FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time
Wildland Fire Smoke Detection
- URL: http://arxiv.org/abs/2112.08598v1
- Date: Thu, 16 Dec 2021 03:49:58 GMT
- Title: FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time
Wildland Fire Smoke Detection
- Authors: Anshuman Dewangan, Yash Pande, Hans-Werner Braun, Frank Vernon, Ismael
Perez, Ilkay Atlintas, Gary Cottrell, Mai H. Nguyen
- Abstract summary: Fire Ignition Library (FIgLib) is a publicly-available dataset of nearly 25,000 labeled wildfire smoke images.
SmokeyNet is a novel deep learning architecture usingtemporal information from camera imagery for real-time wildfire smoke detection.
When trained on the FIgLib dataset, SmokeyNet outperforms comparable baselines and rivals human performance.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The size and frequency of wildland fires in the western United States have
dramatically increased in recent years. On high fire-risk days, a small fire
ignition can rapidly grow and get out of control. Early detection of fire
ignitions from initial smoke can assist the response to such fires before they
become difficult to manage. Past deep learning approaches for wildfire smoke
detection have suffered from small or unreliable datasets that make it
difficult to extrapolate performance to real-world scenarios. In this work, we
present the Fire Ignition Library (FIgLib), a publicly-available dataset of
nearly 25,000 labeled wildfire smoke images as seen from fixed-view cameras
deployed in Southern California. We also introduce SmokeyNet, a novel deep
learning architecture using spatio-temporal information from camera imagery for
real-time wildfire smoke detection. When trained on the FIgLib dataset,
SmokeyNet outperforms comparable baselines and rivals human performance. We
hope that the availability of the FIgLib dataset and the SmokeyNet architecture
will inspire further research into deep learning methods for wildfire smoke
detection, leading to automated notification systems that reduce the time to
wildfire response.
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