UCL Discovery Stage
UCL home » Library Services » Electronic resources » UCL Discovery Stage

Enabling scalable deployment of data-driven applications across building portfolios

Mavrokapnidis, Dimitris; (2023) Enabling scalable deployment of data-driven applications across building portfolios. In: Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference. (pp. pp. 1-4). European Council for Computing in Construction Green open access

[thumbnail of EC32023_342.pdf]
Preview
PDF
EC32023_342.pdf - Published Version

Download (975kB) | Preview

Abstract

Despite the promising benefits of data-driven applications to improve building performance, they are still developed on an ad-hoc basis, mainly due to the burden of discovering and reusing building data across deployment sites. Recent efforts in semantic data modelling aim to overcome these barriers, though application development remains building-specific, leading to bespoke configurations that cannot scale. This research seeks to establish a new regime of data-driven applications that are developed once and run across multiple buildings — similarly to the applications we download and use in our mobile phones. This research contributes to realising this vision in two ways: introducing (a) a method for automatic building metadata model generation through the lifecycle, and (b) a portable application development paradigm that offsets the burden of configuration in the authoring process. An overview of this vision and contributions are illustrated in Figure 1. These advancements are expected to overcome expertise barriers, reduce time for applications’ configuration and deployment, and thus, accelerate their adoption at scale.

Type: Proceedings paper
Title: Enabling scalable deployment of data-driven applications across building portfolios
Event: 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference
Open access status: An open access version is available from UCL Discovery
DOI: 10.35490/ec3.2023.342
Publisher version: http://www.doi.org/10.35490/EC3.2023.342
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: Building Information Modelling, Data Analytics, Semantic Web Technologies, Smart Buildings, Scalability
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10173508
Downloads since deposit
160Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item