The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Wireless Sensor Networks for Condition Monitoring in the Railway Industry: A Survey
Open accessAbstract
In recent years, the range of sensing technologies has expanded rapidly, whereas sensor devices have become cheaper. This has led to a rapid expansion in condition monitoring of systems, structures, vehicles, and machinery using sensors. Key factors are the recent advances in networking technologies such as wireless communication and mobile ad hoc networking coupled with the technology to integrate devices. Wireless sensor networks (WSNs) can be used for monitoring the railway infrastructure such as bridges, rail tracks, track beds, and track equipment along with vehicle health monitoring such as chassis, bogies, wheels, and wagons. Condition monitoring reduces human inspection requirements through automated monitoring, reduces maintenance through detecting faults before they escalate, and improves safety and reliability. This is vital for the development, upgrading, and expansion of railway networks. This paper surveys these wireless sensors network technology for monitoring in the railway industry for analyzing systems, structures, vehicles, and machinery. This paper focuses on practical engineering solutions, principally, which sensor devices are used and what they are used for; and the identification of sensor configurations and network topologies. It identifies their respective motivations and distinguishes their advantages and disadvantages in a comparative review.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An introduction to multisensor data fusion
Hall, D. L., & Llinas, J. (1997) · Proceedings of the IEEE · doi:10.1109/5.554205 · Cited by 2,629
Challenges Toward Wireless Communications for High-Speed Railway
Ai, B., Briso-Rodriguez, C., Cheng, X., Kurner, T., Zhong, Z.-D., Guan, K., He, R.-S., Xiong, L., Matolak, D. W., & Michelson, D. G. (2014) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2014.2310771 · Cited by 498
Research works printed but not linked: 136
- 10.1109/JSEN.2008.926519 · doi:10.1109/jsen.2008.926519
- coraluppi, 0, Multi-stage data fusion and the MSTWG TNO datasets, Proc 12th Int Conf Inform Fusion, 1552
- cheekiralla, 0, Wireless sensor network-based tunnel monitoring, Proc 1st Workshop Real-World WSN Poster Session
- 10.1145/1378600.1378603 · DOI
- 10.1109/IMIS.2012.51 · DOI
- carrascal, 0, Unsupervised methods for anomalies detection through intelligent monitoring systems, Proc 4th Int Conf Hybrid Artif Intell Syst, 137
- 10.1109/JPROC.2003.814918 · DOI · Paper page
- 10.1049/ic:20060048 · doi:10.1049/ic:20060048
- chen, 2013, RAISE: RAIlway infrastructure health monitoring using wireless sensor networks, Sensor Systems and Software, 122, 143, 10.1007/978-3-319-04166-7_10 · DOI
- 10.1109/SUTC.2008.89 · doi:10.1109/sutc.2008.89
- bukova, 2007, Smart dust in transport services, Railway Transp Logist, 3, 39
- buggy, 2011, Intelligent infrastructure for rail and tramways using optical fibre sensors, IET Railway Young Professionals' Best Paper Competition
- cardenas, 0, Attacks against process control systems: Risk assessment, detection, response, Proc 6th ACM Symp Inf Comput Commun Security, 355
- bocciolone, 0, An application of FBG accelerometers for monitoring pantographs of underground trains, Proc SPIE 4th Eur Workshop Opt Fibre Sens, 765341-1
- bollas, 2010, Acoustic emission inspection of rail wheels, J Acoust Emission, 28, 215
- 10.1109/JSEN.2009.2020244 · doi:10.1109/jsen.2009.2020244
- 10.1080/00423110701426690 · DOI · Paper page
- brickle, 2008, Identification of Existing and New Technologies for Wheelset Condition Monitoring
- pourghodrat, 2011, Energy Harvesting Systems Design for Railroad Safety
