Building feature extraction based on natural neighborhood decomposable point feature extraction algorithm
DOI:
https://doi.org/10.31449/inf.v48i22.6888Abstract
Intelligent buildings, emerging as a fusion of modern information technology and architectural structures, aim to provide intelligent, comfortable, and efficient building environments. However, the information processing and decision-making processes within intelligent buildings face challenges in dealing with large-scale, complex data for feature extraction. This research introduces a Natural Neighborhood Decomposable Point algorithm, effectively extracting crucial features within intelligent buildings. This extraction supports the decision-making and control processes for intelligence. Experimental results demonstrate that employing this algorithm for registration reduces registration errors by 0.068 mm and 0.021 mm after the first iteration. This outcome validates the algorithm's efficiency in enhancing registration algorithms, maintaining both accuracy and interpretability while extracting data in intelligent building contexts. This algorithm can effectively analyze both local and global features in point cloud data, contributes to enhancing the energy efficiency, comfort, automation, and intelligence management levels within intelligent buildings. It propels innovation and development in intelligent buildings, improves security, and promotes sustainable development.翻译搜索复制
Downloads
Published
How to Cite
Issue
Section
License
I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.
I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.
In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.
I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal. The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.
Copyright © Slovenian Society Informatika
