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A Web Based Data Processing Concept for Building Diagnostics and Performance Evaluation

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Abstract:

Buildings are responsible for a major amount of the annual energy consumption. A detailed recording and evaluation of building data could provide a deeper understanding of building operation schemes and the corresponding performance. This could help building owners and operators to evaluate and better understand the actual situation. Based on this (real-time) data an optimized operation scheme can be designed and implemented for future time steps. Additionally, a more detailed understanding of the impact of previous building systems interactions will be possible. The building automation industry and the related service provider sector are actually providing proprietary solutions for data logging, visualization and energy optimization. Such solutions are regularly integrated into their own specific software of the used proprietary building management solutions. As an alternative, we suggest an Internet of Things (IoT) and web services inspired concept for the implementation of a generic web service for building diagnostics. Our suggestion encompasses a holistic performance evaluation that considers both the energy consumptions and delivered building service. In this contribution, a general design of a web service based solution is presented and the future possibilities for data access from various sources are discussed. Furthermore, details of actually developed and demonstratively implemented software components for data preprocessing are presented. Data processing examples for different types of data are included and highlight the potential of such web-based approaches. Moreover, possibilities for improved building control by the use of web services for operation schedule generation or model predictive control are illustrated and critically debated.

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Info:

Periodical:

Applied Mechanics and Materials (Volume 887)

Pages:

641-649

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.887.641

Citation:

Cite this paper

Online since:

January 2019

Authors:

Matthias Schuss*, Farhang Tahmasebi, Ardeshir Mahdavi

Keywords:

Building Diagnostic, Building Monitoring, Building Performance, Data Analysis, Embedded Systems, Internet of Things, Software as a Service

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* - Corresponding Author

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