- 10.1016/j.ndteint.2004.02.001 · doi:10.1016/j.ndteint.2004.02.001
- pascale, 0, A wireless sensor network architecture for railway signalling, Proc 9th Italian Netw Workshop, 1
- 10.1243/0954409011531549 · doi:10.1243/0954409011531549
- 10.1109/EMEIT.2011.6023638 · doi:10.1109/emeit.2011.6023638
- ghosh, 2011, Development of fishplate tampering detection system for railway security based on wireless sensor network, Int J Comput Appl, 2, 29
- hay, 2007, Wireless Remote Structural Integrity Monitoring for Railway Bridges
- hay, 0, Transforming bridge monitoring from time-based to predictive maintenance using acoustic emission MEMS sensors and artificial intelligence, Proc 7th World Congr Railway Res
- han, 2006, Data mining: Concepts and techniques, Morgan Kaufmann Series in Data Management Systems
- grudén, 0, Reliability experiments for wireless sensor networks in train environment, Proc Eur Wireless Technol Conf, 37
- 10.12989/sss.2010.6.3.197 · DOI
- grosse, 0, Wireless acoustic emission sensor networks for structural health monitoring in civil engineering, Proc Eur Conf Non-Destructive Testing, 1
- goodall, 2006, concepts and techniques for railway condition monitoring, 2006 IET International Conference On Railway Condition Monitoring IET, 90, 10.1049/ic:20060050 · DOI
- 10.1109/COGSIMA.2011.5753459 · doi:10.1109/cogsima.2011.5753459
- 10.1016/j.adhoc.2003.09.010 · DOI · Paper page
- 10.1109/MCOM.2002.1024422 · DOI · Paper page
- 10.1016/S1389-1286(01)00302-4 · DOI · Paper page
- aw, 2007, Low cost monitoring system to diagnose problematic rail bed case study of mud pumping site
- fukuta, 0, Possibility of sensor network applying for railway signal system, Proc 5th Int Conf Network Sensing Syst, 170
- anastasopoulos, 0, Acoustic emission on-line inspection of rail wheels, Proc 29th Eur Conf Acoust Emission Testing, 1
- balas, 2010, World knowledge for sensors and estimators by models and internal models, J Intell Fuzzy Syst, 21, 79, 10.3233/IFS-2010-0437 · doi:10.3233/ifs-2010-0437
- feltrin, 0, Wireless sensor networks: A monitoring tool for improving remaining lifetime estimation, Civil Struct Health Monitoring Workshop, 1
- 10.1109/MPRV.2002.993145 · DOI · Paper page
- 10.1109/ESARS.2010.5665249 · DOI
- 10.1109/JSEN.2011.2135848 · doi:10.1109/jsen.2011.2135848
- 10.1049/ic:20060044 · doi:10.1049/ic:20060044
- den buurman, 0, Quo Vadis: Review of the contribution of a weigh-in-motion system to optimising railway performance, Proc 7th World Congr Railway Res, 1
- 10.1049/ic:20060052 · doi:10.1049/ic:20060052
- dierkx, 2009, The Smarter Railroad Transport R&D for Innovation Project Report
- 10.1155/2012/409048 · doi:10.1155/2012/409048
- 10.1177/09544097JRRT406 · doi:10.1177/09544097jrrt406
- waki, 2010, Monitoring of contact line equipment by trains in operation, JR East Tech Rev East Japan Railway Culture Found, 17, 11
- 10.5772/35205 · doi:10.5772/35205
- 10.1109/JSEN.2009.2019315 · doi:10.1109/jsen.2009.2019315
- 10.1155/2012/365165 · DOI
- 10.1117/12.619430 · doi:10.1117/12.619430
- lagnebäck, 2007, Evaluation of wayside condition monitoring technologies for condition-based maintenance of railway vehicles
- wilkinson, 2013, Long range inspection and condition monitoring of rails using guided waves, Proc 12th Int Conf Exhib Railway Eng
- krüger, 2007, Sustainable Bridges Technical Report on Wireless Sensor Networks using MEMS for Acoustic Emission Analysis including other Monitoring Tasks
- 10.1109/PIMRC.2009.5449796 · doi:10.1109/pimrc.2009.5449796
- 10.1088/0964-1726/20/8/085014 · DOI
- liu, 0, Relay node placement for wireless sensor networks deployed in tunnels, Proc IEEE 6th Int Conf Wireless Mobile Comput Netw Commun, 144
- 10.1007/978-3-642-27963-8_29 · doi:10.1007/978-3-642-27963-8_29
