Abstract Industrial Internet of Things (IIoT) is a convincing stage by interfacing different
sensors around us to the Internet, giving incredible chances for the acknowledgment of …

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

While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …

This paper provides a brief survey of the basic concepts and algorithms used for Machine
Learning and its applications. We begin with a broader definition of machine learning and …

The predominant paradigm for using machine learning models on a device is to train a
model in the cloud and perform inference using the trained model on the device. However …

The functionality of the Internet is continually changing from the Internet of Computers (IoC)
to the “Internet of Things (IoT)”. Most connected systems, called Cyber-Physical Systems …

Abstract Machine learning is one of the emerging technologies that has grabbed the
attention of academicians and industrialists, and is expected to evolve in the near future …

Machine learning techniques will contribution towards making Internet of Things (IoT)
symmetric applications among the most significant sources of new data in the future. In this …

This paper will address the Positive and Unlabeled learning problem (PU learning) and its
importance in the growing field of semi-supervised learning. In most real-world classification …

The majority of IoT edge devices are embedded systems with a tiny microcontroller unit
(MCU), which acts as its brain. When users want their edge devices to continuously improve …