{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T12:47:04Z","timestamp":1781614024166,"version":"3.54.5"},"reference-count":33,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T00:00:00Z","timestamp":1628553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Nowadays, location awareness becomes the key to numerous Internet of Things (IoT) applications. Among the various methods for indoor localisation, received signal strength indicator (RSSI)-based fingerprinting attracts massive attention. However, the RSSI fingerprinting method is susceptible to lower accuracies because of the disturbance triggered by various factors from the indoors that influence the link quality of radio signals. Localisation using body-mounted wearable devices introduces an additional source of error when calculating the RSSI, leading to the deterioration of localisation performance. The broad aim of this study is to mitigate the user\u2019s body shadowing effect on RSSI to improve localisation accuracy. Firstly, this study examines the effect of the user\u2019s body on RSSI. Then, an angle estimation method is proposed by leveraging the concept of landmark. For precise identification of landmarks, an inertial measurement unit (IMU)-aided decision tree-based motion mode classifier is implemented. After that, a compensation model is proposed to correct the RSSI. Finally, the unknown location is estimated using the nearest neighbour method. Results demonstrated that the proposed system can significantly improve the localisation accuracy, where a median localisation accuracy of 1.46 m is achieved after compensating the body effect, which is 2.68 m before the compensation using the classical K-nearest neighbour method. Moreover, the proposed system noticeably outperformed others when comparing its performance with two other related works. The median accuracy is further improved to 0.74 m by applying a proposed weighted K-nearest neighbour algorithm.<\/jats:p>","DOI":"10.3390\/s21165405","type":"journal-article","created":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T08:57:14Z","timestamp":1628585834000},"page":"5405","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Landmark-Assisted Compensation of User\u2019s Body Shadowing on RSSI for Improved Indoor Localisation with Chest-Mounted Wearable Device"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0310-4078","authenticated-orcid":false,"given":"Md Abdulla Al","family":"Mamun","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Systems Engineering, Clayton Campus, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4301-8484","authenticated-orcid":false,"given":"David Vera","family":"Anaya","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Systems Engineering, Clayton Campus, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5011-5004","authenticated-orcid":false,"given":"Fan","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Systems Engineering, Clayton Campus, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mehmet Rasit","family":"Yuce","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Systems Engineering, Clayton Campus, Monash University, Melbourne, VIC 3800, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4035","DOI":"10.1109\/JIOT.2020.3019199","article-title":"Toward Location-Enabled IoT (LE-IoT): IoT Positioning Techniques, Error Sources, and Error Mitigation","volume":"8","author":"Li","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wang, H., Sen, S., Elgohary, A., Farid, M., Youssef, M., and Choudhury, R.R. (2012, January 25\u201329). No need to war-drive: Unsupervised indoor localization. Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services, Low Wood Bay, UK.","DOI":"10.1145\/2307636.2307655"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Schmitt, S., Adler, S., and Kyas, M. (2014, January 27\u201330). The effects of human body shadowing in RF-based indoor localization. Proceedings of the 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, Korea.","DOI":"10.1109\/IPIN.2014.7275497"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"101022","DOI":"10.1016\/j.pmcj.2019.05.003","article-title":"Improving ambient FM indoor localization using multipath-induced amplitude modulation effect: A year-long experiment","volume":"58","author":"Popleteev","year":"2019","journal-title":"Pervasive Mob. Comput."},{"key":"ref_5","unstructured":"Bahl, P., and Padmanabhan, V.N. (2000, January 26\u201330). RADAR: An in-building RF-based user location and tracking system. Proceedings of the IEEE INFOCOM 2000, Tel Aviv, Israel."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"8343","DOI":"10.1109\/JIOT.2020.2989501","article-title":"Landmark Graph-Based Indoor Localization","volume":"7","author":"Gu","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Xu, C., Firner, B., Moore, R.S., Zhang, Y., Trappe, W., Howard, R., Zhang, F., and An, N. (2013, January 8\u201311). SCPL: Indoor device-free multi-subject counting and localization using radio signal strength. Proceedings of the 12th International Conference on Information Processing in Sensor Networks, Philadelphia, PA, USA.","DOI":"10.1145\/2461381.2461394"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1049\/cmu2.12043","article-title":"DFC: Device-free human counting through WiFi fine-grained subcarrier information","volume":"15","author":"Jeong","year":"2021","journal-title":"IET Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1109\/TMC.2016.2557792","article-title":"WiFall: Device-Free Fall Detection by Wireless Networks","volume":"16","author":"Wang","year":"2017","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1109\/JIOT.2016.2624800","article-title":"Device-Free RF Human Body Fall Detection and Localization in Industrial Workplaces","volume":"4","author":"Kianoush","year":"2017","journal-title":"IEEE Internet Things J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6258","DOI":"10.1109\/TVT.2016.2635161","article-title":"Device-Free Wireless Localization and Activity Recognition: A Deep Learning Approach","volume":"66","author":"Wang","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1145\/3431832.3431840","article-title":"Coronavirus contact tracing: Evaluating the potential of using bluetooth received signal strength for proximity detection","volume":"50","author":"Leith","year":"2020","journal-title":"SIGCOMM Comput. Commun. Rev."