- 10.1016/j.conengprac.2006.02.021 · DOI
- 10.1049/ic:19980986 · doi:10.1049/ic:19980986
- 10.1016/j.comnet.2008.04.002 · DOI · Paper page
- 10.1109/RRCON.2006.215319 · DOI
- 10.1109/JLT.2011.2106479 · DOI · Paper page
- 10.1061/(ASCE)1090-0241(2006)132:10(1360) · doi:10.1061/(asce)1090-0241(2006)132:10(1360
- lorestani, 2012, Monitoring rail traffic using Wireless Sensor Network (WSN), Int J Comput Sci Eng Technol, 2, 1280
- zhou, 0, Remote condition monitoring for railway point machine, Proc ASME/IEEE Joint Railroad Conf, 103
- yilmazer, 0, The structural health condition monitoring of rail steel using acoustic emission techniques, Proc 51st Annu Conf NDT, 1
- zöller, 2011, Efficient real-time monitoring of multimodal transports with wireless sensor networks, Proc 36th IEEE Conf Local Comput Netw
- 10.1109/TCOM.1980.1094702 · DOI · Paper page
- hendry, 2012, The geomechanical behaviour of peat foundations below rail-track structures
- 10.1680/cien.2009.162.3.136 · DOI
- hodge, 2011, Outlier and Anomaly Detection A Survey of Outlier and Anomaly Detection Methods
- 10.2219/rtriqr.47.78 · doi:10.2219/rtriqr.47.78
- ishida, 2004, New train control and information services utilizing broadband networks, Hitachi Rev, 53, 21
- 10.1016/j.sna.2008.07.014 · doi:10.1016/j.sna.2008.07.014
- 10.1007/978-3-642-23583-2_4 · doi:10.1007/978-3-642-23583-2_4
- 10.1088/0964-1726/20/3/035016 · DOI
- konrad, 0, Influence of repeated heavy axle loading on peat bearing capacity, Proc 60th Can Geotech Conf, 1551
- 10.1109/MVT.2008.927489 · doi:10.1109/mvt.2008.927489
- 10.1109/SSD.2012.6198111 · doi:10.1109/ssd.2012.6198111
- 10.1109/.2006.1629461 · DOI
- 10.1109/MMW.2003.1266068 · doi:10.1109/mmw.2003.1266068
- 10.1088/1742-6596/364/1/012016 · doi:10.1088/1742-6596/364/1/012016
- salaberria, 0, Wireless communications architecture for ‘train-to-earth’ communication in the railway industry, Proc 10th Int Work-Conf Artif Neural Netw, 626
- 10.1109/ISSE.2008.5276628 · doi:10.1109/isse.2008.5276628
- sala, 2009, Wireless transmission system for a railway bridge subject to structural health monitoring, Diagnostyka, 50, 69
- 10.1109/RRCON.2000.869993 · doi:10.1109/rrcon.2000.869993
- 10.1109/ICSensT.2011.6137033 · doi:10.1109/icsenst.2011.6137033
- nelson, 0, Power harvesting for railroad track health monitoring using piezoelectric and inductive devices, Proc SPIE Active Passive Smart Struct Integrated Syst, 6928, 1
- 10.1147/JRD.2009.5429019 · doi:10.1147/jrd.2009.5429019
- 10.1088/1742-6596/305/1/012024 · DOI
- 10.1007/978-3-642-12607-9_6 · DOI
- 10.1016/j.engstruct.2010.02.020 · doi:10.1016/j.engstruct.2010.02.020
- 10.1016/j.eswa.2010.12.014 · DOI
- rabatel, 2009, SO_MAD: SensOr mining for anomaly detection in railway data, Adv Data Mining Appl Theor Aspects LNCS, 5633, 191, 10.1007/978-3-642-03067-3_16 · DOI
- 10.1002/stc.416 · doi:10.1002/stc.416
- 10.1109/AUSWIRELESS.2007.74 · DOI
- schwarzenbach, 2010, Mapping the remote condition monitoring architecture—Core report
- 10.1049/ic:20060034 · DOI
- palo, 2012, Condition Monitoring of Railway Vehicles A Study on Wheel Condition for Heavy Haul Rolling Stock
- nuffer, 0, Application of piezoelectric materials in transportation industry, Proc Global Symp Innovative Solutions Advancement Transp Ind, 1
- 10.1049/ic:20060065 · doi:10.1049/ic:20060065
- 10.1177/1475921705049764 · doi:10.1177/1475921705049764
- 10.1016/j.comcom.2006.12.020 · DOI · Paper page
- 10.1145/1460412.1460418 · doi:10.1145/1460412.1460418
- basagni, 0, Controlled vs. uncontrolled mobility in wireless sensor networks: Some performance insights, Proc IEEE 66th Veh Technol Conf, 269
- baum, 0, Early warning of landslides for rail traffic between Seattle and Everett, Proc Landslide Risk Manage, 731
