@article{ref1,
title="Thermal infrared sensing for near real-time data-driven fire detection and  monitoring systems",
journal="Sensors (Basel)",
year="2020",
author="Sousa, Maria João and Moutinho, Alexandra and Almeida, Miguel",
volume="20",
number="23",
pages="e6803-e6803",
abstract="With the increasing interest in leveraging mobile robotics for fire detection and  monitoring arises the need to design recognition technology systems for these  extreme environments. This work focuses on evaluating the sensing capabilities and  image processing pipeline of thermal imaging sensors for fire detection  applications, paving the way for the development of autonomous systems for early  warning and monitoring of fire events. The contributions of this work are threefold. First, we overview image processing algorithms used in thermal imaging regarding  data compression and image enhancement. Second, we present a method for data-driven  thermal imaging analysis designed for fire situation awareness in robotic  perception. A study is undertaken to test the behavior of the thermal cameras in  controlled fire scenarios, followed by an in-depth analysis of the experimental  data, which reveals the inner workings of these sensors. Third, we discuss key  takeaways for the integration of thermal cameras in robotic perception pipelines for  autonomous unmanned aerial vehicle (UAV)-based fire surveillance.  Keywords: Pipeline transportation<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s20236803",
url="http://dx.doi.org/10.3390/s20236803"
}