Computer Vision (CV) has become increasingly important for Single-Board Computers
(SBCs) due to their widespread deployment in addressing real-world problems. Specifically …

Advances in Artificial Intelligence (AI) and sensors are significantly impacting multiple areas,
including education and workplaces. Following the PRISMA methodology, this review …

Abstract While Federated Learning (FL) provides a privacy-preserving approach to analyze
sensitive data without centralizing training data, the field lacks an detailed comparison of …

The approach of federated learning (FL) addresses significant challenges, including access
rights, privacy, security, and the availability of diverse data. However, edge devices produce …

Decentralized federated learning tries to address the single point of failure and privacy issue
of federated learning by leveraging committee-based blockchain, which has been …

Sufficient building operational data serve as the key premise to enable the development of
reliable data-driven technologies for building energy management. Considering that …

Federated learning (FL) has recently gained popularity as a distributed machine learning
approach that protects privacy. However, this concept has not yet been extensively adopted …

Mass spectrometry (MS) is a powerful tool for compound structure elucidation, crucial in
various domains including pharmaceuticals, chemical synthesis, environmental analysis …

With the rapid growth of power demand and the advancement of new power system
intelligence, smart energy measurement system data quality and security are also facing the …

The advancement of digitization and automation in Low Altitude Intelligent Networking
(LAIN) is constrained by limited computational resources and the absence of a dedicated …