Embedded systems technology is undergoing a phase of transformation owing to the novel
advancements in computer architecture and the breakthroughs in machine learning …

The advancements in machine learning (ML) opened a new opportunity to bring intelligence
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …

In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …

With the rapid development of mobile devices and deep learning, mobile smart applications
using deep learning technology have sprung up. It satisfies multiple needs of users, network …

Machine learning is becoming increasingly important in this era of big data. It enables us to
extract meaningful information from the overwhelming amount of data being generated and …

Abstract In recent years, Artificial Intelligence (AI) and Machine learning (ML) have gained
significant interest from both, industry and academia. Notably, conventional ML techniques …

Edge Impulse is a cloud-based machine learning operations (MLOps) platform for
developing embedded and edge ML (TinyML) systems that can be deployed to a wide range …

This paper presents the Edge Learning Machine (ELM), a machine learning framework for
edge devices, which manages the training phase on a desktop computer and performs …

Edge Impulse is a cloud-based machine learning operations (MLOps) platform for
developing embedded and edge ML (TinyML) systems that can be deployed to a wide range …

Advanced computing systems have long been enablers for breakthroughs in artificial
intelligence (AI) and machine learning (ML) algorithms, either through sheer computational …