Journal of Sensor and Actuator Networks, Volume 14, Issue 2

The development of reliable sensor networks for vibration monitoring is essential for the preventive conservation of buildings and structures. The identification of natural frequencies is crucial both for sensor network planning, to ensure optimal pl...

Chest X-ray interpretation is essential for diagnosing cardiac and respiratory diseases. This study introduces a deep learning ensemble approach that integrates Convolutional Neural Networks (CNNs), including ResNet-152, VGG19, EfficientNet, and a Vi...

The Internet of Military Things (IoMT) is transforming defense operations by enabling the seamless integration of sensors and actuators for the real-time transmission of critical data in diverse military environments. End devices (EDs) collect essent...

Human activity recognition (HAR) is the task of classifying sequences of data into defined movements. Taking advantage of deep learning (DL) methods, this research investigates and optimizes neural network architectures to effectively classify physic...

The growing complexity and volume of genomic and omics data present critical challenges for storage, transfer, and analysis in edge–cloud platforms. Existing compression techniques often involve trade-offs between efficiency and speed, requirin...

The unprecedented rise of deepfake technologies, leveraging sophisticated AI like Generative Adversarial Networks (GANs) and diffusion-based models, presents both opportunities and challenges in terms of digital media authenticity. In response, this...

Urban air mobility (UAM) is expected to provide environmental benefits while enhancing transportation for citizens and businesses, particularly in commercial and emergency medical applications. The rapid development of electric vertical take-off and...

This paper proposes a new approach to integrating Q learning into the fuzzy linear programming (FLP) paradigm to improve peer selection in P2P networks. Using Q learning, the proposed method employs real-time feedback to adjust and update peer select...

Two technologies of great interest in recent years—Artificial Intelligence (AI) and massive wireless communication networks—have found a significant point of convergence through Federated Learning (FL). Federated Learning is a Machine Lea...

The resource limitations of Low-Power Wireless Networks (LP-WNs), such as Wireless Sensor Networks (WSNs), Wireless Actuator/Sensor Networks (WA/SNs), and Internet of Things (IoT) outdoor applications, restrict the utilization of the error-performanc...