Analysis of an energy efficient building design through data mining approach

Kim, Hyun‐Joo; Stumpf, Annette L.; Kim, Wooyoung

doi:10.1016/j.autcon.2010.07.006

Cited by 93 publications

(44 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…BIM has been widely used in various areas such as visualisation and collaboration [18,[49][50][51][52], design optimisation [53][54][55][56], construction planning [8,[57][58][59][60] and maintenance [9,61]. In this paper, BIM is used for providing a visualisation platform and benchmarking model for quality management.…”

Section: Bim-based Real-time Checking Systemmentioning

confidence: 99%

Integrating BIM and LiDAR for Real-Time Construction Quality Control

Wang

Sun

Shou

et al. 2014

J Intell Robot Syst

134

View full text Add to dashboard Cite

In the construction process, real-time quality control and early defects detection are still the most significant approach to reducing project schedule and cost overrun. Current approaches for quality control on construction sites are time-consuming and ineffective since they only provide data at specific locations and times to represent the work in place, which limit a quality manager's abilities to easily identify and manage defects. The purpose of this paper is to develop an integrated system of Building Information Modelling (BIM) and Light Detection and Ranging (LiDAR) to come up with real-time onsite quality information collecting and processing for construction quality control. Three major research activities were carried out systematically, namely, literature review and investigation, system development and system evaluation. The proposed BIM and LiDAR-based construction quality control system were discussed in five sections: LiDAR-based real-time tracking system, BIM-based real-time checking system, quality control system, point cloud coordinate transformation system, and data processing system. Then, the system prototype was developed for demonstrating the functions of flight path control and real-time construction quality deviation analysis. Finally, three case studies or pilot projects were selected to evaluate the developed system. The results show that the system is able to efficiently identify potential construction defects and support real-time quality control.

show abstract

Section: Bim-based Real-time Checking Systemmentioning

confidence: 99%

Integrating BIM and LiDAR for Real-Time Construction Quality Control

Wang

Sun

Shou

et al. 2014

J Intell Robot Syst

134

View full text Add to dashboard Cite

show abstract

“…For example, Kavousian et al [18] studied the energy consumption factors in green homes using classification techniques. Kim et al [19] addressed energy efficient building design using pattern recognition techniques. By using association rule mining techniques, Cheng and Ma [20] explored the LEED credit bundles that could be achieved using the same green building technologies.…”

Section: Methodology Frameworkmentioning

confidence: 99%

A data-driven study of important climate factors on the achievement of LEED-EB credits

Cheng

Lucky

2015

Building and Environment

View full text Add to dashboard Cite

“…A case in point is Kim et al [41], whose research focused on finding basic building elements (windows, walls, floors, etc.) that could significantly improve the energy efficiency.…”

Section: Analysis Of Infrastructures and Retrofittingmentioning

confidence: 99%

Data science for building energy management: A review

Molina-Solana

Ros

Ruiz

et al. 2017

Renewable and Sustainable Energy Reviews

228

108

View full text Add to dashboard Cite

The energy consumption of residential and commercial buildings has risen steadily in recent years, an increase largely due to their HVAC systems. Expected energy loads, transportation, and storage as well as user behavior influence the quantity and quality of the energy consumed daily in buildings. However, technology is now available that can accurately monitor, collect, and store the huge amount of data involved in this process. Furthermore, this technology is capable of analyzing and exploiting such data in meaningful ways. Not surprisingly, the use of data science techniques to increase energy efficiency is currently attracting a great deal of attention and interest. This paper reviews how Data Science has been applied to address the most difficult problems faced by practitioners in the field of Energy Management, especially in the building sector. The work also discusses the challenges and opportunities that will arise with the advent of fully connected devices and new computational technologies.

show abstract

Analysis of an energy efficient building design through data mining approach

Cited by 93 publications

References 3 publications

Integrating BIM and LiDAR for Real-Time Construction Quality Control

Integrating BIM and LiDAR for Real-Time Construction Quality Control

A data-driven study of important climate factors on the achievement of LEED-EB credits

Data science for building energy management: A review

Contact Info

Product

Resources

About