Nowadays, the challenges related to technological and environmental development are
becoming increasingly complex. Among the environmentally significant issues, wildfires …

Although there has been study on worker detection using computer vision (CV) for the safety
of construction sites, it is still challenging to identify employees who are obstructed or have …

Deep learning-based fire detection models are usually trained offline on static datasets. For
continuously increasing heterogeneous sensor data, incremental learning is a resolution to …

In recent years, tragedies caused by forest fires have been frequently reported. Forest fires
not only result in significant economic losses but also cause environmental damage. The …

In this critical brief review, we explore the pivotal role of computer vision in wildfire detection,
following the PRISMA methodology and focusing on 35 key studies published between …

Open burning is the main factor contributing to the occurrence of wildfires in Thailand, which
every year result in forest fires and air pollution. Open burning has become the natural …

This study explores the potential of RGB image data for forest fire detection using deep
learning models, evaluating their advantages and limitations, and discussing potential …

Currently, the spectra-based physical models and deep learning methods are frequently
used to detect wildfires from remote sensing data. However, physical algorithms mainly rely …

Satellite data are essential during wildfires for understanding its adverse effects and
improving the effectiveness of rapid disaster management. However, existing techniques …

Introduction: Fatal fall from height accidents, especially on construction sites, persist,
underscoring the importance of monitoring and managing worker behaviors to enhance …