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Project Overview: This NSF-funded project (Award #2019754) is part of the Belmont Forum’s Disaster Risk, Reduction, and Resilience (DR3) initiative, a global effort to assess and mitigate disaster risks through transdisciplinary collaboration. The study investigates strategies to enhance the resilience of low-income communities living in flood-prone and climate-vulnerable regions, with a geographic focus on Brazil, East Africa, and the southeastern United States. The U.S. component centers on coastal and urban communities in Florida, particularly those at risk from flooding and extreme weather events. Research Objectives: Through a transdisciplinary approach, the project integrates machine learning, geospatial analytics, and socio-economic data to: - Assess community-level vulnerabilities to flooding and extreme heat, -Identify barriers to adopting disaster-resilient housing, - Co-design affordable, climate-resilient housing prototypes using sustainable, locally sourced materials. The research aims to support community-informed design strategies and policy recommendations that are adaptable across different socio-economic and geographic contexts. Dataset Description: The dataset contains responses from approximately 500 residents aged 18+ living in low-income, flood-prone neighborhoods in Florida. The survey captures detailed information on: - Housing conditions and infrastructure, - Disaster preparedness and flood risk perception, - Access to services during and after disasters, - Health and economic impacts of extreme weather events, - Community cohesion and recovery strategies. This dataset serves as a resource for researchers, urban planners, emergency response agencies, and policymakers seeking data-driven insights to inform resilient housing design, climate adaptation, and disaster recovery planning. Data Collection and Anonymity: Survey distribution and data collection were conducted in partnership with Centiment, a third-party research company that recruits demographically targeted panels for academic and applied research. For this study, Centiment distributed the survey to residents of low-income, flood-prone communities in Florida, based on geographic and socio-economic criteria specified by the research team. All personally identifiable information (PII), such as IP addresses, email addresses, and precise geolocation data, was removed prior to uploading the dataset to DesignSafe. The dataset has been reviewed to ensure participant anonymity in accordance with DesignSafe data protection policies and applicable ethical standards. 

Abstract The research discussed is part of a Belmont Forum disaster risk reduction project aimed at enhancing the resilience of low-income housing. This paper examines feasibility and viability of using emerging digital technologies to enhance the resilience of low-income housing based on requirements of resource constrained, low-lying coastal areas in East Africa. The authors focus on the need to facilitate data and knowledge sharing across domains to: 1) reduce or avoid the potential property loss from flooding events through mapping the interdependencies and interconnectedness across natural and human systems; 2) coordinate the provision of temporary shelter for displaced victims, and 3) building (back) better during the recovery phase. The deployment of Artificial Intelligence, Internet of Things, BIM, Digital twin, VR/AR in disaster risk management is still an emerging area of research. In general, cutting-edge digital technologies are deployed as standalone solutions to address existing data and knowledge sharing needs that are unique to a sub-group of stakeholders. A more holistic and comprehensive solution will require an integrative framework that supports the seamless flow of information across the stakeholders. We propose to address this need through an artificial intelligence enhanced data, information and knowledge sharing platform that synthesizes content into actionable insights 

There are ongoing research efforts directed at addressing strength limitations of compressed earth blocks (CEB) that inhibit their deployment for structural applications, particularly in areas where masonry systems are regularly subjected to lateral loads from high winds. In this paper, the authors focus specifically on the extent to which polypropylene (PP) fibers can be used to enhance the flexural performance of CEB. Cementitious matrices used for CEB production exhibit low tensile and flexural strength (brittle) properties. This work investigates plain (unreinforced) and fiber-reinforced specimens (short flexural beams) with fiber mass content of 0.2, 0.4, 0.6, 0.8, and 1.0% and ordinary Portland cement (OPC) content of 8%. The influence of the inclusion of fiber was based on tests conducted using the Standard Test Method for Flexural Performance of Fiber-Reinforced Concrete (ASTM C1609). Material properties that were quantified included first-peak strength, peak strength, equivalent flexural strength, residual strength, and flexural toughness. There was an observed improvement in the performance of the soil-fiber matrixes based on these results of these tests. It was also observed that when the fiber content exceeded 0.6% and above, specimens exhibited a deflection- hardening behavior; an indication of improvement in ductility. An equivalent flexural strength predictive model is proposed.