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Publication type: Conference paper
Type of review: Peer review (publication)
Title: Low power LoRaWAN node based on FRAM microcontroller
Authors: Meli, Marcel
Furter, Claudio
Karakostas, Konstantinos
Kouzinopoulos, Charalampos
Tzovaras, Dimitrios
et. al: No
DOI: 10.1109/IDAACS-SWS50031.2020.9297075
Proceedings: Proceedings of the 2020 IEEE 5th International Symposium on Smart and Wireless Systems
Conference details: 2020 IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS), Dortmund (online), 17-18 September 2020
Issue Date: 2020
Publisher / Ed. Institution: IEEE
ISBN: 978-1-7281-9960-3
Language: English
Subjects: LPWAN; LoRaWAN; FRAM; Low power; Energy Harvesting; LoRa
Subject (DDC): 004: Computer science
Abstract: In the quest to improve the energy requirements of LPWAN nodes and make them more suitable for energy harvesting, a microcontroller with onchip Ferroelectric Random Access Memory (FRAM) was used as a controller in a LoRaWAN node. Energy measurements showed that the performance of such a device is comparable or better than that of a similar FLASH-based microcontroller. Furthermore, the advantages resulting from the high endurance and low-power characteristics of FRAM memories can be used to improve the node.
Further description: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Fulltext version: Accepted version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Embedded Systems (InES)
Published as part of the ZHAW project: AMANDA – AutonoMous self powered miniAturized iNtelligent sensor for environmental sensing anD asset tracking in smArt IoT environments
Appears in collections:Publikationen School of Engineering

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