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Urban areas face mounting pressure from increased space demand, degrading key environmental services. Thus, understanding Land Use/Land Cover (LULC) changes is vital. In order to offer a robust decision-support framework...

Environmental justice communities across the United States continue to experience disproportionate exposure to industrial pollution, particularly in regions dominated by petrochemical infrastructure. The Alsen / St. Irma...

This study presents a novel, site-specific deployment of a Long Range Wide Area Network (LoRaWAN)-driven air pollution monitoring network specifically for the Iraqi city of Mosul, which is beset by widespread power outag...

The perception systems for Traffic Sign Recognition (TSR) and Lane Line Recognition (LLR) are foundational pillars for the safe and effective operation of Advanced Driver-Assistance Systems (ADAS) and fully autonomous ve...

Soilless cultivation systems such as hydroponics rely on continuous and accurate monitoring of physicochemical parameters to maintain optimal plant growth conditions. In practice, however, hydroponic operations are const...

Small unmanned aerial systems (sUAS) are increasingly being used to conduct atmospheric research. Because of the dynamic nature and inhomogeneity of the atmospheric boundary layer (ABL), the ability of instrumented sUAS ...

Cities of the future will have to overcome congestion, air pollution and increasing infrastructure cost while moving more people and goods smoothly, efficiently and in an eco-friendly manner. Urban air mobility (UAM) is ...

Electroencephalography (EEG) is a crucial technique for interpreting neurocognitive functions and the underlying neural information. Despite its advantages, such as high portability, cost-effectiveness and exceptional te...

Rich in multiple strategic rare metals, deep-sea manganese nodules constitute an essential mineral resource for balancing terrestrial resource supply and demand and facilitating the global energy transition. Accurate pre...

Oil spill monitoring in port and maritime environments is essential for environmental protection and emergency response. However, precise segmentation from UAV-captured optical imagery is still difficult due to specular ...

The environmental performance of vehicle electrification depends critically on the extent to which electric vehicles (EV) actually replace conventional vehicles (CV). Comparative life cycle assessment (LCA) studies typic...

Abstract Simulating the response of granular materials under realistic loading scenarios is essential for ensuring the reliability of geotechnical infrastructure. This task is particularly challenging because natural soi...

Low-resolution images often lack fine detail and are prone to blurring, noise, and distortions, making accurate assessment challenging. This issue becomes even more challenging for applications, such as land mapping, env...

Spark detection in distribution line videos remains challenging due to weak visual saliency, multi-scale variation, and complex environmental interference. To address these issues, this paper presents an enhanced Swin Tr...

This paper proposes beam training algorithms for robust line-of-sight (LoS) multi-input and multi-output (MIMO) systems with subarray-based beamforming functionality at both the transmitter (TX) and receiver (RX). In gen...

Abstract The Internet of Things (IoT) encompasses a diverse array of solutions with applications ranging from smart cities to environmental monitoring and industrial processes. In this context, communication techniques t...

Wireless Sensor Networks (WSNs) are extensively used in applications such as environmental monitoring, surveillance, and smart security, but their performance is limited by the restricted energy capacity of sensor nodes,...

In recent years, the resilience of road traffic during abnormal events has drawn considerable attention. Intelligent navigation systems, which proactively guide drivers along optimal routes in such situations, are viewed...

The present study focuses on proposing various statistical models, such as linear regression (LR), nonlinear regression (NLR), and artificial neural network (ANN), to forecast the compressive strength of environmentally ...

The foremost task in agriculture is the decisive identification of citrus plants and the timely identification of diseases in the plants with the aim of improving the quality of crops and the yield. In this work, a machi...

Terrestrial evaporation ($E$) plays a crucial role in the water, energy, and carbon cycles and modulates climate change through multiple feedback mechanisms. While process-based models estimate $E$ using satellite-derive...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Chattanooga has undergone a remarkable transformation from a heavily industrialized rail depot and one of the nation’s most polluted cities to the first designated National Park City in the United States of America...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...