Evaluating the impact of data quality on the accuracy of the predicted energy performance for a fixed building design using probabilistic energy performance simulations and uncertainty analysis

Ekström, Tomas; Burke, Stephen; Wiktorsson, Magnus; Hassanie, Samer; Harderup, Lars-Erik; Arfvidsson, Jesper

doi:10.1016/j.enbuild.2021.111205

Cited by 21 publications

(3 citation statements)

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“…A common theme in all these studies is that the sensors used do not have a standardized way of describing the data they produce, even if they refer to the same physical properties. The management of the content and quality of the data produced in Smart Cities and buildings is not standardized, leading to challenges when it comes to their integration, usage and interpretation [13][14][15][16]. In fact, the authors of [17] have proposed that the integration of IoT data in Building Infrastructure Management:…”

Section: Literature Reviewmentioning

confidence: 99%

Smart Cities as Hubs: A Use Case in Public School Buildings

Nikolaou,

Anthopoulos

2024

Buildings

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Contextual data are receiving increasing attention in Smart Cities as they enable the development and delivery of smart services for their citizens. The homogenization of contextual data flows has become an important topic for standardization bodies as they attempt to enable data flow control and vendor-independent solutions. Buildings are a critical component of cities, due to their role in several dimensions of Smart Cities (including the United Nations Sustainable Development Goals); these may include the monitoring of their operation, maintenance, energy consumption, ability to respond in emergencies, and people flows, all of which affect the sustainability of a Smart City’s ecosystem. In this respect, Building Information Management Systems and Building Infrastructure Management Systems can benefit from this standardization. This paper presents how a novel solution named Smart-City-as-Hub can homogenize building contextual data and enable smart services’ development and delivery based on these data. The analysis of the data from several IoT deployments in public school buildings is the method used to highlight the segmentation and fragmentation of the IoT landscape and to present the benefits that the Smart-City-as-Hub provides in this context. The ways in which the Smart-City-as-Hub concept can mitigate these challenges and enable Smart City stakeholders to concentrate their efforts on developing value-added services is presented in the discussion section. By providing real-life data of the IoT devices deployed in Smart City projects, this study aims to further advance research pursuing the homogenization and standardization of Smart City flows.

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Section: Literature Reviewmentioning

confidence: 99%

Smart Cities as Hubs: A Use Case in Public School Buildings

Nikolaou,

Anthopoulos

2024

Buildings

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“…Model simulation analyses are increasingly being conducted in many contexts, such as in medical studies on explaining a system or examining how the system will look in the future or how it behaved in past times (See, e.g., Greenberg et al, 2022;Shi et al, 2022;Wallett et al, 2022). The accuracy of the simulation outcomes, however, is a much-debated issue; but there is little doubt that it depends to a large extent on the quality of the input data (Ekström et al (2021), defined here as 'a measure of the condition of data with regard to factors such as completeness, consistency, accuracy and reliability, and whether or not it is up-to-date' (Hassenstein and Vanella, 2022). These were therefore the factors taken into account (in the present critical overview) in compiling the geomedically relevant attributes of Hg, making use of the most authentic and up-to-date sources of reference available as of 2022/2023.…”

Section: Mercury Simulation Modellingmentioning

confidence: 99%

“…A number of important studies have recently been conducted on the development of a general model to assess the impact of data quality on the accuracy of model output (See, e.g., Hasan and Padman, 2006;Ekström et al, 2021;Wang et al, 2023). Indeed, as Forbus and Berleant (2022) recently retorted: "A simulation model output is only as good as the data input that drives it, and without taking the time to ensure quality input data, the output may not yield usable results."…”

Section: Mercury Simulation Modellingmentioning

confidence: 99%

An updated review of the salient geomedical aspects of mercury for enhancement of data quality in simulation modelling and other prognostic applications: Africa case descriptions

Davies

2023

Front. Anal. Sci.

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Mercury (Hg) pollution is of global concern. Despite the prolificity of research in the past two decades or so, there are still several uncertainties and variabilities in our knowledge of both the element’s exposure dynamics and its health effects. Understanding the intricacies of the element’s emissions-to-impact path, for instance, is rendered intractable by its varied environmental fate and the overarching influence of environmental, geochemical, biological and socioeconomic drivers. In this paper, an updated synopsis of the relevant and more important geomedical characteristics of Hg is considered to constitute part of the provision of high-quality input data needed in Hg simulation modelling studies, and other applications such as the provision of long-term data necessary for evaluating the effectiveness of regulatory measures at various scales. A critical overview is presented on the importance of data quality in parameterisation, and validation of Hg simulation models and other related applications. In this connection, the dearth of modern measurements of Hg abundance in crustal rocks and other Earth materials which needs to be set prior to simulation as well as in modelling source to sink transfers in the Hg cycle, is highlighted. An improved input data quality would also foster the production of model outcomes that are accurate enough for applications in design of better exposure-limiting strategies; and in providing insights on how the course of diagnosis and treatment currently proffered by physicians for Hg-induced maladies, can be revised or expanded. Model results derived from high-quality input datasets also have a high potential for providing forecasting capabilities to inform policy.

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