Towards an Integrated Performance Framework for Fire Science and Management Workflows
Reliable performance metrics are necessary prerequisites to building large-scale end-to-end integrated workflows for collaborative scientific research, particularly within context of use-inspired decision making platforms with many concurrent users and when computing real-time and urgent results using large data. This work is a building block for the National Data Platform, which leverages multiple use-cases including the WIFIRE Data and Model Commons for wildfire behavior modeling and the EarthScope Consortium for collaborative geophysical research. This paper presents an artificial intelligence and machine learning (AI/ML) approach to performance assessment and optimization of scientific workflows. An associated early AI/ML framework spanning performance data collection, prediction and optimization is applied to wildfire science applications within the WIFIRE BurnPro3D (BP3D) platform for proactive fire management and mitigation.
Code (0)
등록된 구현이 없습니다.
Tasks
Decision MakingManagementSimilar Papers 제목 키워드 기반
A review of machine learning applications in wildfire science and management
Artificial intelligence has been applied in wildfire science and management since the 1990s, with early applications including neural networks and expert systems. Since then the field has rapidly progressed congruently w…
BIG-bench Machine LearningFire DetectionManagementSmoke Sky -- Exploring New Frontiers of Unmanned Aerial Systems for Wildland Fire Science and Applications
Wildfire has had increasing impacts on society as the climate changes and the wildland urban interface grows. As such, there is a demand for innovative solutions to help manage fire. Managing wildfire can include proacti…
ManagementEnhancing Tree Type Detection in Forest Fire Risk Assessment: Multi-Stage Approach and Color Encoding with Forest Fire Risk Evaluation Framework for UAV Imagery
Forest fires pose a significant threat to ecosystems, economies, and human health worldwide. Early detection and assessment of forest fires are crucial for effective management and conservation efforts. Unmanned Aerial V…
Fire DetectionManagementobject-detectionObject DetectionData Interpretation Support in Rescue Operations: Application for French Firefighters
This work aims at developing a system that supports French firefighters in data interpretation during rescue operations. An application ontology is proposed based on existing crisis management ones and operational expert…
ManagementAssessment of deep learning models integrated with weather and environmental variables for wildfire spread prediction and a case study of the 2023 Maui fires
Predicting the spread of wildfires is essential for effective fire management and risk assessment. With the fast advancements of artificial intelligence (AI), various deep learning models have been developed and utilized…