Disaster Recovery Journal Summer 2025

n Images, videos, messages: Mobile devices can capture a variety of data types, including images and audio, which can be transferred directly from sites of interest. Smartphones with sensors, can also collect valuable data. n IoT, sensors, and stations: Telecommunication networks connect a wide range of devices, sensors, and meteorological and seismological stations. These devices collect real-time data from strategically determined locations, covering various parameters like weather conditions, temperature, seismic activity, precipitation, and river levels. n Satellites: Satellite imagery offers a global view of natural phenomena, helping to detect large-scale patterns and changes, such as flooded areas, wildfires, ground deformation (e.g., landslides and seismic or volcanic movements), and more. This data can be complemented with additional layers of information, such as land use, geography, geology, and terrain topography. 3.2 Data Processing and Analysis n Quality assurance: Collected structured and unstructured data undergo processes such as normalization, quality validation, identification of false positives and negatives, and verification of legitimacy before utilization. n Data centers/cloud computing: Data is sent to processing centers or cloud environments, where specialized software processes and analyzes it. n Predictive models: Advanced technologies like artificial intelligence (AI), machine learning, and mathematical modeling are used to analyze and predict disaster event evolution. These models enable timely alerts by identifying potential risks. n Data evaluation: Relevant information is compared against permissible patterns, generating statistics, projections, vulnerability assessments, damage evaluations, risk modeling, and direct monitoring results. These outputs support decision-making through maps, reports, and detailed analysis. 3.3 Alert Transmission and Dissemination to the Population Effective transmission of alerts is essential for saving lives, protecting assets and heritage, preserving the environment, and maintaining business and operational continuity. Different com munication methods can be utilized, including: n Mass communication systems: Examples include traditional Emergency Alert Systems (EAS) via radio and television, mobile messaging systems, social media, digital platforms, specialized alert applications, and official portals and websites. n Local communication technologies:

Satellite-based alert systems, amateur radio networks, community committees and local networks, specific radio systems, digital and physical signage in public spaces, emails, call centers, and emergency hotlines. n Direct and complementary methods: These include public sirens, loudspeaker systems, physical and digital signage in public areas, and house-to-house alerts. 4. Challenges and Barriers in Early Warning System Generation 4.1 Governance and Institutional Actions Challenges n Lack of clear or coherent policies: Absence of well-defined or harmonized policies to achieve satisfactory results. n Non-compliance with legal and regulatory frameworks: The need to identify commitments and legal requirements to ensure their proper implementation. n Corruption and misappropriation of resources: Misuse of domestic or international aid funds is a persistent issue, particularly in developing countries. n Lack of coordination: Poor coordination between centralized and decentralized entities, and political interests taking precedence over community needs, can hinder early warning system implementation. n Challenges in resource allocation: Competition for limited resources can make it difficult to invest in, modernize, and maintain early warning systems. 4.2 Technological Challenges n Selection of appropriate technologies: The most suitable technologies must be chosen for each case, balancing the cost-benefit ratio of the investments. n Lack of infrastructure: Insufficient meteorological stations, seismographs, mapping tools, IoT devices, and other detection mechanisms limit the ability to collect accurate real-time data for analysis, diagnostics, and monitoring of behavioral changes. n Data quality and integration from multiple sources: Combining information from satellites, radars, meteorological stations, seismographs, and other sensors to form a comprehensive picture of the situation. n Access to technology and information: Limited access to information and communication technologies in many regions hinders data collection, transmission, processing, and dissemination. 4.3 Social and Cultural Challenges n Social vulnerability: Communities in highly exposed areas with unfavorable conditions lack the capacity to reduce, prevent, or recover from disasters and catastrophic events.

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