Mostafa Sameer

<div> Communities experience cascading losses when natural hazards trigger simultaneous damage to the built environment, critical lifelines, and the social systems that shape preparedness, response, and recovery. Yet, post-event evidence is often heavily fragmented due to data unavailability and siloed reporting. Critical information—such as missing physical measurements of structural damage, incomplete environmental observations of inundation extents and debris, and isolated human-centered records like eyewitness accounts—remains disconnected. This research addresses the core problem of how to seamlessly fuse heterogeneous human-centered data with physical sensing to improve the predictability of equitable recovery timelines for lifelines. </div> <div> To achieve this, the paper proposes a human-centered, multi-scale workflow that integrates these disparate data streams into an operational digital twin. This digital twin represents affected communities and supports resilience assessment and decision-making, specifically focusing on the case studies of wind-driven residential damage and its impact on power-grid restoration in coastal communities. This study leverages curated datasets from the NHERI DesignSafe Data Depot, including StEER Hurricane Michael reconnaissance data and high-resolution Hurricane Ian building-damage records. To establish a defensible baseline for resilience assessment, we prioritize the physical chain of causality: wind load, pressure, component demand, and subsequent failure. </div> <div> The proposed workflow operates in three primary stages. First, it ethically and rapidly captures human-centered data through structured interviews, community reporting, and privacy-preserving digital traces. Second, it harmonizes this information with remote and in-situ sensing to comprehensively characterize hazard intensity, exposure, and damage. Third, it utilizes multi-scale modeling to couple household- and facility-level functionality with community-wide lifeline interdependencies, enabling detailed scenario-based recovery analysis. </div> <div> To ensure rigor and defensibility, this study explicitly excludes monetary loss and long-term climate migration. Instead, the scope is intentionally limited to the first 30 days of the response-to-recovery transition to provide immediate, actionable insights for early-stage intervention. By linking hybrid simulations of representative components to data-assimilated network models, the framework provides decision-relevant indicators for equitable recovery planning. Anticipated key findings indicate that integrating human-centric records with physical sensing significantly reduces uncertainty in predicting initial lifeline restoration timelines. Ultimately, this work contributes to the natural hazards literature by providing a validated, ground-up engineering workflow that favors defensible assumptions over purely sophisticated modeling. </div>

Pedestrian safety at school locations has become a matter of great concern owing to the high vulnerability of young children traveling on foot. The percentage of children walking or cycling to school has decreased considerably because of traffic risks. This study employs GIS-based techniques to evaluate pedestrian and roadway safety around selected elementary schools in Miami-Dade County, Florida. Schools analysed include Miami Gardens Elementary, Crestview Elementary, Scott Lake Elementary, Hialeah Gardens Elementary, Noorwood Elementary, and Nathan B. Young Elementary. Using ArcGIS 10.7, the analysis integrates crash history data (1996-2004), land use maps, road network inventories, and the Highway Safety Manual (HSM) Predictive Method to identify high-risk corridors and propose countermeasures. Key findings reveal systemic infrastructure deficiencies including absence of traffic signals at critical intersections, lack of crossing guards at documented high-crash locations and missing median protection on high-volume arterials. Targeted recommendations-crossing guards, high-visibility crosswalk markings, signal upgrades, and pedestrian refuge islands-are proposed to reduce pedestrian-vehicle conflicts across all study sites.

<p>The growing global demand for energy and the urgent need to mitigate climate change have made improving building energy efficiency a critical component of sustainable development. Buildings account for a significant share of global energy consumption and carbon emissions, highlighting the importance of effective retrofitting strategies to enhance their performance.</p> <p>This study presents a comprehensive literature review of building retrofitting approaches, encompassing both passive and active measures designed to enhance the sustainability of commercial and residential structures. Key factors influencing energy consumption are identified, and the role of energy-efficient retrofitting in reducing carbon footprints and operational costs is examined. The study also analyzes major barriers to implementation, including financial, technical, and regulatory challenges.</p> <p>Furthermore, the review explores the application of energy simulation tools in optimizing retrofit strategies and presents relevant case studies demonstrating successful implementations. Sector-specific retrofitting strategies are discussed for buildings such as educational facilities, supermarkets, hotels, and retail spaces.</p> <p>Finally, the study highlights future research directions, emphasizing the integration of emerging technologies such as artificial intelligence, smart sensors, and renewable energy systems to further enhance building sustainability. This work provides valuable insights for researchers, policymakers, and practitioners aiming to advance energy-efficient and sustainable building practices.</p>