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

Ricardo Carreño (), Verónica Aguilar, Daniel Pacheco, Marco Antonio Acevedo, Wen Yu and María Elena Acevedo
Additional contact information
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

International Journal of Information Technology & Decision Making (IJITDM), 2019, vol. 18, issue 01, 87-104

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.

Keywords: Block-chain; initial coin offer; expert system; blockchain maker expert system; extreme learning machine; internet of things (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0219622018500499

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