39,463 research outputs found

    Open-source digital technologies for low-cost monitoring of historical constructions

    Get PDF
    This paper shows new possibilities of using novel, open-source, low-cost platforms for the structural health monitoring of heritage structures. The objective of the study is to present an assessment of increasingly available open-source digital modeling and fabrication technologies in order to identify the suitable counterparts of the typical components of a continuous static monitoring system for a historical construction. The results of the research include a simple case-study, which is presented with low-cost, open-source, calibrated components, as well as an assessment of different alternatives for deploying basic structural health monitoring arrangements. The results of the research show the great potential of these existing technologies that may help to promote a widespread and cost-efficient monitoring of the built cultural heritage. Such scenario may contribute to the onset of commonplace digital records of historical constructions in an open-source, versatile and reliable fashion.Peer ReviewedPostprint (author's final draft

    Developing a distributed electronic health-record store for India

    Get PDF
    The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

    Wastewater-based epidemiology in hazard forecasting and early-warning systems for global health risks

    Get PDF
    With the advent of the SARS-CoV-2 pandemic, Wastewater-Based Epidemiology (WBE) has been applied to track community infection in cities worldwide and has proven succesful as an early warning system for identification of hotspots and changingprevalence of infections (both symptomatic and asymptomatic) at a city or sub-city level. Wastewater is only one of environmental compartments that requires consideration. In this manuscript, we have critically evaluated the knowledge-base and preparedness for building early warning systems in a rapidly urbanising world, with particular attention to Africa, which experiences rapid population growth and urbanisation. We have proposed a Digital Urban Environment Fingerprinting Platform (DUEF) – a new approach in hazard forecasting and early-warning systems for global health risks and an extension to the existing concept of smart cities. The urban environment (especially wastewater) contains a complex mixture of substances including toxic chemicals, infectious biological agents and human excretion products. DUEF assumes that these specific endo- and exogenous residues, anonymously pooled by communities’ wastewater, are indicative of community-wide exposure and the resulting effects. DUEF postulates that the measurement of the substances continuously and anonymously pooled by the receiving environment (sewage, surface water, soils and air), can provide near real-time dynamic information about the quantity and type of physical, biological or chemical stressors to which the surveyed systems are exposed, and can create a risk profile on the potential effects of these exposures. Successful development and utilisation of a DUEF globally requires a tiered approach including: Stage I: network building, capacity building, stakeholder engagement as well as a conceptual model, followed by Stage II: DUEF development, Stage III: implementation, and Stage IV: management and utilization. We have identified four key pillars required for the establishment of a DUEF framework: (1) Environmental fingerprints, (2) Socioeconomic fingerprints, (3) Statistics and modelling and (4) Information systems. This manuscript critically evaluates the current knowledge base within each pillar and provides recommendations for further developments with an aim of laying grounds for successful development of global DUEF platforms

    Big data for monitoring educational systems

    Get PDF
    This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

    Preventing and Mitigating Natural Disasters

    Get PDF
    This report highlights the importance of developing and sharing information on natural hazards, ensuring that the disaster-management community, decision-makers and the public understand the risks posed by these hazards and recognize the onset of hazardous weather and its impact on safety and survival procedures. Educational levels: High school, Undergraduate lower division, Undergraduate upper division, Graduate or professional, Informal education, General public

    Integrated Sensor Fusion Device with an Optimized Mathematical Model to Monitor Civil Engineering Structures

    Get PDF
    Integrated sensor fusion is a new technique in which multiple sensors intelligently combine data to support application or system performance improvement software. With this method, many sensors combine data for accurate position and orientation information to overcome the inadequacy of each sensor. Data consolidation can be described as measuring the state of an entity as a mixture of data or information. This multidisciplinary field has several advantages, including increased confidence, reliability, and reduced ambiguity when measuring company conditions in engineered systems. This paper discusses the various applications of data fusion in civil engineering in recent years, and puts forward some potential advantages of data fusion in civil engineering. Mathematical modeling (MM) is the skill to transform challenges from application to tractable mathematical formulations that provide insight, answers, and instructions in the theoretical and numerical analysis of the original application. This article presented an integer linear programming mathematical model to divide building activities in a project to solve building planning problems. MMCE (Mathematical Modeling Conceptual Evaluation) introduced it to complete an accurate and quick estimation of civil systems such as traffic networks, structural systems, and building projects, becoming more and more achievable through omnipresent sensor networks and communications systems. By assessing the condition of the system, it can make better decisions more rapidly and better. This has enormous value and a variety of impacts. Fusion data is an essential element of system status assessment. Applications and needs for research are underlined for the future
    • …
    corecore