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Reliability Analysis in Cyber-Physical System Using Deep Learning for Smart Cities Industrial IoT Network Node

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AI and IoT for Smart City Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1002))

Abstract

The reliability, availability, security, and survivability analysis of any IoT (Internet-of-things) device is important because it provides all necessary information about the IoT device applications for smart city development to improve its performance of smart cities’ Industrial IoT Network Node. The in-depth knowledge about the IoT Device Applications to be analyzed from a parameters point of view is needed, which inspires the researcher to understand the IoT Device network system very profoundly in terms of Cyber-Physical System (CPS). Until now, less attention is being given to the reliability analysis of smart city-based Industrial IoT devices and Cyber-Physical Systems (CPS). The root failure causes a cyber-attack. The analysis provides the base failure causes, the information about the type of failures and estimates the various reliability parameters. Through this analysis, a better design, a better manufacturing process in Smart Cities, Industrial IoT devices, preventive and corrective maintenance, redundancy, etc., we can easily be recommended for better performance of the device or CPS Using Deep Learning for Smart Cities based Industrial IoT Device (IIOT) Applications. The proposed technique is useful for addressing the system's dependability, design, and development since it can correctly and efficiently analyze the IoT network's reliability.

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Authors and Affiliations

  1. Department of Computer Science Engineering, Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India

    Anand Singh Rajawat

  2. Computer Science and Engineering, KCC Institute of Technology and Management, Greater Noida, Uttar Pradesh, India

    Pradeep Bedi

  3. City University, Petaling Jaya, Malaysia

    S. B. Goyal

  4. Department of Electrical, Electronics and Communication Engineering, Galgotias University, Greater Noida, India

    Rabindra Nath Shaw

  5. School of Engineering and Applied Sciences, The Neotia University, Sarisha, West Bengal, India

    Ankush Ghosh

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  1. Anand Singh Rajawat
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  2. Pradeep Bedi
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  3. S. B. Goyal
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  4. Rabindra Nath Shaw
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  5. Ankush Ghosh
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Milan, Milano, Milano, Italy

    Vincenzo Piuri

  2. Department of Electrical, Electronics and Communication Engineering, School of Engineering, Galgotias University, Greater Noida, India

    Rabindra Nath Shaw

  3. School of Engg and Applied Sciences, The Neotia University, Sarisha, West Bengal, India

    Ankush Ghosh

  4. School of Electrical, Computer and Telecommunications Engineering (SECTE), Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW, Australia

    Rabiul Islam

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Rajawat, A.S., Bedi, P., Goyal, S.B., Shaw, R.N., Ghosh, A. (2022). Reliability Analysis in Cyber-Physical System Using Deep Learning for Smart Cities Industrial IoT Network Node. In: Piuri, V., Shaw, R.N., Ghosh, A., Islam, R. (eds) AI and IoT for Smart City Applications. Studies in Computational Intelligence, vol 1002. Springer, Singapore. https://doi.org/10.1007/978-981-16-7498-3_10

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  • DOI: https://doi.org/10.1007/978-981-16-7498-3_10

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  • Publisher Name: Springer, Singapore

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  • Online ISBN: 978-981-16-7498-3

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