H Han, J Siebert - … on Artificial Intelligence in Information and …, 2022 - ieeexplore.ieee.org
Tiny Machine Learning (TinyML), a rapidly evolving edge computing concept that links embedded systems (hardware and software) and machine learning, with the purpose of …
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 …
VJ Reddi, B Plancher, S Kennedy, L Moroney… - arXiv preprint arXiv …, 2021 - arxiv.org
Broadening access to both computational and educational resources is critical to diffusing machine-learning (ML) innovation. However, today, most ML resources and experts are …
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 …
Recently, there has been a substantial interest in on-device Machine Learning (ML) models to provide intelligence for the Internet of Things (IoT) applications such as image …
Internet of Things devices are frequently used as consumer devices to provide digital solutions, such as smart lighting and digital voice-activated assistants, but they are also …
This paper provides an overview of blockchain technology's security and privacy features, as well as an overview of IoT-based cache memory and single-bit six transistor static random …
The monitoring of presence is a timely topic in intelligent building management systems. Nowadays, most rooms, halls, and auditoriums use a simple binary presence detector that is …
Recent advances in Tiny Machine Learning (TinyML) empower low-footprint embedded devices for real-time on-device Machine Learning (ML). While many acknowledge the …