Related papers: Wireless Sensor Networks anomaly detection using M…

Wireless Sensor Networks forms the backbone of modern cyber physical systems used in various applications such as environmental monitoring, healthcare monitoring, industrial automation, and smart infrastructure. Ensuring the reliability of…

Wireless sensor networks (WSNs) are employed across a wide range of industrial applications where ultra-low power consumption is a critical prerequisite. At the same time, these systems must maintain a certain level of determinism to ensure…

After decades of research, the Internet of Things (IoT) is finally permeating real-life and helps improve the efficiency of infrastructures and processes as well as our health. As a massive number of IoT devices are deployed, they naturally…

Anomaly detection is critical in the smart industry for preventing equipment failure, reducing downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large volumes of data from industrial machinery, providing…

Technology evolves quickly. Low-cost and ready-to-connect devices are designed to provide new services and applications. Smart grids or smart healthcare systems are some examples of these applications, all of which are in the context of…

The application of machine learning (ML) techniques in wireless communication domain has seen a tremendous growth over the years especially in the wireless sensing domain. However, the questions surrounding the ML model's inference…

Wireless sensor networks (WSNs) have been adopted as merely data producers for years. However, the data collected by WSNs can also be used to manage their operation and avoid unnecessary measurements that do not provide any new knowledge…

Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the…

Wireless Sensor Networks(WSN) are a today technology with great practicability in the real world. We focus on describing WSN architecture, regarding usefulness in constructions like structural health monitoring and importance, and…

Distributed machine learning (DML) techniques, such as federated learning, partitioned learning, and distributed reinforcement learning, have been increasingly applied to wireless communications. This is due to improved capabilities of…

The nature of Wireless Sensor Networks (WSN) and the widespread of using WSN introduce many security threats and attacks. An effective Intrusion Detection System (IDS) should be used to detect attacks. Detecting such an attack is…

Wireless Sensor Networks (WSNs) are the key components of the emerging Internet-of-Things (IoT) paradigm. They are now ubiquitous and used in a plurality of application domains. WSNs are still domain specific and usually deployed to support…

This paper describes the use of neural networks to enhance simulations for subsequent training of anomaly-detection systems. Simulations can provide edge conditions for anomaly detection which may be sparse or non-existent in real-world…

Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Unfortunately, these networks are vulnerable to numerous security threats that can adversely affect…

Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Unfortunately, these networks are vulnerable to numerous security threats that can adversely affect…

Thanks to the recent advances in processing speed and data acquisition and storage, machine learning (ML) is penetrating every facet of our lives, and transforming research in many areas in a fundamental manner. Wireless communications is…

Wireless Sensor Networks (WSNs) have the goal of gathering data from the environment. The advent of the Internet of Things (IoT) drastically changed WSN's vision that, as never before, needs to expand and include hundreds or thousands of…

Wireless sensor networks (WSNs) have enabled continuous monitoring of an area of interest (body, room, region, etc.) while eliminating expensive wired infrastructure. Typically in such applications, wireless sensor nodes report the sensed…

Wireless signal recognition (WSR) is crucial in modern and future wireless communication networks since it aims to identify properties of the received signal. Although many deep learning-based WSR models have been developed, they still rely…

Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge.…