Wildfire Mapping Using SAR-Derived NBR through Generative Adversarial Network
Improving Disaster Management with Multimodal Information from Social Media
When a natural disaster occurs, the situation on-site can be quite chaotic and overwhelming, making it hard to understand for emergency responders. To react effectively, a detailed understanding of the situation on the ground is required, as it determines where resources and manpower are deployed. After events such as floods or earthquakes, traditional methods of information gathering and transportation are often hindered, e.g. by physical barriers or overwhelmed call centres.
Adjusting the Rate of Spread of Fire Simulations in Real-time
Leveraging Information Fusion for Enhanced Natural Disaster Management
The Federated Learning Technique for Mitigating the Climate Change
Synthetic Images in People Detection: Balancing Effectiveness and Ethical Imperatives
Interoperability Governance in Emergency Services in the European Union
Targeted and Ex-ante Assessments: Protecting the Right to Privacy and the Protection of Personal Data and Enhancing the Overall Data Processing Mechanism within and Outside the TEMA Project
In a recent publication[1], AUTH (TEMA coordinator) proposed a fully-fledged privacy-assessment that could be applied to future uses of Autonomous Systems (AS) for Natural Disaster Management (NDM) purposes. After exploring whether and how certain implementations may interfere with the right to privacy and the protection of personal data, the authors detected key challenges stemming from non-compliance with the General Data Protection Regulation (GDPR).
Big Data and XR for Emergency Response Management
In today's world, where natural disasters seem to be occurring with increasing frequency and intensity, the importance of effective emergency and disaster management cannot be overstated. It's a collective effort that requires international collaboration between countries, organisations, and individuals to tackle these challenges head-on.
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