., Michelson, D. G., & Hamdi, M. (2016) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2016.2586844 · Cited by 159
Manesh, M. R., & Kaabouch, N. (2017) · International Journal of Critical Infrastructure Protection · doi:10.1016/j.ijcip.2017.10.002 · Cited by 153
A Review of Internet of Things Technologies for Ambient Assisted Living Environments
Maskeliūnas, R., Damaševičius, R., & Segal, S. (2019) · Future Internet · doi:10.3390/fi11120259 · Cited by 147
Seamless Outdoors-Indoors Localization Solutions on Smartphones
Maghdid, H. S., Lami, I. A., Ghafoor, K. Z., & Lloret, J. (2016) · ACM Computing Surveys · doi:10.1145/2871166 · Cited by 140
Smelling Nano Aerial Vehicle for Gas Source Localization and Mapping
Burgués, J., Bennetts, V. H., Lilienthal, A. J., & Marco, S. (2019) · Sensors · doi:10.3390/s19030478 · Cited by 137
Oguntala, G., Abd‐Alhameed, R. A., Jones, S. M., Noras, J., Patwary, M., & Rodrı́guez, J. (2018) · Computer Science Review · doi:10.1016/j.cosrev.2018.09.001 · Cited by 134
SVM-based indoor localization in Wireless Sensor Networks
Chriki, A., Touati, H., & Snoussi, H. (2017) · International Wireless Communications and Mobile Computing Conference (IWCMC) · doi:10.1109/iwcmc.2017.7986446 · Cited by 137
TOURIST ADOPTION OF MAPPING APPS: A UTAUT2 PERSPECTIVE OF SMART TRAVELLERS
Gupta, A., & Dogra, N. (2017) · Tourism and hospitality management · doi:10.20867/thm.23.2.6 · Cited by 127
A Look at the Recent Wireless Positioning Techniques With a Focus on Algorithms for Moving Receivers
Tahat, A. A., Kaddoum, G., Yousefi, S., Valaee, S., & Gagnon, F. (2016) · IEEE Access · doi:10.1109/access.2016.2606486 · Cited by 126
An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion
Ma, R., Guo, Q., Hu, C., & Xue, J. (2015) · Sensors · doi:10.3390/s150921824 · Cited by 124
A Survey of Smartphone-Based Indoor Positioning System Using RF-Based Wireless Technologies
Subedi, S., & Pyun, J.-Y. (2020) · Sensors · doi:10.3390/s20247230 · Cited by 135
Manesh, M. R., & Kaabouch, N. (2019) · Computers & Security · doi:10.1016/j.cose.2019.05.003 · Cited by 119
Survey on indoor localization system and recent advances of WIFI fingerprinting technique
Chaimaa, B., & Khadimi, A. E. (2016) · doi:10.1109/icmcs.2016.7905633 · Cited by 109
Wi-Fi based indoor location positioning employing random forest classifier
Jedari, E., Wu, Z., Rashidzadeh, R., & Saif, M. (2015) · International Conference on Indoor Positioning and Indoor Navigation · doi:10.1109/ipin.2015.7346754 · Cited by 107
RSSI-Based Bluetooth Indoor Localization
Wang, Y., Ye, Q., Cheng, J., & Wang, L. (2015) · International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) · doi:10.1109/msn.2015.14 · Cited by 105
Indoor Localization Using 802.11 Time Differences of Arrival
Makki, A., Siddig, A., Saad, M., Cavallaro, J. R., & Bleakley, C. J. (2015) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2015.2506239 · Cited by 102
Model-Based Localization and Tracking Using Bluetooth Low-Energy Beacons
Daniş, F. S., & Cemgil, A. T. (2017) · Sensors · doi:10.3390/s17112484 · Cited by 101
Fingerprinting-assisted UWB-based localization technique for complex indoor environments
Djosic, S. M., Stojanovic, I. Z., Jovanović, M. D., Nikolic, T. R., & Djordjevic, G. L. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114188 · Cited by 94
MetaRadar: Indoor Localization by Reconfigurable Metamaterials
Zhang, H., Hu, J., Zhang, H., Di, B., Bian, K., Han, Z., & Song, L. (2020) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2020.3044603 · Cited by 83
Comparison of 2.4 GHz WiFi FTM- and RSSI-Based Indoor Positioning Methods in Realistic Scenarios
Bullmann, M., Fetzer, T., Ebner, F., Ebner, M., Deinzer, F., & Grzegorzek, M. (2020) · Sensors · doi:10.3390/s20164515 · Cited by 82
