Fire detection is a crucial research topic that has recently attracted many works. However,
most of these existing methods tend to achieve high accuracy based on large deep neural …

Advancements in deep learning and the Internet of Things (IoT) enable early fire detection
through vision-based systems, reducing ecological, social, and economic damage. These …

Fire disasters typically result in lot of loss to life and property. It is therefore imperative that
precise, fast, and possibly portable solutions to detect fire be made readily available to the …

Fire detection and management is very important to prevent social, ecological, and
economic damages. However, achieving real‐time fire detection with higher accuracy in an …

Fire hazards cause huge ecological, social and economical losses in day to day life. Due to
the rapid increase in the prevalence of fire accidents, it has become vital to equip the assets …

To mitigate social, ecological, and financial damage, effective fire detection and control are
crucial. Performing real-time fire detection in Internet of Things (IoT) environments, however …

This research paper presents the development of an advanced IoT-based fire and smoke
detection system leveraging deep learning and TinyML techniques. The objective is to …

Tactile Internet can combine multiple technologies by enabling intelligence via mobile edge
computing and data transmission over a 5G network. Recently, several convolutional neural …

Fire and smoke detection using deep learning have recently proven to be a robust and
efficient detection approach in contrast to traditional vision-based techniques. Efforts are …

Fire detection employing vision sensors has drawn significant attention within the computer
vision community, primarily due to its practicality and utility. Previous research …