Reinforcement getting to know (RL) has emerged as a famous method to predict
considerable occasions inside the Net of Things (IoT) networks. RL is a form of artificial …

Debasements and disappointments underway frameworks are brought about by functional
and natural conditions. Spontaneous, unscheduled maintenance techniques do, truth be …

The modern Web of Things (IIoT) alludes to the use of Web of Things (IoT) innovation
underway that empowers the use of machine information created by different sensors and …

Internet of Things (IoT) with its growing number of deployed devices and applications raises
significant challenges for network maintenance procedures. In this work, we formulate a …

In this paper, we consider the problem of deriving recommended resilient and predictive
actions for an IoT network in the presence of faulty components and malicious agents. The …

In the age of the Internet of Things (IoT), day-to-day objects are outfitted with sensors and
actuators. It is also referred to as IoT units that gather information and function moves …

This study examines the predictive maintenance of industrial equipment. Through a Google
form, we gathered various viewpoints from experts in the disciplines of Machine Learning …

In the era of the Internet of Things (IoT), everyday objects are equipped with sensors and
actuators. They are also referred to as IoT devices that collect data and perform actions by …

Reinforcement learning (RL) is a promising research area that focusses on the devices that
can be interconnected on the internet commonly known as the internet of things (IoT) where …

With many devices in the big data system, the challenge arises on how to configure the
devices based on the system constraints like the energy budget. The typical scenarios …