A Hybrid Method to Improve the BLE-Based Indoor Positioning in a Dense Bluetooth Environment
Huang, K., He, K., & Xue-cheng, D. (2019) · Sensors · doi:10.3390/s19020424 · Cited by 72
Cyber-Security of Smart Grids: Attacks, Detection, Countermeasure Techniques, and Future Directions
Khoei, T. T., Slimane, H. O., & Kaabouch, N. (2022) · Communications and Network · doi:10.4236/cn.2022.144009 · Cited by 102
A survey: Spoofing attacks in physical layer security
Yılmaz, M. H., & Arslan, H. (2015) · IEEE Conference on Local Computer Networks Workshops (LCN Workshops) · doi:10.1109/lcnw.2015.7365932 · Cited by 69
A received signal strength RFID-based indoor location system
López, Y. Á., Gómez, M. E. D. C., & Las‐Heras, F. (2017) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2017.01.007 · Cited by 68
Recent advances in RF-based passive device-free localisation for indoor applications
Palipana, S., Pietropaoli, B., & Pesch, D. (2017) · Ad Hoc Networks · doi:10.1016/j.adhoc.2017.06.007 · Cited by 67
Hiraguri, T., Shimizu, H., Kimura, T., Matsuda, T., Maruta, K., Takemura, Y., Ohya, T., & Takanashi, T. (2023) · IEEE Access · doi:10.1109/access.2023.3312151 · Cited by 66
Artificial Intelligence for Adaptive and Reconfigurable Antenna Arrays: A Review
Zardi, F., Nayeri, P., Rocca, P., & Haupt, R. L. (2020) · IEEE Antennas and Propagation Magazine · doi:10.1109/map.2020.3036097 · Cited by 64
Comparative analysis of the Bluetooth Low-Energy indoor positioning systems
Čabarkapa, D., Grujic, I., & Pavlović, P. D. (2015) · International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services · doi:10.1109/telsks.2015.7357741 · Cited by 62
Et Tu Alexa? When Commodity WiFi Devices Turn into Adversarial Motion Sensors
Zhu, Y., Xiao, Z., Chen, Y., Li, Z., Liu, M., Zhao, B. Y., & Zheng, H. (2020) · Network and Distributed System Security Symposium · doi:10.14722/ndss.2020.23053 · Cited by 61
Abari, O., Vasisht, D., Katabi, D., & Chandrakasan, A. P. (2015) · ACM Special Interest Group on Data Communication · doi:10.1145/2785956.2787504 · Cited by 60
A Review of Advanced Localization Techniques for Crowdsensing Wireless Sensor Networks
Coluccia, A., & Fascista, A. (2019) · Sensors · doi:10.3390/s19050988 · Cited by 54
Wireless Indoor Localization Using Convolutional Neural Network and Gaussian Process Regression
Zhang, G., Wang, P., Chen, H., & Zhang, L. (2019) · Sensors · doi:10.3390/s19112508 · Cited by 53
Analysis of RSSI Fingerprinting in LoRa Networks
Anjum, M., Khan, M. A., Hassan, S. A., Mahmood, A., & Gidlund, M. (2019) · International Wireless Communications and Mobile Computing Conference (IWCMC) · doi:10.1109/iwcmc.2019.8766468 · Cited by 53
Kunhoth, J., Karkar, A., Al-Maadeed, S. A., & Al-Attiyah, A. A. (2019) · International Journal of Health Geographics · doi:10.1186/s12942-019-0193-9 · Cited by 58
A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G
Isaia, C., & Michaelides, M. P. (2023) · Signals · doi:10.3390/signals4010006 · Cited by 50
Indoor Navigation Using Augmented Reality
Verma, P., Agrawal, K., & Sarasvathi, V. (2020) · International Conference Virtual and Augmented Reality Simulations · doi:10.1145/3385378.3385387 · Cited by 49
RFID Localisation for Internet of Things Smart Homes : A Survey
Alsinglawi, B. S., Elkhodr, M., Nguyễn, Q. V., Gunawardana, U., Maeder, A. J., & Simoff, S. J. (2017) · International journal of Computer Networks & Communications · doi:10.5121/ijcnc.2017.9107 · Cited by 49
Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies
Elgendy, M., Sik-Lanyi, C., & Kelemen, A. (2019) · Applied Sciences · doi:10.3390/app9061061 · Cited by 48
“RFID tags have some benefits: their signals can penetrate walls and obstacles, which cover a wide area, and reuse existing infrastructures, resulting in cost reduction [90].”
