Occupancy driven building performance assessment

Ioannidis, Dimosthenis; Tropios, Pantelis; Krinidis, Stelios; Stavropoulos, George; Tzovaras, Dimitrios; Likothanasis, Spiridon

doi:10.1016/j.jides.2016.10.008

Cited by 20 publications

(8 citation statements)

References 29 publications

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“…Data Mining: Data mining activities are performed to produce useful information from obtained data sources such as databases [46]. Data mining (DM) in the FM industry is essential to generate actionable information in the facility environment [47].…”

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confidence: 99%

“…While supervised learning aims to produce predictions by using data, unsupervised learning is used in group identification and to discover new knowledge from historical data. Ioannidis et al [46] and Yafooz et al [43] mentioned five commonly used DM categories; "anomaly detection/outlier detection, association rule learning, clustering analysis, classification analysis, and regression analysis". In anomaly detection, the outliers are identified by comparing expected patterns.…”

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confidence: 99%

“…Visual analytics contain informative answers for "what is happening", "what happened" and "what will happen" [45]. Ioannidis et al [46] identified nine visualization techniques from literature; "1D to 3D graphics, geometric techniques, pixel oriented techniques, iconographic techniques, topic-based methods, feature-based methods, graph layout techniques, clutter reduction methods, and combinations". The authors expressed that the visualization techniques allow users to explore data more effectively and efficiently than DM results, which are very complex to infer information from for facility managers.…”

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confidence: 99%

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Determination of Business Intelligence and Analytics-Based Healthcare Facility Management Key Performance Indicators

2022

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The use of digital technologies such as Internet of Things (IoT) and smart meters induces a huge data stack in facility management (FM). However, the use of data analysis techniques has remained limited to converting available data into information within activities performed in FM. In this context, business intelligence and analytics (BI&A) techniques can provide a promising opportunity to elaborate facility performance and discover measurable new FM key performance indicators (KPIs) since existing KPIs are too crude to discover actual performance of facilities. Beside this, there is no comprehensive study that covers BI&A activities and their importance level for healthcare FM. Therefore, this study aims to identify healthcare FM KPIs and their importance levels for the Turkish healthcare FM industry with the use of the AHP integrated PROMETHEE method. As a result of the study, ninety-eight healthcare FM KPIs, which are categorized under six categories, were found. The comparison of the findings with the literature review showed that there are some similarities and differences between countries’ FM healthcare ranks. Within this context, differences between countries can be related to the consideration of limited FM KPIs in the existing studies. Therefore, the proposed FM KPIs under this study are very comprehensive and detailed to measure and discover healthcare FM performance. This study can help professionals perform more detailed building performance analyses in FM. Additionally, findings from this study will pave the way for new developments in FM software and effective use of available data to enable lean FM processes in healthcare facilities.

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Determination of Business Intelligence and Analytics-Based Healthcare Facility Management Key Performance Indicators

2022

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“…Energy needs are influenced by the building geometry, equipment and user behaviour [218,221]. So far, as a ''proof of concept" [76], BIM models can store all of this information, apart from user behaviour, which lacks research [81,99,104] but, as shown by Baldi et al [227], occupant-building interaction can be automated and help improve overall building performance, opening the door to BIM integration. Moreover, BIM can act as a basis for energy analysis software to estimate a building's energy needs [36,175,194,202].…”

Section: Energy Needs Estimationmentioning

confidence: 99%

Using BIM to improve building energy efficiency – A scientometric and systematic review

Pereira

Santos

Leite

et al. 2021

Energy and Buildings

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“…To demonstrate the need for data and referential integrity, let us consider the example of a building occupancy analysis system [14]. This system collects and analyses large datasets about a building: its' sensors, equipment, energy consumption and occupancy information.…”

Section: Motivating Examplementioning

confidence: 99%

Keeping Data Inter-related in a Blockchain

Chitti

Chitchyan

2019

Lecture Notes in Business Information Processing

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Blockchains are gaining a substantial recognition as an alternative to the traditional data storage systems due to their tamperingresistant and decentralized storage, independence from any centralized authority, and low entry barriers for new network participants. Presently blockchains allow users to store transactions and datasets, however they don't provide an easy way of creating and keeping relationships between data entities. In this paper we demonstrate a solution that helps software developers maintain relationships between inter-related data entities and datasets in a blockchain. Our solution runs over Ethereum's Go implementation. This is the first step towards a database management-like middleware system for blockchains.

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Occupancy driven building performance assessment

Cited by 20 publications

References 29 publications

Determination of Business Intelligence and Analytics-Based Healthcare Facility Management Key Performance Indicators

Determination of Business Intelligence and Analytics-Based Healthcare Facility Management Key Performance Indicators

Using BIM to improve building energy efficiency – A scientometric and systematic review

Keeping Data Inter-related in a Blockchain

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