- 10.1049/ic:20060041 · doi:10.1049/ic:20060041
- 2005, Gotcha—wheel flat detection and axle load measurement system
- 10.1016/j.ymssp.2005.12.012 · DOI
- 10.1109/ITSC.2005.1520059 · doi:10.1109/itsc.2005.1520059
- stoneburner, 2002, Risk Management Guide for Information Technology Systems, 800
- 10.12989/sss.2010.6.5_6.619 · DOI
- mahlknecht, 0, On architecture of low power wireless sensor networks for container tracking and monitoring applications, Proc 5th IEEE Int Conf Ind Inf, 353
- 10.1109/DCOSS.2013.38 · DOI
- 10.1080/00423114.2012.669130 · DOI
- tam, 2007, Utilization of fiber optic Bragg Grating sensing systems for health monitoring in railway applications, Struct Health Monit Quantification Validat Implement, 1?2, 1824
- bischoff, 0, Event-based strain monitoring on a railway bridge with a wireless sensor network, Proc 4th Int Conf Struct Health Monitor Intell Infrastructure, 1
- 10.1016/j.engfailanal.2007.03.005 · doi:10.1016/j.engfailanal.2007.03.005
- 10.1109/TITS.2012.2227315 · DOI
- 10.1109/TITS.2010.2041057 · doi:10.1109/tits.2010.2041057
- 10.1016/j.adhoc.2010.04.002 · DOI
- 10.1177/0583102406061499 · DOI · Paper page
- 10.1109/WICOM.2010.5601106 · doi:10.1109/wicom.2010.5601106
- 10.1109/WAINA.2009.113 · doi:10.1109/waina.2009.113
- 10.1115/JRC2010-36243 · doi:10.1115/jrc2010-36243
- 10.1016/j.ymssp.2009.06.007 · doi:10.1016/j.ymssp.2009.06.007
- 10.1145/565702.565708 · DOI · Paper page
- 10.1016/B978-075067729-5/50062-8 · doi:10.1016/b978-075067729-5/50062-8
- mcconnell, 0, A distributed approach for prediction in sensor networks, Proc 1st Int Workshop Data Mining Sens Netw a, 28
- 10.1111/j.1475-1305.2005.00202.x · doi:10.1111/j.1475-1305.2005.00202.x
- 10.1243/09544097JRRT154 · doi:10.1243/09544097jrrt154
- 10.1145/1824766.1824771 · doi:10.1145/1824766.1824771
Cited by
Data Mining and Analytics in the Process Industry: The Role of Machine Learning
Ge, Z., Song, Z., Ding, S. X., & Huang, B. (2017) · IEEE Access · doi:10.1109/access.2017.2756872 · Cited by 922
Challenges, Applications, and Future of Wireless Sensors in Internet of Things: A Review
Jamshed, M. A., Ali, K., Abbasi, Q. H., Imran, M. A., & Ur-Rehman, M. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3148128 · Cited by 495
Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways
Fraga-Lamas, P., Fernández-Caramés, T., & Castedo, L. (2017) · Sensors · doi:10.3390/s17061457 · Cited by 267
Security and Privacy Issues in Intelligent Transportation Systems: Classification and Challenges
Hahn, D., Munir, A., & Behzadan, V. (2021) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2019.2898973 · Cited by 183
A carbon nanotube based NTC thermistor using additive print manufacturing processes
Turkani, V. S., Maddipatla, D., Narakathu, B. B., Bazuin, B. J., & Atashbar, M. Z. (2018) · Sensors and Actuators A: Physical · doi:10.1016/j.sna.2018.05.042 · Cited by 145
Metadata
- Authors
- Hodge, V. J., O'Keefe, S., Weeks, M., & Moulds, A.
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2015-06
- Volume
- 16
- Issue
- 3
- Pages
- 1088-1106
- ISSN
- 1524-9050 (ISSN-L)
- 1558-0016
- OpenAlex
- W2000618191
- Cited by
- 530
- References
- 2
- FWCI
- 54.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- Funders
- the U.K. Engineering and Physical Sciences Research Council (EP/J012343/1)
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Wireless Sensor Networks for Condition Monitoring in the Railway Industry: A Survey. https://app.cochat.ai/papers/10.1109/tits.2014.2366512
- The paper
- Hodge, V. J., O'Keefe, S., Weeks, M., & Moulds, A. (2015). Wireless Sensor Networks for Condition Monitoring in the Railway Industry: A Survey. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2014.2366512
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.