BackgroundAlshami, I. H., Ahmad, N. A., Sahibuddin, S., & Firdaus, F. (2017) · Sensors · doi:10.3390/s17081789 · Cited by 46
Indoor positioning systems in hospitals: A scoping review
Wichmann, J. (2022) · Digital Health · doi:10.1177/20552076221081696 · Cited by 45
Ferracuti, N., Norscini, C., Frontoni, E., Gabellini, P., Paolanti, M., & Placidi, V. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2018.11.005 · Cited by 45
Visible Light Positioning and Navigation Using Noise Measurement and Mitigation
Zhuang, Y., Hua, L., Wang, Q., Cao, Y., Gao, Z., Qi, L., Yang, J., & Thompson, J. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2943517 · Cited by 44
ZigBee-based Sensor Network for Indoor Location and Tracking Applications
Álvarez, Y., & Las‐Heras, F. (2016) · IEEE Latin America Transactions · doi:10.1109/tla.2016.7587622 · Cited by 43
Hybrid Indoor Localization Using WiFi and UWB Technologies
Monica, S., & Bergenti, F. (2019) · Electronics · doi:10.3390/electronics8030334 · Cited by 43
LoRaIn: Making a Case for LoRa in Indoor Localization
Islam, B., Islam, M. T., Kaur, J., & Nirjon, S. (2019) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2019.8730767 · Cited by 43
Multi-Sensor Accurate Forklift Location and Tracking Simulation in Industrial Indoor Environments
Barral, V., Suárez-Casal, P., Escudero, C. J., & Garcia-Naya, J. A. (2019) · Electronics · doi:10.3390/electronics8101152 · Cited by 43
A Review on Sensor Network Issues and Robotics
Ryu, J.-H., Muhammad, I., & Reyaz, A. (2015) · Journal of Sensors · doi:10.1155/2015/140217 · Cited by 42
Technological Viability Assessment of Bluetooth Low Energy Technology for Indoor Localization
Topak, F., Pekeriçli, M. K., & Tanyer, A. M. (2018) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0000778 · Cited by 41
An Overview of Local Positioning System: Technologies, Techniques and Applications
Hasan, H. S., Hussein, M. E., Saad, S. M., & Dzahir, M. A. M. (2018) · International Journal of Engineering & Technology · doi:10.14419/ijet.v7i3.25.17459 · Cited by 41
Evaluation of accurate indoor localization systems in industrial environments
Karaagac, A., Haxhibeqiri, J., Ridolfi, M., Joseph, W., Moerman, I., & Hoebeke, J. (2017) · 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa.2017.8247587 · Cited by 40
Ahmed, A. U., Arablouei, R., de Hoog, F., Kusý, B., Jurdak, R., & Bergmann, N. W. (2018) · Sensors · doi:10.3390/s18061753 · Cited by 39
Yaro, A. S., Malý, F., & Pražák, P. (2023) · Sensors · doi:10.3390/s23052545 · Cited by 40
Indoor positioning system using Wi-Fi & Bluetooth Low Energy technology
Varshney, V., Goel, R. K., & Qadeer, M. A. (2016) · IFIP International Conference on Wireless and Optical Communications Networks (WOCN) · doi:10.1109/wocn.2016.7759023 · Cited by 38
Yen, H.-C., Yang, L.-Y. O., & Tsai, Z. (2022) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2022.3194563 · Cited by 38
Robust High Resolution Time of Arrival Estimation for Indoor WLAN Ranging
Makki, A., Siddig, A., & Bleakley, C. J. (2017) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2017.2708478 · Cited by 35
A Novel Indoor Mobile Localization System Based on Optical Camera Communication
Hossan, M. T., Chowdhury, M. Z., Islam, A., & Jang, Y. M. (2018) · Wireless Communications and Mobile Computing · doi:10.1155/2018/9353428 · Cited by 35
