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Test the Capability of Arduino TinyML for Machine Learning

  • Aix-Marseille Université
  • Noroff University College
  • Noroff College

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Machine learning can be used for anything in our daily lives using TinyML, with low power and memory constraints. This chapter shows a test of the capability of Arduino Nano 33 BLE Sense board to perform machine learning. For this, TinyML board with its sensors will be compared with equivalent machine learning using a computer. The results of these two approaches will be compared to know whether the board shows satisfying results. This board is still not widely used, and acknowledging what it can do will allow us to use it more effectively.

Original languageEnglish
Title of host publication7th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2023
EditorsÖmer Melih Gül, Paolo Fiorini, Seifedine Nimer Kadry
PublisherSpringer Science and Business Media Deutschland GmbH
Pages161-175
Number of pages15
ISBN (Print)9783031644948
DOIs
StatePublished - 2024
Event7th EAI International Conference on Robotics and Networks, ROSENET 2023 - Istanbul, Turkey
Duration: 15 Dec 202316 Dec 2023

Publication series

NameEAI/Springer Innovations in Communication and Computing
ISSN (Print)2522-8595
ISSN (Electronic)2522-8609

Conference

Conference7th EAI International Conference on Robotics and Networks, ROSENET 2023
Country/TerritoryTurkey
CityIstanbul
Period15/12/2316/12/23

Keywords

  • Embedded system
  • Machine learning
  • Neural network
  • TinyML

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