کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4951344 1441243 2016 13 صفحه PDF سفارش دهید دانلود کنید
عنوان انگلیسی مقاله ISI
Occupancy driven building performance assessment
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موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
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Occupancy driven building performance assessment
چکیده انگلیسی


- Big data analysis of building measurements.
- Building occupancy-based knowledge mining for the building performance assessment.
- Key performance indicators for evaluating the building performance and operation.
- Visual analytics techniques for assessing building performance.
- Heterogeneous building information correlation.

In this paper, we focus on the building performance assessment using big data and visual analytics techniques driven by building occupancy. Building occupancy is a paramount factor in building performance, specifically lighting, plug loads and HVAC equipment utilization. Extrapolation of patterns from big data sets, which consist of building information, energy consumption, environmental measurements and namely occupancy information, is a powerful analysis technique to extract useful semantic information about building performance. To this end, visual analytics techniques are exploited to visualize them in a compact and comprehensive way taking into account properties of human cognition, perception and sense making. Visual Analytics facilitates the detailed spatiotemporal analysis building performance in terms of occupancy comfort, building performance and energy consumption and exploits innovative data mining techniques and mechanisms to allow analysts to detect patterns and crucial point that are difficult to be detected otherwise, thus assisting them to further optimize the building's operation. The presented tool has been tested on real data information acquired from a building located at southern Europe demonstrating its effectiveness and its usability for building managers.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Innovation in Digital Ecosystems - Volume 3, Issue 2, December 2016, Pages 57-69
نویسندگان
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