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IoT-Based Multimodal Biometric Identification for Automation Railway Engine Pilot Security System

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 77))

Abstract

Railways are the most convenient mode of transport, but safety precaution is lagging. Train accidents, due to an unknown person operating the engine, will lead to the end of many lives and also loss of railway property. The optimal solution to meet this problem here proposes the effective system of “Automation of Railway Engine Pilot Security System using Multimodal Biometrics Identification” (AREPSS using MBI). Iris and Fingerprint inputs are given by engine pilot from cabin to control room using Internet of things (IoT). In control room, identifications take place by fusing the inputs and then pass the decision signal to automatically start the engine. The common unimodal biometric system can be seen in most of the places due to its popularity. Its reliability has decreased because it requires larger memory footprint, higher operational cost, and it has slower processing speed. So, we are introducing multimodal biometric identification system which uses iris and fingerprint for security reason. The major advantage of this several modality method is that as both modalities utilized the same matcher component, the reminiscence footprint of the system is reduced. High performance is achieved by integrating multiple modalities in user verification and identification causing high dependability and elevated precision. So this procedure improves the safety in engine and thus helps in saving lives and property.

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References

  1. Sujatha, K., Pappa, N.: Combustion monitoring of a water tube boiler using a discriminant radial basis network. ISA Trans. 50, 101–110 (2011)

    Google Scholar 

  2. Jain, A.K., Hong, L., Kulkarni, Y.: A multimodal biometric system using finger prints, face and speech. In: 2nd International Conference Audio and Video-based Biometric Person Authentication, pp.182–187. Washington, March 22–24 (1999)

    Google Scholar 

  3. Jain, A.k., Prabhakar, S., Chen, S.: Combing multiple matchers for a high security fingerprint verification system. 20(11–13), 1371–1379 (1999)

    Google Scholar 

  4. Roli, F., Kittler, J., Fumera, G., Muntoni, D.: An experimental comparison of classifier fusion rules for multimodal personal identity verification system, pp. 76–82 (2002)

    Google Scholar 

  5. Lumini, A., Nanni, L.: When fingerprints are combined with iris—a case study: FVC2004 and CASIA. Inter. J. Net. Sec. 4, 27–34 (Jan 2007)

    Google Scholar 

  6. Nandakumar, K.: MultiBiometric systems: fusion strategies and template security. Ph.D. Thesis, Michigan State University (2008)

    Google Scholar 

  7. Masek, L., Kovesi, P.: MATLAB source code for a biometric identification system based on iris patterns. The School of Computer Science and Software Engineering, the University of Western Australia (2003)

    Google Scholar 

  8. Baig, A., Bouridane, A., Kurugollu, F., Qu, G.: Fingerprint iris fusion based identification system using single hamming distance matcher. Inter. J. Biosci. BioTech 1, 47–57 (Dec 2009)

    Google Scholar 

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Correspondence to K. Sujatha .

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Sujatha, K., Ponmagal, R.S., Senthil Kumar, K., Shoba Rani, R., Dilip, G. (2018). IoT-Based Multimodal Biometric Identification for Automation Railway Engine Pilot Security System. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Computing and Informatics . Smart Innovation, Systems and Technologies, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-10-5544-7_15

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  • DOI: https://doi.org/10.1007/978-981-10-5544-7_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5543-0

  • Online ISBN: 978-981-10-5544-7

  • eBook Packages: EngineeringEngineering (R0)

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