INOV Researchers Win 2023 Best Paper Award in Fire Sciences Journal

We are thrilled to announce that a team of researchers from INOV – INESC Inovação has been awarded the Best Paper Award for 2023 by the Journal of Fire Sciences. The award-winning paper, entitled “Automatic early detection of wildfire smoke with visible-light cameras and EfficientDet,” authored by Paulo Chaves, Andrei B Utkin, and Armando M Fernandes, represents a significant milestone in the field of fire safety science.

The Best Paper Award, bestowed upon relevant contributions in applied research within the fire safety science community, underscores the innovative approach and impactful findings of the INOV researchers’ work.

Project overview:
The award-winning paper is a product of the ResNetDETECT project, which aims to develop an early automatic forest fire detection system utilizing neural networks. The primary objective of ResNetDETECT is to enhance the detection of small smoke plumes in images captured in visible light wavelengths. This critical endeavour addresses the pressing need for proactive measures in wildfire prevention and mitigation.

Key Objectives:

  • Development of Deep Neural Networks: The project focuses on constructing deep neural networks with optimized architectures tailored for the task of early wildfire detection. These networks are designed to exhibit exceptional sensitivity in identifying subtle smoke patterns indicative of incipient wildfires.
  • False alarm reduction: False alarms are a major problem in automatic systems, as they call for operatives’ attention when nothing is happening in reality. Their large number can lead to the system’s alerts being disregarded. The projects constructed neural networks that reduce the number of false alarms to the point that they no longer bother operatives.

Significance of the Research:
The innovative use of state-of-the-art neural network architectures is revolutionizing wildfire detection capabilities. By enabling early and accurate identification of potential fire outbreaks, the ResNetDETECT project contributes significantly to the ongoing efforts aimed at preventing and mitigating the adverse effects of wildfires.

Conclusion:
The recognition received through the Best Paper Award for their state-of-the-art research in automatic early detection of wildfire smoke underscores the commitment and expertise of the researchers at INOV. As they continue to push the boundaries of innovation in fire safety science, their contributions promise to make invaluable strides towards safeguarding communities and ecosystems from the devastating impact of wildfires.

INOV remains at the forefront of research and development in this field, striving to address societal challenges and advance technological solutions for a safer and more sustainable future.

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Published 08/04/2024
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