skip to main content
10.1145/3274783.3275179acmconferencesArticle/Chapter ViewAbstractPublication PagessensysConference Proceedingsconference-collections
short-paper

IoT for the Power Industry: Recent Advances and Future Directions with Pavatar

Authors Info & Claims
Published:04 November 2018Publication History

ABSTRACT

The development of Internet-of-Things (IoT) technologies in recent years brings us unprecedented opportunities for innovations in the power industry. This demo abstract introduces our research and practice with Pavatar - IoT for the power industry. Pavatar includes a series of system deployments in the core sections of Global Energy Internet (GEI), for the purposes of automatic surveillance and remote diagnosis of ultra-high-voltage converter stations (UHVCSs). Pavatar incorporates technologies like lower-power or battery-free sensing, cross-technology communication, edge computing, machine learning, and enhances the user experience with 3D virtual reality. The deployed system significantly reduces the manpower cost and enhances the operational efficiency of the UHVCS.

References

  1. Zhenya Liu. Global energy interconnection. Academic Press, 2015.Google ScholarGoogle Scholar
  2. Eric J. Tuegel, Anthony R. Ingraffea, Thomas G. Eason, and S. Michael Spottswood. Reengineering aircraft structural life prediction using a digital twin. International Journal of Aerospace Engineering, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  3. Yuan He, Junchen Guo, and Xiaolong Zheng. From surveillance to digital twin: Challenges and recent advances of signal processing for industrial iot. IEEE Signal Processing Magazine, 2018.Google ScholarGoogle Scholar

Index Terms

  1. IoT for the Power Industry: Recent Advances and Future Directions with Pavatar

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        SenSys '18: Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems
        November 2018
        449 pages
        ISBN:9781450359528
        DOI:10.1145/3274783

        Copyright © 2018 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 4 November 2018

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • short-paper
        • Research
        • Refereed limited

        Acceptance Rates

        Overall Acceptance Rate174of867submissions,20%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader