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Utilising Latent Data in Smart Buildings: A Process Model to Collect, Analyse and Make Building Data Accessible for Smart Industries
2017
Position Papers of the 2017 Federated Conference on Computer Science and Information Systems
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Also, this paper elaborates on two industrial use-cases to demonstrate how having access to the building information effectively affects the other industries. ...
information with live data captured from various sources. ...
ACKNOWLEDGMENT This work was supported by the Science Foundation Ireland grant "13/RC/2094" and co-funded under the European Regional Development Fund through the Southern & Eastern Regional Operational ...
doi:10.15439/2017f545
dblp:conf/fedcsis/PourzolfagharH17
fatcat:ku2pyzxlijfuvbutldq43lrkni
Towards green building performance evaluation using asset information modelling
2015
Built Environment Project and Asset Management
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This framework considers emerging requirements for the capture of Building Performance Attribute Data (BPAD), and describes how these can be managed in order to assist with effective post-construction ...
Originality value -A conceptual framework is generated that proposes the use of effective information management and aggregation of building performance attribute data within an Asset Information Model ...
Figure 3 - 3 The information model development process(adapted from PAS 1192-2:2013, p-viii, and effective tracking in AIM
involved in two separate BIM storm events facilitated by The BIM Academy ...
doi:10.1108/bepam-03-2014-0020
fatcat:upxl6tvq5resxk4xafgrluzdfm
Rapid clustering of colorized 3D point cloud data for reconstructing building interiors
2010
2010 International Symposium on Optomechatronic Technologies
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At this scanning stage, the shape capturing process should aim at minimizing the density variations, so that point-based visualization can effectively be used for quick quality evaluation of the captured ...
A movable mechanism (Figure 1 ) helps in synchronizing the coordinate systems of these two shape capturing systems. ...
doi:10.1109/isot.2010.5687331
fatcat:in5ilyflandkte6gptkimlg3yq
Automatic Assessment of Buildings Location Fitness for Solar Panels Installation Using Drones and Neural Network
2021
CivilEng
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Transfer learning on the CNN is used to classify roofs of buildings into two categories of shaded and unshaded. ...
The model presented in this paper can be used to prioritize the buildings based on the likelihood of getting benefits from switching to solar energy. ...
Stage Two: Data Capturing and Image Annotation To collect data, the researchers suggest flying a drone over the area of interest for 30-60 min to capture a high-resolution video of the buildings under ...
doi:10.3390/civileng2040056
fatcat:pkfj3ijaird5tjoji3wzz6nlsy
Reality Capture of Buildings Using 3D Laser Scanners
2021
CivilEng
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How does laser scanning fit with other wider emerging technologies such as building information modeling (BIM)? ...
Some of these include the role of 3D laser scanners in capturing and processing raw construction project data. How accurate are the 3D laser scanner or point cloud data? ...
Cloud-based registration was utilized in registering the cloud points, the registration was conducted through two stages. ...
doi:10.3390/civileng2010012
fatcat:y4kpg5wifzc2fnisurv2entf3y
Evaluation of Land Value Capture for Financing Transportation Infrastructure Development in Sri Lankan Cities.pdf
2021
figshare.com
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As the next stage it analysed the property value impacts through the hedonic pricing method. ...
By applying this theory, a four-step framework was introduced and validated through the case of Kottawa – Makubura Multi Model Transport Centre Development (MMC) and highway development projects. ...
in Overall Distance Buffers Source: Adopted by Author Based on Survey Data
Model two represented the post construction stage in overall distance buffers. ...
doi:10.6084/m9.figshare.13515914.v1
fatcat:pkoofdhc4nfh7fhzm5v2ek5ava
Digital twin-based progress monitoring management model through reality capture to extended reality technologies (DRX)
2021
Smart and Sustainable Built Environment
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/methodology/approachIDEF0 data modeling method has been designed to establish an integration of reality capturing technologies by using BIM, DTs and XR for automated construction progress monitoring. ...
PurposeThe purpose of this research is to develop a generic framework of a digital twin (DT)-based automated construction progress monitoring through reality capture to extended reality (RC-to-XR).Design ...
This data can be 3D stereoscopic or 2D, or a mix of the two. ...
doi:10.1108/sasbe-01-2021-0016
fatcat:msu6gdd6o5fxldxtzhhu3jeeqm
Life-Stage Modeling by Customer-Manifold Embedding
2017
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
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The customer-manifold allows us to train a static prediction model that captures dynamic customer behavior patterns. ...
