دسته بندی:
بینایی ماشین - Machine vision
سال انتشار:
2022
عنوان انگلیسی مقاله:
Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM
ترجمه فارسی عنوان مقاله:
رویکرد دیجیتال دوقلو برای بهبود بهره وری انرژی در روشنایی داخلی بر اساس بینایی کامپیوتر و BIM پویا
منبع:
ScienceDirect- Elsevier- Energy & Buildings, 270 (2022) 112271: doi:10:1016/j:enbuild:2022:112271
نویسنده:
Yi Tan
چکیده انگلیسی:
Intelligent lighting systems and surveillance systems have become an important part of intelligent buildings. However, the current intelligent lighting system generally adopts independent sensor control and
does not perform multi-source heterogeneous data fusion with other digital systems. This paper fully
considers the linkage between the lighting system and the surveillance system and proposes a digital
twin lighting (DTL) system that mainly consists of three parts. Firstly, a visualized operation and maintenance (VO&M) platform for a DTL system was established based on dynamic BIM. Secondly, the environment perception, key-frame similarity judgment, and multi-channel key-frame cut and merge
mechanism were utilized to preprocess the video stream of the surveillance system in real-time.
Lastly, pedestrians detected using YOLOv4 and the ambient brightness perceived by the environment
perception mechanism were transmitted to the cloud database and were continuously read by the
VO&M platform. The intent here was to aid timely adaptive adjustment of the digital twin and realistic
lighting through the internet. The effectiveness of the proposed method was verified by experimenting
with a surveillance video stream for 14 days. The key results of the experiments are as follows: (1) the
accuracy rate of intelligent decision control reached 95.15%; (2) energy consumption and electricity costs
were reduced by approximately 79%; and (3) the hardware cost and energy consumption of detection
equipment and the time and cost of operation and maintenance (O&M) were greatly reduced.
keywords: Computer vision | Digital Twin | Dynamic BIM | Energy-efficient buildings | Intelligent lighting control
قیمت: رایگان
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