Enhancing Post-Earthquake Communication Resilience: Integrating UAVs, LoRa Technology, and GDPR-Compliant Systems (EPECR)

Introducing Unmanned Aerial Vehicles (UAVs) in disaster response and recovery operations has transformed how we handle post-disaster scenarios, particularly if the traditional communication infrastructures are damaged or destroyed. UAVs are flexible, mobile, and can be rapidly deployed, making them essential for establishing communication networks in disaster areas. This research aims to combine the benefits of UAVs with LoRa technology, known for its long-range and low-power capabilities, and ensure data protection as required by the General Data Protection Regulation (GDPR). The goal is to create a resilient and secure mobile network specifically designed for use after earthquakes.

The motivation behind this research is the urgent need to establish reliable and dynamic communication channels during disaster recovery efforts. Effective communication can significantly reduce the overall impact of catastrophic events by enabling timely coordination among rescue teams, efficient allocation of resources, and quick dissemination of crucial information.

Post-disaster environments are challenging due to constantly changing conditions and limited resources. To tackle these challenges, we will employ strategies to extend the network's lifespan, maintain service quality, and ensure compliance with GDPR security protocols. A central part of this research is developing a practical prototype to test our solutions in real-world scenarios. This prototype will allow comprehensive testing and evaluation of our communication methods, providing valuable insights into their performance and effectiveness in disaster recovery operations. We will use a combination of theoretical modelling, simulation, and practical experimentation to achieve our goals.

Our research methods include several innovative strategies. First, we will use network situational awareness to implement load balancing and UAV trajectory-based forwarding protocols. These protocols aim to optimise data routing, ensuring efficient resource use and enhancing overall network performance. Second, we will investigate self-organising UAV swarm mechanisms using artificial intelligence (AI) and machine learning (ML) techniques. These mechanisms will enable UAVs to dynamically adjust their positions and coverage areas, ensuring optimal network coverage and connectivity. Additionally, we will explore edge computing techniques for decentralised data processing. We can reduce latency and improve data handling and analysis efficiency by processing data at the network's edge, closer to the data sources. This approach is crucial in disaster scenarios where timely decision-making is essential.

Equipping UAVs with cellular, LoRa, satellite communications, and GDPR-compliant systems significantly enhances disaster response. This robust, secure network facilitates faster recovery, better resource management, and improved rescue team coordination, ultimately mitigating disaster impacts and accelerating community recovery.

In summary, this research aims to advance disaster recovery communication networks by integrating UAV technology with LoRa, edge computing, AI, and GDPR-compliant security protocols. The development and testing of these innovative communication methods aim to provide a reliable and resilient solution for post-disaster scenarios. The broader impact includes enhanced disaster response, improved recovery times, and better resource management, contributing to societal and economic resilience in the face of natural disasters. This project will significantly impact various stakeholders by improving disaster preparedness and response capabilities, including individuals, organisations, and nations.