Authors
Hung Guo1, *, Evgeni Magid2, Kuo-Hsien Hsia1, Kuo-Lan Su1
1Department of Electrical Engineering, National Yunlin University of Science & Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan, R.O.C.
2Intelligent Robotics Department, Kazan Federal University, 18 Kremlyovskaya Street, Kazan 420008, Russian Federation
*Corresponding author. Email: [email protected]
Corresponding Author
Hung Guo
Received 19 October 2019, Accepted 16 July 2020, Available Online 31 December 2020.
DOI
https://doi.org/10.2991/jrnal.k.201215.009How to use a DOI?
Keywords
Internet of things (IoT); fuzzy-AHP; adaptive fusion method (AFM); sensor network
Abstract
The application of Internet of Things (IoT) has been widely used in our lives with the advancement of related software and hardware technologies. In order to make these IoT modules more intelligent, many IoT modules have begun to incorporate artificial intelligence algorithms. Therefore, this paper develops IoT module with STM32 chip as main controller. This module uses fuzzy analytic hierarchy process (fuzzy-AHP) and adaptive fusion method (AFM) to improve the correctness and self-learning ability of the sensor. In terms of communication, the IoT module has Ethernet, Wi-Fi, LoRa, etc. communication interfaces. We also built a web server on this module, so the IoT module can operate directly in the browser. Finally, we developed a monitoring system. Through this monitoring system, multiple IoT modules can be constructed into a sensor network. This monitoring system can also use same algorithm to correct and isolate data from modules or sensors in the network to make this module more intelligent and applicable in different areas.
Copyright
© 2020 The Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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