A tinyml deep learning approach for indoor tracking of assets

HIGHLIGHTS

  • who: Diego Avellaneda and colleagues from the School of Engineering, Electronics Engineering Department, Pontificia Universidad Javeriana, Bogotu00e1, Colombia have published the Article: A TinyML Deep Learning Approach for Indoor Tracking of Assets, in the Journal: Sensors
  • what: The aim of the IoT indoor positioning system is to allow the identification and tracking of assets in such a way that it is possible to generate presence or absence alerts. The work presents a patent that is specifically oriented in the field of radio frequency and the deployment of multiple devices in an indoor environment, aiming to . . .

     

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