Large-Scale Person Detection and Localization using Overhead Fisheye Cameras
Yang, L., Li, L., Xin, X., Sun, Y., Song, Q., & Wang, W. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01827 · Cited by 35
Hailu, T. G., Guo, X., Si, H., Li, L., & Zhang, Y. (2024) · Sensors · doi:10.3390/s24216876 · Cited by 36
Hossen, M. S., Park, Y., & Kim, K. (2015) · Optical Engineering · doi:10.1117/1.oe.54.4.045101 · Cited by 33
Anchor selection for UWB indoor positioning
Albaidhani, A., Morell, A., & Vicario, J. L. (2019) · Transactions on Emerging Telecommunications Technologies · doi:10.1002/ett.3598 · Cited by 33
Optimal access point location algorithm based real measurement for indoor communication
Abdulwahid, M. M., Shareef, O. A., Mosleh, M. F., & Abd-Alhmeed, R. A. (2019) · doi:10.1145/3321289.3321300 · Cited by 33
A New Dataset of People Flow in an Industrial Site with UWB and Motion Capture Systems
Delamare, M., Duval, F., & Boutteau, R. (2020) · Sensors · doi:10.3390/s20164511 · Cited by 33
Optimal Wi-Fi access point placement for RSSI-based indoor localization using genetic algorithm
Alsmady, A., & Awad, F. H. (2017) · International Conference on Information and Communication Systems (ICICS) · doi:10.1109/iacs.2017.7921986 · Cited by 33
Zhang, H., Liu, K., Jin, F., Feng, L., Lee, V. C. S., & Ng, J. K. (2019) · Neural Computing and Applications · doi:10.1007/s00521-018-3961-8 · Cited by 32
Deep Learning-Based Positioning of Visually Impaired People in Indoor Environments
Mahida, P. T., Shahrestani, S. A., & Cheung, H. (2020) · Sensors · doi:10.3390/s20216238 · Cited by 32
A Survey About Real-Time Location Systems in Healthcare Environments
Bazo, R., da Costa, C. A., Seewald, L. A., da Silveira, L. G., Antunes, R. S., Righi, R. D. R., & Rodrigues, V. F. (2021) · Journal of Medical Systems · doi:10.1007/s10916-021-01710-1 · Cited by 31
An energy aware event-driven routing protocol for cognitive radio sensor networks
Tabassum, M., Razzaque, M. A., Miazi, N. S., Hassan, M. M., Alelaiwi, A. A., & Alamri, A. M. (2015) · Wireless Networks · doi:10.1007/s11276-015-1043-8 · Cited by 31
RSS Based Localization Using a New WKNN Approach
Gholoobi, A., & Stavrou, S. (2015) · International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN) · doi:10.1109/cicsyn.2015.15 · Cited by 30
Towards a Decentralized Magnetic Indoor Positioning System
Kasmi, Z., Norrdine, A., & Blankenbach, J. (2015) · Sensors · doi:10.3390/s151229799 · Cited by 30
Guidara, A., Derbel, F., Fersi, G., Bdiri, S., & Jemaa, M. B. (2019) · Ad Hoc Networks · doi:10.1016/j.adhoc.2019.101902 · Cited by 30
Shiwani, M. A., Chico, T., Ciravegna, F., & Mihaylova, L. S. (2023) · Sensors · doi:10.3390/s23125752 · Cited by 37
RESIMA: An Assistive Paradigm to Support Weak People in Indoor Environments
Andò, B., Baglio, S., & Lombardo, C. O. (2014) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2014.2320396 · Cited by 28
Calibration-Free Indoor Positioning Using Crowdsourced Data and Multidimensional Scaling
Zhao, Y., Wong, W., Feng, T., & Garg, H. K. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2957363 · Cited by 27
An efficient indoor localization system based on Affinity Propagation and Support Vector Regression
Abdou, A. S., Mostafa, M. A. A.-A., & Aboshosha, A. M. (2016) · International Conference on Digital Information Processing and Communications · doi:10.1109/icdipc.2016.7470782 · Cited by 27
