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oai:recercat.cat:2117/4002252026-01-14T08:22:19Zcom_2072_1033col_2072_452950

Position paper: LoRa mesh networks for enabling distributed intelligence on tiny IoT nodes Freitag, Fèlix Miquel Solé, Joan Meseguer Pallarès, Roc Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic Internet of things Machine learning IoT Embedded learning LoRa Mesh networks Internet de les coses Aprenentatge automàtic LoRaWAN is a widely used solution in today’s Internet of Things (IoT) applications to connect remote sensor nodes to the Internet. At the same time, microcontroller-based sensor nodes with increased processing capacities are in- creasingly becoming smart nodes applied for performing machine learning tasks. We argue that LoRaWAN has important connectivity limitations to truly unleash the potential of these smart tiny nodes. We position to apply LoRa mesh networks as a communication substrate to enable novel networking capacities for the new scenario of distributed smart IoT nodes. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 957258 — ASSIST-IoT, and was partially supported by the Spanish Government under contract PID2019-106774RB-C21, and the Generalitat de Catalunya as Consolidated Research Group 2021-SGR-01059. Peer Reviewed Postprint (published version) 2023 Part of book or chapter of book https://ebooks.iospress.nl/volume/workshop-proceedings-of-the-19th-international-conference-on-intelligent-environments-ie2023 info:eu-repo/grantAgreement/EC/H2020/957258/EU/Architecture for Scalable, Self-*, human-centric, Intelligent, Secure, and Tactile next generation IoT/ASSIST-IoT info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-106774RB-C21/ES/SISTEMAS INFORMATICOS Y DE RED DESCENTRALIZADOS CON RECURSOS DISTRIBUIDOS/ http://creativecommons.org/licenses/by-nc/4.0/ Open Access Attribution-NonCommercial 4.0 International IOS Press