This review comprehensively investigates the current state and emerging trends of
autonomous vehicle terrain detection and segmentation. By systematically reviewing …

As Large Language Models (LLMs) have achieved significant success in handling multi-
modal tasks such as text, images, videos, and sounds, particularly showcasing emergent …

The advancement of the communications system has resulted in the rise of the Internet of
Things (IoT), which has increased the importance of cybersecurity research. IoT, which …

This study proposes a two-phase framework to enhance disaster management strategies for
flooding using Geographic Information System (GIS) and Internet of Things (IoT) real-time …

Green building (GB) techniques are essential for reducing energy waste in the construction
sector, which accounts for almost 40% of global energy consumption. Despite their …

Accurately estimating the state-of-health of batteries is critical for effective battery monitoring
and management. However, the estimation remains challenging due to dynamic operation …

Data-driven models, especially deep learning models, are proposed for remaining useful life
(RUL) estimation with multisensor signals. Various treatments to reduce data sensitivity …

In pursuit of carbon neutrality and advancing energy-efficient practices within the steel and
coking industries, the traditional cokemaking process is progressively evolving towards …

Microplastics (MPs) in farming soils can have a substantial impact on soil ecology and
agricultural productivity, as well as affecting human health and the food chain cycle. As a …

Smart cities and villages present a plethora of opportunities for fusing and managing multi-
source data. However, in the analysis of mobility patterns, the use of only one data source …