Abstract
Various green projects were executed to reduce the energy consumption in building sector. In particular, it is necessary to improve the thermal insulation performance of existing residential buildings. Even though it is critical to evaluate the thermal insulation performance in operation and maintenance phase, most of the policies and previous studies have focused on thermal insulation materials and systems in design phase. To address this limitation, this study aimed to develop the framework for evaluating the thermal insulation performance of existing residential buildings using the infrared thermal image and image processing method. Towards this end, this study was conducted in two steps: (i) establishment of the building information and infrared thermal image; and (ii) estimation of the thermal loss areas in building surface using the image processing. The result of this study could help building users and managers to estimate the thermal insulation performance in operation and maintenance phase.
| Original language | English |
|---|---|
| Title of host publication | 32nd International Symposium on Automation and Robotics in Construction and Mining |
| Subtitle of host publication | Connected to the Future, Proceedings |
| Publisher | International Association for Automation and Robotics in Construction I.A.A.R.C) |
| ISBN (Electronic) | 9789517585972 |
| DOIs | |
| Publication status | Published - 2015 |
| Event | 32nd International Symposium on Automation and Robotics in Construction and Mining: Connected to the Future, ISARC 2015 - Oulu, Finland Duration: 2015 Jun 15 → 2015 Jun 18 |
Publication series
| Name | 32nd International Symposium on Automation and Robotics in Construction and Mining: Connected to the Future, Proceedings |
|---|
Other
| Other | 32nd International Symposium on Automation and Robotics in Construction and Mining: Connected to the Future, ISARC 2015 |
|---|---|
| Country/Territory | Finland |
| City | Oulu |
| Period | 15/6/15 → 15/6/18 |
Bibliographical note
Funding Information:Acknowledgements: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP; Ministry of Science, ICT & Future Planning) (NRF-2012R1A2A1A01004376).
All Science Journal Classification (ASJC) codes
- Building and Construction
- Artificial Intelligence
- Civil and Structural Engineering
- Hardware and Architecture
