Georgios Kormpakis, Panagiotis Kapsalis, Konstantinos A. Psilopanagiotis, Sotiris Pelekis, Evangelos Karakolis, H. Doukas
{"title":"An Advanced Visualisation Engine with Role-Based Access Control for Building Energy Visual Analytics","authors":"Georgios Kormpakis, Panagiotis Kapsalis, Konstantinos A. Psilopanagiotis, Sotiris Pelekis, Evangelos Karakolis, H. Doukas","doi":"10.1109/IISA56318.2022.9904353","DOIUrl":null,"url":null,"abstract":"One of the main challenges of today’s societies is the avoidance of the climate change since the climate crisis in now more evident than ever. Buildings have a large share of total energy consumption and, thus, it is obvious that actions should be taken to reduce their needs. Taking into consideration that nowadays data related to building’s metrics are available in significantly higher rate than in the past, due to the advance of the related technologies, it is necessary to find ways to exploit them in order to draw useful inferences regarding their consumptions and how they can be reduced. For that reason, in this paper we present a Visualisation Engine, which offers a variety of visualisations over stored data. With the usage of the proposed Visualisation Engine, we envision to be able to conduct sufficient research over the data, to generate insightful information regarding their behaviour, and to assist the development of useful solutions towards the direction of more energy efficient buildings.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IISA56318.2022.9904353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
One of the main challenges of today’s societies is the avoidance of the climate change since the climate crisis in now more evident than ever. Buildings have a large share of total energy consumption and, thus, it is obvious that actions should be taken to reduce their needs. Taking into consideration that nowadays data related to building’s metrics are available in significantly higher rate than in the past, due to the advance of the related technologies, it is necessary to find ways to exploit them in order to draw useful inferences regarding their consumptions and how they can be reduced. For that reason, in this paper we present a Visualisation Engine, which offers a variety of visualisations over stored data. With the usage of the proposed Visualisation Engine, we envision to be able to conduct sufficient research over the data, to generate insightful information regarding their behaviour, and to assist the development of useful solutions towards the direction of more energy efficient buildings.