Survey of RFID applications in railway industry

Malakar, Bidhan; Roy, Binoy Krishna

doi:10.1109/aces.2014.6807999

Cited by 15 publications

(7 citation statements)

References 8 publications

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“…-the use of Radio-Frequency IDentification (RFID) tags in determining the position of the train in this kind of harsh environments may not be a suitable choice and there are certain limitations as discussed in (Zhang et al 2010); a brief survey of RFID application in railway industry is presented in (Malakar, Roy 2014); -the error related to the GPS or Global Navigation Satellite System (GNSS) receiver may increase whenever the train passes through dense forest, tunnels or GPS dark regions Bajaj et al (2002); -the degraded adhesion between the wheel and rail contacts, which commonly occurs in this kind of hilly routes may affect the performance of tachometer (Wang et al 2014; Government of India 2012).…”

Section: An Overview Of Tcas In Indian Railwaysmentioning

confidence: 99%

Train Localization Using an Adaptive Multisensor Data Fusion Technique

Malakar

Roy

2019

Transport

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This work deals with the development of an adaptive multisensor data fusion technique for the accurate estimation of the trains position and velocity. The proposed technique will work with the Train Collision Avoidance System (TCAS) used in Indian railways during Global Positioning System (GPS) outages. The determination of accurate position of trains is a challenging task for the TCAS during GPS outages. The accuracy of the proposed Volterra Recursive Least Square (VRLS) based adaptive multisensor data fusion technique is evaluated by generating two kinematic profiles for a passenger train running between Silchar-Lumding broad gauge route in Indian railways. The effect of accelerometer bias is also considered during the analysis. It is observed that the developed technique can provide a better estimate of the position and velocity for the TCAS especially during GPS outages and without using any additional railway infrastructure. The simulation results indicate that the proposed technique is superior to the earlier works in terms of achieving better positional accuracy in presence of accelerometer bias.

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Section: An Overview Of Tcas In Indian Railwaysmentioning

confidence: 99%

Train Localization Using an Adaptive Multisensor Data Fusion Technique

Malakar

Roy

2019

Transport

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“…15–18 A particular area of interest is asset management with radio-frequency identification (RFID) systems. 19–22 Although the works contain some references to safe operation, they do not deal with safety or risk management. Another data-hungry domain is condition monitoring: detectors attached to trains and rails are collecting and analysing huge amounts of data that would have been unmanageable until relatively recent advances in technology.…”

Section: Drivers For It Transformation and Big Data Risk Analysismentioning

confidence: 99%

The case for IT transformation and big data for safety risk management on the GB railways

Gulijk

Hughes

Figueres-Esteban

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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This paper presents the case for IT transformation and big data for safety risk management on the GB railways. This paper explains why the interest in data driven safety solutions is very high in the railways by describing the drivers that shape risk management for the railways. A brief overview of research projects in the Big Data Risk Analysis (BDRA) programme supports the case and helps understand the research agenda for the transformation of safety and risk on the GB railways. The drivers and the projects provide insight in the current research needs for the transformation and explains why safety researchers have to broaden their skill set to include digital skills and potentially even programming. The case for IT transformation of risk management systems is compelling and the paper describes just the tip of the iceberg of opportunities opening up for safety analysis that, after all, depends on data.

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“…There are some limitations while using the RFID system in railway environments as discussed in [50]. A brief survey of RFID application in railways is presented in [51]. Semi‐passive tags may be one of the solutions, but again the maintenance cost may increase. (b) The GPS or GNSS receiver accuracy may become poor whenever the train passes through dense forest, tunnels or GPS dark regions [52].…”

Section: Localisation System On Ir – a Brief Overview And Multisensmentioning

confidence: 99%