Generation of BIM data based on the automatic detection, identification and localization of lamps in buildings
This work addresses energy-saving strategies in the building sector by automating lighting infrastructure management, though it appears incremental as it builds on existing BIM and detection methods.
The paper tackles the problem of automatically generating Building Information Modeling (BIM) data for energy management by detecting, identifying, and localizing lamps in buildings using a method that focuses on limited image regions, achieving near-real-time processing with low computational needs.
In this paper we introduce a method that supports the detection, identification and localization of lamps in a building, with the main goal of automatically feeding its energy model by means of Building Information Modeling (BIM) methods. The proposed method, thus, provides useful information to apply energy-saving strategies to reduce energy consumption in the building sector through the correct management of the lighting infrastructure. Based on the unique geometry and brightness of lamps and the use of only greyscale images, our methodology is able to obtain accurate results despite its low computational needs, resulting in near-real-time processing. The main novelty is that the focus of the candidate search is not over the entire image but instead only on a limited region that summarizes the specific characteristics of the lamp. The information obtained from our approach was used on the Green Building XML Schema to illustrate the automatic generation of BIM data from the results of the algorithm.