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An IoT Expert System Shell in Block-Chain Technology with ELM as Inference Engine

Author

Listed:
  • Ricardo Carreño

    (Universidad del Istmo, Campus Tehuantepec, Santo Domingo Tehuantepec, Oaxaca, México)

  • Verónica Aguilar

    (Universidad del Istmo, Campus Tehuantepec, Santo Domingo Tehuantepec, Oaxaca, México)

  • Daniel Pacheco

    (Universidad del Istmo, Campus Tehuantepec, Santo Domingo Tehuantepec, Oaxaca, México)

  • Marco Antonio Acevedo

    (#x2020;Instituto Politécnico Nacional, Escuela Superior de Ingeniería, Mecánica y Eléctrica Zacatenco, México City, México)

  • Wen Yu

    (#x2021;CINVESTAV, IPN, Zacatenco, México City, México)

  • María Elena Acevedo

    (#x2020;Instituto Politécnico Nacional, Escuela Superior de Ingeniería, Mecánica y Eléctrica Zacatenco, México City, México)

Abstract

Knowledge society blockchain is one of the most powerful and recent tools to make the internet environment safer and reliable. Manufacturing has traditionally been dominated by standard designs that are mass-produced, due to the fact, that custom production causes additional costs that make it less affordable than mass production. This paper proposes to develop a designer expert system for IoT installation layout designs, using blockchain distributed system based on a machine learning, with users entering data to the expert system by a smart bot software. This expert system will work using extreme learning machine as inference engine; therefore, this is a shell to develop any expert system with fast learning. The whole system is represented by a smart contract with a value linked to the value of the expert system, the more this expert system be quoted on the web, the more the shares of the smart contract will cost.

Suggested Citation

  • Ricardo Carreño & Verónica Aguilar & Daniel Pacheco & Marco Antonio Acevedo & Wen Yu & María Elena Acevedo, 2019. "An IoT Expert System Shell in Block-Chain Technology with ELM as Inference Engine," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 87-104, January.
    • Handle: RePEc:wsi:ijitdm:v:18:y:2019:i:01:n:s0219622018500499
    DOI: 10.1142/S0219622018500499
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    References listed on IDEAS

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    1. Wei Gu & Thomas L. Saaty & Rozann Whitaker, 2016. "Expert System for Ice Hockey Game Prediction: Data Mining with Human Judgment," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 763-789, July.
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    6. Jonathan Donier & Julius Bonart, 2014. "A Million Metaorder Analysis of Market Impact on the Bitcoin," Papers 1412.4503, arXiv.org, revised Sep 2015.
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    Cited by:

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