Cloud Computing and Internet of Things Concepts Applied on Buildings Data Analysis

Florin-Adrian Hebean 1  and Sorin Caluianu 2
  • 1 PhD Student, Technical University of Civil Engineering Bucharest, Faculty of Building Services, , Bucharest, Romania
  • 2 Professor – PhD Director, Technical University of Civil Engineering, Bucharest, Romania

Abstract

Used and developed initially for the IT industry, the Cloud computing and Internet of Things concepts are found at this moment in a lot of sectors of activity, building industry being one of them. These are defined like a global computing, monitoring and analyze network, which is composed of hardware and software resources, with the feature of allocating and dynamically relocating the shared resources, in accordance with user requirements. Data analysis and process optimization techniques based on these new concepts are used increasingly more in the buildings industry area, especially for an optimal operations of the buildings installations and also for increasing occupants comfort. The multitude of building data taken from HVAC sensor, from automation and control systems and from the other systems connected to the network are optimally managed by these new analysis techniques. Through analysis techniques can be identified and manage the issues the arise in operation of building installations like critical alarms, nonfunctional equipment, issues regarding the occupants comfort, for example the upper and lower temperature deviation to the set point and other issues related to equipment maintenance. In this study, a new approach regarding building control is presented and also a generalized methodology for applying data analysis to building services data is described. This methodology is then demonstrated using two case studies.

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  • [1]. Kevin, A. (2009, June). That ‘Internet of Things’ Thing. Retrieved October 10, 2017, from http://www.rfidjournal.com/articles/view?4986

  • [2]. Sethi, P. & Sarangi, S. (2017, January). Internet of Things: Architectures, Protocols and Applications. Journal of Electrical and Computer Engineering. Volume 2017 (2017), 1-25. Retrieved October 09, 2017, from Hindawi database on the World Wide Web: https://doi.org. DOI: 10.1155/2017/9324035

  • [3]. Iserman, R.(2005). Model-based fault-detection and diagnosis - status and applications. Annual Reviews in Control, 29(1), 71-85. DOI: 10.1016/j.arcontrol.2004.12.002

  • [4]. Petze, J. (2017, April). Analytics Software for a World of Smart Devices. Retrieved October 07, 2017, from https://skyfoundry.com/file/8/SkySpark-Overview-Brochure.pdf

  • [5]. Harbor Research (2016, August). The Future of Smart Systems and IoT Analytics. Retrieved October 05, 2017 from https://skyfoundry.com/file/218/Harbor-Research---The-Future-of-IoT-Analytics.pdf

  • [6]. Project Haystack Standard (2013). Project Haystack Open Source Data Modeling Standard. v2013-10-1. Glen Allen

  • [7]. Guarino, N. (1997). Understanding, building and using ontologies. International Journal of Human-Computer Studies, 46(2-3), 293-310. DOI: 10.1006/ijhc.1996.0091

  • [8]. Charpenay, V. (2015, November). Haystack tagging ontology. Retrieved October 02, 2017 from http://vcharpenay.github.io/hto/

  • [9]. Wurfel, L., Blokker, S. & Fry,J. (2014). Applying data science to property. Retrieved October 11, 2017 from http://docplayer.net/43491736-Applying-data-science-to-property.html

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