Localizing Smoke and Gas Sources using Physics-Inspired Sparse Bayesian Learning Method

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Localizing Smoke and Gas Sources using Physics-Inspired Sparse Bayesian Learning Method

Accurate modeling and estimation of airborne materials, such as gases, smoke, or particulate matter, are critical for effective disaster response, particularly in the context of both natural and manmade disasters. In scenarios where traditional visual sensors cannot reliably detect the material of interest, it is crucial to understand its spatio-temporal dynamics in order to coordinate… Continue reading Localizing Smoke and Gas Sources using Physics-Inspired Sparse Bayesian Learning Method

Flood Image Analysis

Climate change has increased the frequency and severity of flooding, presenting significant challenges for Natural Disaster Management (NDM). Effective emergency response depends on the timely detection of flooded areas and critical objects. Advanced Deep Neural Networks (DNNs) are applied for flood region segmentation and object detection, specifically focusing on persons, vehicles, and house roofs in… Continue reading Flood Image Analysis

Wildfire Image Analysis

With climate change accelerating, new challenges in Natural Disaster Management (NDM) are driving significant advancements in Deep Neural Networks (DNNs), particularly for wildfire detection and segmentation. These tasks demand precise, near real-time decision-making to address the complex and dynamic nature of wildfires. Drone imagery, a primary data source, enables efficient detection and monitoring of fire… Continue reading Wildfire Image Analysis

Sensors and Big Visual Data Analytics for Natural Disaster Management (NDM)

Natural Disaster Management (NDM), such as for wildfires and floods, can be significantly enhanced through automated, precise semantic 3D mapping and disaster evolution prediction, enabling near-real-time decision-making. This requires the analysis and fusion of heterogeneous extreme data sources, including smart drone sensors (e.g., RGB, RGBD, thermal cameras, Lidars), emergency vehicle sensors, in-situ sensors (smoke, moisture,… Continue reading Sensors and Big Visual Data Analytics for Natural Disaster Management (NDM)