Advertisement

An Experimental Study on the Integration of Embedded Devices into Private Manufacturing Cloud Infrastructures

  • Silviu RăileanuEmail author
  • Florin Anton
  • Theodor Borangiu
  • Octavian Morariu
  • Iulia Iacob
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 803)

Abstract

The paper presents a solution for data collection from devices embedded on industrial resources. The proposed architecture is validated using an industrial robot from Omron. Since not all devices that acquire electrical signals from sensors and transmit them in centralized environments (e.g., Cloud) have advanced processing capabilities, the creation of an aggregation node that concentrates data from different types of sources and sends it to the Cloud database is proposed. The data is collected, aggregated and uploaded to the private cloud platform for centralized manufacturing control tasks (product scheduling, resource allocation, monitoring and diagnosis). Experimental results are reported.

Keywords

Edge computing Distributed intelligence Intelligent devices Cloud 

Notes

Acknowledgement

This research work has been partially supported by the IBM Faculty Awards 2016 Project: Big Data, Analytics and Cloud for Digital Transformation on Manufacturing – DTM, period of execution 2016-2018.

References

  1. 1.
    Evans, D.: The Internet of Things. How the Next Evolution of the Internet is Changing Everything, CISCO white paper (2011)Google Scholar
  2. 2.
    Rose, K., Eldridge, S., Chapin, L.: The Internet of Things: An Overview, Understanding Issues and Challenges of a More Connected World. The Internet Society (ISOC), Reston (2015)Google Scholar
  3. 3.
    Al-Osta, M., Ahmed, B., Abdelouahed, G.: A lightweight semantic web-based approach for data annotation on IoT gateways. Procedia Comput. Sci. 113, 186–193 (2017).  https://doi.org/10.1016/j.procs.2017.08.339CrossRefGoogle Scholar
  4. 4.
    Ai, Y., Peng, M., Zhang, K.: Edge cloud computing technologies for internet of things: a primer. Digit. Commun. Netw. (2017).  https://doi.org/10.1016/j.dcan.2017.07.001CrossRefGoogle Scholar
  5. 5.
  6. 6.
    Takiishi, K., Tazaki, K., Fabre, S.: Edge Computing for Improved Digital Business Networks, Published: 21 October 2015 by Gartner, ID: G00291619 (2015). https://www.gartner.com/doc/3155018/edge-computing-improved-digital-business
  7. 7.
    FogHorn Systems: Bringing the Power of Big Data to the Edge (2017). https://www.foghorn.io/technology/
  8. 8.
    Barbon, G., Margolis, M., Palumbo, F., Raimondi, F., Weldin, N.: Taking Arduino to the Internet of Things: the ASIP programming model. Comput. Commun. 89–90, 128–140 (2016)CrossRefGoogle Scholar
  9. 9.
    Desai, N.: What is an IoT Gateway and How Do I Keep It Secure? Global Sign Internet GMO Group (2016). https://www.globalsign.com/en/blog/what-is-an-iot-gateway-device/
  10. 10.
    Al-Osta, M., Ahmed, B., Abdelouahed, G.: A lightweight semantic web-based approach for data annotation on IoT gateways. In: EUSPN 2017 (2017). ScienceDirect, Procedia Computer Science, vol. 113, pp. 186–193Google Scholar
  11. 11.
    Kang, B., Choo, H.: An experimental study of a reliable IoT gateway. ICT Express (2017). http://dx.doi.org/10.1016/j.icte.2017.04.002
  12. 12.
    Răileanu, S., Anton, F., Borangiu, T.: High availability cloud manufacturing system integrating distributed MES agents. In: Borangiu, T., Trentesaux, D., Thomas, A., Leitao, P., Barata, J. (eds.) Service Orientation in Holonic and Multi-Agent Manufacturing. Proceedings of SOHOMA 2016. Studies in Computational Intelligence, vol. 694, Chap. 2, pp. 11–23 (2016).  https://doi.org/10.1007/978-3-319-51100-9_2
  13. 13.
    Gloria, A., Cercasa, F., Souto, N.: Design and implementation of an IoT gateway to create smart environments. In: Proceedings of the 8th International Conference on Ambient Systems, Networks and Technologies (ANT 2017) (2017).  https://doi.org/10.1016/j.procs.2017.05.343
  14. 14.
  15. 15.
    Automation Control Environment (ACE). http://www.ia.omron.com/products/family/3521/lineup.html. Consulted in March 2018
  16. 16.
    eCobra SCARA Robot. https://industrial.omron.us/en/products/ecobra. Consulted in March 2018
  17. 17.
    Främling, K., Kubler, S., Buda, A.: Universal messaging standards for the IoT from a lifecycle management perspective. IEEE Internet Things J. 1(4), 319–327. ISSN: 2327-4662 (2014)Google Scholar
  18. 18.
    Forouzan, B.: TCP/IP Protocol Suite, 2nd edn. McGraw-Hill, New York (2003). ISBN 0-07-246060-1Google Scholar
  19. 19.
    Kubler, S., Madhikermi, M., Buda, A., Främling, K.: QLM messaging standards: introduction and comparison with existing messaging protocols. In: Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics. Studies in Computational Intelligence, vol. 544. Springer, Berlin (2014). ISBN 978-3-319-04734-8Google Scholar
  20. 20.
    Eclipse Mosquitto, An open source MQTT broker. https://mosquitto.org/. Consulted in March 2018
  21. 21.
    Eclipse Paho, open-source client implementations of MQTT. https://www.eclipse.org/paho/. Consulted in March 2018
  22. 22.
    https://pubsubclient.knolleary.net/. Consulted in March 2018

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Silviu Răileanu
    • 1
    Email author
  • Florin Anton
    • 1
  • Theodor Borangiu
    • 1
  • Octavian Morariu
    • 1
  • Iulia Iacob
    • 1
  1. 1.Department of Automation and Applied InformaticsUniversity Politehnica of BucharestBucharestRomania

Personalised recommendations