Although this phenomena has been recognized previously, very few studies tried to model the life-stage and make use of it. ...
temporal effects in the models. ...
doi:10.24963/ijcai.2017/455
dblp:conf/ijcai/YangYZ17
fatcat:l6457f32vbenhjegrdfftlpxl4
Information Fusion for Cultural Heritage Three-Dimensional Modeling of Malay Cities
2020
ISPRS International Journal of Geo-Information
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The results showed that fusing photogrammetry and laser scanning can effectively capture the architectural uniqueness of Malay buildings, including specific façade geometries on walls, roofs, and motifs ...
In this study, we fused drone images and range data from a laser scanner to construct a high-resolution three-dimensional GIS city model for one traditional Malay settlement located in Malaysia. ...
Quality correlation between the two details can be helpful for achieving objectives through the use of compatible data sources. ...
doi:10.3390/ijgi9030177
fatcat:elt5ctqchrh4bfmf4axs3oslmy
An autoencoder-based deep learning approach for clustering time series data
2020
SN Applied Sciences
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This paper introduces a two-stage deep learning-based methodology for clustering time series data. ...
The paper reports a case study in which the selected financial and stock time series data of over 70 stock indices are clustered into distinct groups using the introduced two-stage procedure. ...
The algorithms The introduced autoencoder-based deep learning methodology for time series clustering is represented through two algorithms: (1) Transforming unsupervised data into supervised through building ...
doi:10.1007/s42452-020-2584-8
fatcat:ebtmxxqftzbo7bbm3abpju43sm
Investigating Approaches of Integrating BIM, IoT, and Facility Management for Renovating Existing Buildings: A Review
2021
Sustainability
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This approach is based on the integration of Building Information Modeling (BIM) with real-time data from IoT devices aiming at improving construction and operational efficiencies and to provide high-fidelity ...
The first step to better integrating IoT and Building Information Modeling (BIM) can be performed by implementing the Service-Oriented-Architecture (SOA) to combining software and other services by replacing ...
Stage 2: Gathering BIM and Live Data Stage Two includes proposing various sub-processes aiming at capturing the building information and the live data from various sources such as reports and IoT devices ...
doi:10.3390/su13073930
fatcat:5con44dqrbhv3pjkwdncots2ey
Abnormal activity capture from passenger flow of elevator based on unsupervised learning and fine-grained multi-label recognition
[article]
2020
arXiv
pre-print
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We present a work-flow which aims at capturing residents' abnormal activities through the passenger flow of elevator in multi-storey residence buildings. ...
Experiment shows effects are there, and the captured records will be directly reported to our customer(property managers) for further confirmation. ...
Anomaly detection with Isolation Forest is a process composed of two main stages: In the first stage, a training data set is used to build isolation trees(iTrees). ...
arXiv:2006.15873v1
fatcat:lhwb3rjrinc3dnu6vynj63r4bm
Automatic Generation of Residential Areas using Geo-Demographics
[chapter]
2008
Lecture Notes in Geoinformation and Cartography
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data. ...
The algorithms main body of work focuses on a classification based system which applies a texture library of captured building instances to extruded and optimised virtual buildings created from 2D GIS ...
Whilst the majority of research is concerned with stages 1 through to 5 the focus is primarily on the building stage and concentrates on creating realistic buildings. ...
doi:10.1007/978-3-540-72135-2_22
fatcat:opdec2s3kvbl7axpje6kju2p4y
Clustering Time Series Data through Autoencoder-based Deep Learning Models
[article]
2020
arXiv
pre-print
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To address this problem, this paper introduces a two-stage method for clustering time series data. ...
In particular, deep learning techniques are capable of capturing and learning hidden features in a given data sets and thus building a more accurate prediction model for clustering and labeling problem ...
Building Feature Vector: Capturing Descriptive MetadataStock market data and their time series can be characterized through two concepts: 1) volatility, and 2) return. ...
arXiv:2004.07296v1
fatcat:tzgyg2t3m5dp7k54gwyq7fgeda
Methodological Aspects of Architectural Documentation
2011
Geoinformatics FCE CTU
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Several technologies are tested ranging from the simplest to the more sophisticated ones, used in the main stages of the documentation project, as follows: work overall planning, data acquisition, processing ...
Over the last decades, many conservation actions have been implemented (legal protection, recovery and restoration works), but none of them have resulted in effective conservation of such property, whether ...
When data acquisition is done by Photogrammetry, data processing consists in processing the photos and other data gathered in the field through the restitution models implemented in software algorithms ...
doi:10.14311/gi.6.5
fatcat:kpaof7ygdrdchdhv7ot3ao4wby
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