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Cully, W.P.L., Cotton, S.L., Scanlon, W.G., and McQuiston, J.B. (2012, January 1\u20134). Body shadowing mitigation using differentiated LOS\/NLOS channel models for RSSI-based Monte Carlo personnel localization. Proceedings of the 2012 IEEE Wireless Communications and Networking Conference (WCNC), Paris, France.","DOI":"10.1109\/WCNC.2012.6214458"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"King, T., Kopf, S., Haenselmann, T., Lubberger, C., and Effelsberg, W. (2006, January 29). COMPASS: A probabilistic indoor positioning system based on 802.11 and digital compasses. Proceedings of the 1st International Workshop on Wireless Network Testbeds, Experimental Evaluation & Characterization, Los Angeles, CA, USA.","DOI":"10.1145\/1160987.1160995"},{"key":"ref_15","first-page":"959140","article-title":"Human-Induced Effects on RSS Ranging Measurements for Cooperative Positioning","volume":"2012","author":"Pelosi","year":"2012","journal-title":"Int. J. Navig. Obs."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Trogh, J., Plets, D., Martens, L., and Joseph, W. (2015, January 6\u201310). Improved Tracking by Mitigating the Influence of the Human Body. Proceedings of the 2015 IEEE Globecom Workshops (GC Wkshps), San Diego, CA, USA.","DOI":"10.1109\/GLOCOMW.2015.7414013"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2105","DOI":"10.1109\/JSEN.2015.2508002","article-title":"Enhanced Indoor Location Tracking Through Body Shadowing Compensation","volume":"16","author":"Trogh","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_18","first-page":"117","article-title":"Influence of human body on Radio Signal Strength Indicator readings in indoor positioning systems","volume":"19","author":"Zinkiewicz","year":"2016","journal-title":"Tech. Sci. Univ. Warm. Mazury Olszt."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1550147718785885","DOI":"10.1177\/1550147718785885","article-title":"A novel method of adaptive weighted K-nearest neighbor fingerprint indoor positioning considering user\u2019s orientation","volume":"14","author":"Bi","year":"2018","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Deng, Z., Fu, X., and Wang, H. (2018). An IMU-Aided Body-Shadowing Error Compensation Method for Indoor Bluetooth Positioning. Sensors, 18.","DOI":"10.3390\/s18010304"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1186\/1687-1499-2012-123","article-title":"Coverage prediction and optimization algorithms for indoor environments","volume":"2012","author":"Plets","year":"2012","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Wang, J., and Wang, Q. (2013). Body Area Communications: Channel Modeling, Communication Systems, and EMC, John Wiley & Sons.","DOI":"10.1002\/9781118188491"},{"key":"ref_23","unstructured":"Hall, P.S., and Hao, Y. (2012). Antennas and Propagation for Body-Centric Wireless Communications, Artech House."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Harmuth, H.F., Hussain, M.G., and Boules, R.N. (1999). Electromagnetic Signals: Reflection, Focusing, Distortion, and Their Practical Applications, Springer.","DOI":"10.1007\/978-1-4615-4849-2"},{"key":"ref_25","unstructured":"Mamun, M.A.A., Anaya, D.V., Wu, F., Redout\u00e9, J.M., and Yuce, M.R. (2019, January 13\u201315). Radio Map Building with IEEE 802.15.4 for Indoor Localization Applications. Proceedings of the 2019 IEEE International Conference on Industrial Technology (ICIT), Melbourne, Australia."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1109\/TIM.2011.2159317","article-title":"Accurate Pedestrian Indoor Navigation by Tightly Coupling Foot-Mounted IMU and RFID Measurements","volume":"61","author":"Ruiz","year":"2012","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Antigny, N., Servi\u00e8res, M., and Renaudin, V. (2017, January 18\u201321). Pedestrian track estimation with handheld monocular camera and inertial-magnetic sensor for urban augmented reality. Proceedings of the 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Sapporo, Japan.","DOI":"10.1109\/IPIN.2017.8115934"},{"key":"ref_28","unstructured":"Zhang, Y., Hu, W., Xu, W., Wen, H., and Chou, C.T. (2016, January 15\u201317). NaviGlass: Indoor Localisation Using Smart Glasses. Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks, Graz, Austria."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1539","DOI":"10.3390\/s130201539","article-title":"Motion Mode Recognition and Step Detection Algorithms for Mobile Phone Users","volume":"13","author":"Susi","year":"2013","journal-title":"Sensors"},{"key":"ref_30","first-page":"9497151","article-title":"Registration and Analysis of Acceleration Data to Recognize Physical Activity","volume":"2019","author":"Majkowski","year":"2019","journal-title":"J. Healthc. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1689239.1689243","article-title":"Using mobile phones to determine transportation modes","volume":"6","author":"Reddy","year":"2010","journal-title":"ACM Trans. Sen. Netw."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"8507","DOI":"10.3390\/s120708507","article-title":"Step Length Estimation Using Handheld Inertial Sensors","volume":"12","author":"Renaudin","year":"2012","journal-title":"Sensors"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1016\/j.comnet.2004.09.004","article-title":"Statistical learning theory for location fingerprinting in wireless LANs","volume":"47","author":"Brunato","year":"2005","journal-title":"Comput. Netw."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/16\/5405\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:43:35Z","timestamp":1760165015000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/16\/5405"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,10]]},"references-count":33,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["s21165405"],"URL":"https:\/\/doi.org\/10.3390\/s21165405","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,10]]}}}