ディープラーニング・モデルで火災検知に挑む(Firing Up Fire Detection Efforts with Deep Learning Models)

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2023-08-22 カリフォルニア大学サンディエゴ校(UCSD)

◆サンディエゴ・スーパーコンピューターセンター(SDSC)の研究者は、山火事の早期検出を改善するための新しい深層学習モデルを開発しました。これには、異なるデータソースを統合するモデルが含まれ、特にMultimodal SmokeyNetモデルが精度、検出速度で改善を示しました。
◆チームは今後、他の地域やカメラタイプのデータを活用し、偽陽性の問題に対処する方法を検討する予定です。また、リアルタイムの煙検出を効果的に支援するためにモデルの最適化も進めます。

<関連情報>

マルチモーダルな山火事の煙検知 Multimodal Wildland Fire Smoke Detection

Jaspreet Kaur Bhamra,Shreyas Anantha Ramaprasad,Siddhant Baldota,Shane Luna,Eugene Zen,Ravi Ramachandra,Harrison Kim,Chris Schmidt,Chris Arends,Jessica Block,Ismael Perez,Daniel Crawl,Ilkay Altintas,Garrison W. Cottrell andMai H. Nguyen
Remote Sensing  Published: 27 May 2023
DOI: https://doi.org/10.3390/rs15112790

ディープラーニング・モデルで火災検知に挑む(Firing Up Fire Detection Efforts with Deep Learning Models)

Abstract

Research has shown that climate change creates warmer temperatures and drier conditions, leading to longer wildfire seasons and increased wildfire risks in the United States. These factors have, in turn, led to increases in the frequency, extent, and severity of wildfires in recent years. Given the danger posed by wildland fires to people, property, wildlife, and the environment, there is an urgent need to provide tools for effective wildfire management. Early detection of wildfires is essential to minimizing potentially catastrophic destruction. To that end, in this paper, we present our work on integrating multiple data sources into SmokeyNet, a deep learning model using spatiotemporal information to detect smoke from wildland fires. We present Multimodal SmokeyNet and SmokeyNet Ensemble for multimodal wildland fire smoke detection using satellite-based fire detections, weather sensor measurements, and optical camera images. An analysis is provided to compare these multimodal approaches to the baseline SmokeyNet in terms of accuracy metrics, as well as time-to-detect, which is important for the early detection of wildfires. Our results show that incorporating weather data in SmokeyNet improves performance numerically in terms of both F1 and time-to-detect over the baseline with a single data source. With a time-to-detect of only a few minutes, SmokeyNet can be used for automated early notification of wildfires, providing a useful tool in the fight against destructive wildfires.

2100総合技術監理一般
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