$HTrack$ : An Efficient Heading-Aided Map Matching for Indoor Localization and Tracking
Wu, Y., Chen, P., Gu, F., Zheng, X., & Shang, J. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2891313 · Cited by 27
Dynamic Wi-Fi fingerprinting indoor positioning system
Costilla-Reyes, O., & Namuduri, K. R. (2014) · International Conference on Indoor Positioning and Indoor Navigation · doi:10.1109/ipin.2014.7275493 · Cited by 26
Indoor localization using Wi-Fi method based on Fingerprinting Technique
Chabbar, H., & Chami, M. (2017) · International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS) · doi:10.1109/wits.2017.7934613 · Cited by 26
Development and Validation of a Distance Measurement System in Metro Lines
Song, H., & Schnieder, E. (2018) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2018.2819799 · Cited by 26
Radio map generation approaches for an RSSI-based indoor positioning system
Sulaiman, B., Tarapiah, S., Natsheh, E. M., Atalla, S., Mansoor, W., & Himeur, Y. (2023) · Systems and Soft Computing · doi:10.1016/j.sasc.2023.200054 · Cited by 25
Implementation of a tracking system based on UWB technology in a retail environment
Contigiani, M., Pietrini, R., Mancini, A., & Zingaretti, P. (2016) · IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications · doi:10.1109/mesa.2016.7587123 · Cited by 25
Positioning Slow-Moving Platforms by UWB Technology in GPS-Challenged Areas
Toth, C. K., Jóźków, G., Koppányi, Z., & Grejner‐Brzezinska, D. A. (2017) · Journal of Surveying Engineering · doi:10.1061/(asce)su.1943-5428.0000231 · Cited by 25
Pannuto, P., Kempke, B. P., Chuo, L.-X., Blaauw, D. T., & Dutta, P. K. (2018) · ACM Transactions on Sensor Networks · doi:10.1145/3185752 · Cited by 25
Wireless Indoor Localization Using Passive RFID Tags
Diallo, A., Lu, Z., & Zhao, X. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.08.031 · Cited by 24
Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility
Rosa, L., Silva, F., & Analide, C. (2021) · Smart Cities · doi:10.3390/smartcities4020046 · Cited by 24
Metadata
- Authors
- Farid, Z., Nordin, R., & Ismail, M.
- Affiliations
- National University of Malaysia (MY)
- Corresponding author
- Farid, Zahid
- Venue
- Journal of Computer Networks and Communications
- Publisher
- Wiley
- Published
- 2013
- Volume
- 2013
- Pages
- 1-12
- ISSN
- 2090-7141 (ISSN-L)
- 2090-715X
- OpenAlex
- W1963996689
- Cited by
- 514
- References
- 40
- Citations by year
- 2026: 11 · 2025: 17 · 2024: 15 · 2023: 18 · 2022: 30 · 2021: 44 · 2020: 59 · 2019: 79 · 2018: 67 · 2017: 79 · 2016: 44 · 2015: 39 · 2014: 12
- FWCI
- 19.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Journal of Computer Networks and Communications (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Greater South Information System
- Funders
- Ministério da Ciência, Tecnologia e Inovação
- Universiti Kebangsaan Malaysia
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Indoor and Outdoor Localization Technologies
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optical Wireless Communication Technologies
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Keywords
- indoor positioning, wireless positioning, location-based services, ubiquitous computing, location estimation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
