Machine Learning (ML) and Internet of Things (IoT) are complementary advances: ML
techniques unlock the potential of IoT with intelligence, and IoT applications increasingly …

The pursuit of many research questions requires massive computational resources. State-of-
the-art research in physical processes using simulations, the training of neural networks for …

Smart, secure and energy-efficient data collection (DC) processes are key to the realization
of the full potentials of future Internet of Things (FIoT)-based systems. Currently, challenges …

The massive number of Internet of Things (IoT) devices connected to the Internet is
continuously increasing. The operations of these devices rely on consuming huge amounts …

This study proposes a novel concept of reinforcement learning (RL) framework to facilitate
automated structural design, with a particular focus on reinforced concrete (RC) beam …

Nowadays, many research studies and industrial investigations have allowed the integration
of the Internet of Things (IoT) in current and future networking applications by deploying a …

With the recent explosive growth of the Internet of Things (IoT), edge computing is emerging
as a modern computing paradigm that coexists with the cloud to process massive amounts …

Research on autonomous management for large-scale deployments of constrained devices
is still a maturing field in the Internet of Things (IoT). Although much research has been …

Energy management can extend the lifetime of batteryless, energy-harvesting systems by
judiciously utilizing the energy available. Duty cycling of such systems is especially …

In order to make better use of deep reinforcement learning in the creation of sensing policies
for resource-constrained IoT devices, we present and study a novel reward function based …