[HTML][HTML] TinyML for ultra-low power AI and large scale IoT deployments: A systematic review
The rapid emergence of low-power embedded devices and modern machine learning (ML)
algorithms has created a new Internet of Things (IoT) era where lightweight ML frameworks …
algorithms has created a new Internet of Things (IoT) era where lightweight ML frameworks …
A comprehensive survey on tinyml
Recent spectacular progress in computational technologies has led to an unprecedented
boom in the field of Artificial Intelligence (AI). AI is now used in a plethora of research areas …
boom in the field of Artificial Intelligence (AI). AI is now used in a plethora of research areas …
[PDF][PDF] TinyML-Based Classification in an ECG Monitoring Embedded System
Recently, the development of the Internet of Things (IoT) has enabled continuous and
personal electrocardiogram (ECG) monitoring. In the ECG monitoring system, classification …
personal electrocardiogram (ECG) monitoring. In the ECG monitoring system, classification …
Intelligence at the extreme edge: A survey on reformable tinyml
Machine Learning (TinyML) is an upsurging research field that proposes to democratize the
use of Machine Learning and Deep Learning on highly energy-efficient frugal …
use of Machine Learning and Deep Learning on highly energy-efficient frugal …
TinyML: Tools, applications, challenges, and future research directions
R Kallimani, K Pai, P Raghuwanshi, S Iyer… - Multimedia Tools and …, 2024 - Springer
Abstract In recent years, Artificial Intelligence (AI) and Machine learning (ML) have gained
significant interest from both, industry and academia. Notably, conventional ML techniques …
significant interest from both, industry and academia. Notably, conventional ML techniques …
[HTML][HTML] Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study
The use of artificial intelligence (AI) at the edge is transforming every aspect of the lives of
human beings from scheduling daily activities to personalized shopping recommendations …
human beings from scheduling daily activities to personalized shopping recommendations …
Tinyreptile: Tinyml with federated meta-learning
Tiny machine learning (TinyML) is a rapidly growing field aiming to democratize machine
learning (ML) for resource-constrained microcontrollers (MCUs). Given the pervasiveness of …
learning (ML) for resource-constrained microcontrollers (MCUs). Given the pervasiveness of …
[HTML][HTML] Federated learning for IoT devices: Enhancing TinyML with on-board training
M Ficco, A Guerriero, E Milite, F Palmieri… - Information …, 2024 - Elsevier
The spread of the Internet of Things (IoT) involving an uncountable number of applications,
combined with the rise of Machine Learning (ML), has enabled the rapid growth of pervasive …
combined with the rise of Machine Learning (ML), has enabled the rapid growth of pervasive …
[HTML][HTML] Leveraging Edge Computing ML Model Implementation and IoT Paradigm towards Reliable Postoperative Rehabilitation Monitoring
E Faliagka, V Skarmintzos, C Panagiotou, V Syrimpeis… - Electronics, 2023 - mdpi.com
In this work, an IoT system with edge computing capability is proposed, facilitating the
postoperative surveillance of patients who have undergone knee surgery. The main …
postoperative surveillance of patients who have undergone knee surgery. The main …
[HTML][HTML] On the adoption of modern technologies to fight the COVID-19 pandemic: a technical synthesis of latest developments
A Majeed, X Zhang - COVID, 2023 - mdpi.com
In the ongoing COVID-19 pandemic, digital technologies have played a vital role to minimize
the spread of COVID-19, and to control its pitfalls for the general public. Without such …
the spread of COVID-19, and to control its pitfalls for the general public. Without such …