INSPIRE-5Gplus insights on TinyML for IoT presented at MLIS 2021
At the 3rd International Conference on Machine Learning and Intelligent Systems (MLIS 2021), which was held online from 8th to 11th November 2021, Dr. Ramón Sánchez Iborra from INSPIRE-5Gplus partner University of Murcia gave an invited talk on the latest insights of the project in the area of Tiny Machine Learning (TinyML). TinyML is an embedded software technology that integrates reduced and optimized machine learning applications for making computing at the edge less expensive and more effective.
Presentation by Dr. Ramón Sánchez Iborra from University of Murcia at MLIS 2021
The talk entitled “TinyML: A groundbreaking shift for the Internet of Things” explored how the dawn of the TinyML paradigm has brought a new wave of capabilities to new and already deployed Internet of Things (IoT) infrastructures. Concretely, TinyML permits to embed powerful ML mechanisms within resource-limited end-devices, hence evolving these elements into truly intelligent units. Besides, the conjunction of TinyML and edge-computing architectures paves the way for the development of distributed-intelligence systems. Dr. Sánchez Iborra pointed out the impact of these technologies on end-device security, privacy and integrity. In addition, he highlighted the crucial security interactions between all the elements forming the IoT system, in order to enable their safe integration within the 5G architecture.
The talk raised numerous questions and comments from the online audience. The vibrant discussion particularly focused on how the security aspects of TinyML are dealt with in INSPIRE-5Gplus.
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