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NERD—middleware for IoT human machine interfaces

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Abstract

Industrial control systems (ICS), such as smart grid systems, are frequently composed of hundreds of devices distributed over a large geographic area. While mobile applications have been used with good success in managing ICSs, traditional methods of distributing applications (e.g., app stores) are not well suited to the task of discovering, distributing, and building human machine interfaces (HMIs) for ICS, as the highly individualized and often proprietary individual components of ICSs have vastly different interfaces leading to a need to download hundreds of applications. We propose the No Effort Rapid Development (NERD) middleware framework to address the challenges of in-field HMI discovery, provisioning, communication, and co-evolution with related ICSs. Middleware services offer the ability to simplify on-demand HMI distribution and operation of ICSs. NERD leverages existing ICS device-markers (e.g., QR-codes or RFID tags) or Bluetooth low-energy protocols for rapid cyber-physical discovery and provisioning of HMIs in the field. Device-markers and Bluetooth low-energy protocols have a very limited data capacity and transmission speed, and to achieve on-device storage of HMIs, we propose using a compact data-driven domain-specific language that emphasizes data sources and sinks between the HMI and IC.

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Authors and Affiliations

  1. Bradley Department of Electrial and Computer Engineering, Virginia Tech, Blacksburg, VA, USA

    Thaddeus Czauski & Hamilton Turner

  2. Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA

    Jules White

  3. Department of Computer Science, California State Polytechnic University, Pomona, CA, USA

    Yu Sun

  4. Siemens Corporate Research, Siemens, Princeton, NJ, USA

    Sean Eade

Authors
  1. Thaddeus Czauski
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  2. Jules White
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  3. Yu Sun
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  4. Hamilton Turner
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  5. Sean Eade
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Corresponding author

Correspondence to Yu Sun.

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Czauski, T., White, J., Sun, Y. et al. NERD—middleware for IoT human machine interfaces. Ann. Telecommun. 71, 109–119 (2016). https://doi.org/10.1007/s12243-015-0486-3

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  • DOI: https://doi.org/10.1007/s12243-015-0486-3

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