Building heating technology in Smart Home using PI System management tools

Vaňuš, Jan; Vojcinak, Petr; Martínek, Radek; Kelnar, Michal; Macháček, Zdeněk; Bilík, Petr; Koziorek, Jiří; Žídek, Jan

doi:10.1016/j.pisc.2015.11.019

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…The visualization of control and regulation of the operating and technical functions in the building (HVAC, blinds, lighting, etc.) and storage of the measured data in the database was created using DESIGO Insight software tools [49]. To unify the monitoring and control of various automation and electronic systems into a single environment, it is necessary to use a software tool that allows you to consolidate several types of bus systems, standards and communication, and data protocols into o single monitoring application.…”

Section: Description Of Used Technologies In Shcmentioning

confidence: 99%

Using the IBM SPSS SW Tool with Wavelet Transformation for CO2 Prediction within IoT in Smart Home Care

Vaňuš

Kubíček

Gorjani

et al. 2019

Sensors

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Standard solutions for handling a large amount of measured data obtained from intelligent buildings are currently available as software tools in IoT platforms. These solutions optimize the operational and technical functions managing the quality of the indoor environment and factor in the real needs of residents. The paper examines the possibilities of increasing the accuracy of CO2 predictions in Smart Home Care (SHC) using the IBM SPSS software tools in the IoT to determine the occupancy times of a monitored SHC room. The processed data were compared at daily, weekly and monthly intervals for the spring and autumn periods. The Radial Basis Function (RBF) method was applied to predict CO2 levels from the measured indoor and outdoor temperatures and relative humidity. The most accurately predicted results were obtained from data processed at a daily interval. To increase the accuracy of CO2 predictions, a wavelet transform was applied to remove additive noise from the predicted signal. The prediction accuracy achieved in the selected experiments was greater than 95%.

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Section: Description Of Used Technologies In Shcmentioning

confidence: 99%

Using the IBM SPSS SW Tool with Wavelet Transformation for CO2 Prediction within IoT in Smart Home Care

Vaňuš

Kubíček

Gorjani

et al. 2019

Sensors

Self Cite

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“…According to Vanus et al (2016) and Okung-Dike, Dimitra & David (2012), the main aim of the home entertainment and multimedia sub-system is to ensure the clean generation or creation of media contents on-the-fly and also ensure the smooth transmission of contents over multiple networks and media environments. Depending on the compression used, data rates of about 128 kb/s to about 1 Mb/s are required by Audio applications.…”

Section: Home Entertainment and Multimedia Sub-systemmentioning

confidence: 99%

“…The Niagara Framework could therefore be used to reap all the benefits associated with the full integration of IoT in the Smart Home. They can be used to amongst other things save power when rates are low, re-inject saved power into the Home system when power rates are higher or switch to alternate power sources such as solar power, etc (Vanus et al, 2016). A methodology aimed at improving Smart Home Information management through improved device interoperability and network efficiency can also be adopted (Margherita et al, 2013).…”

Section: Product Compatibility and Platform Interoperabilitymentioning

confidence: 99%

A PROPOSED FRAMEWORK FOR SMART HOME SYSTEMS DESIGN & ADOPTION

Oluoha¹,

Ebem²

2019

AIMS Research Journal Publication

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The Smart Home concept is an extensive technological concept which have seen a major resurgence in recent years. They are aimed at automating daily living activities, central monitoring and control of the home, power consumption optimization, greater security, and ensuring a healthier living condition among other things. The capabilities of the Smart Home are further enhanced when combined with the Internet of Things (IoT) and cutting edge technologies such as embedded artificial intelligence. However, the Smart Home design is beset by a number of issues including a lack of universal technical standards and platform fragmentation. This paper is aimed at generating operational guidelines and a design framework for Smart Home architecture. An extensive survey of literature is carried out to investigate the general architecture, existing models and designs of the Smart Home System in other to establish how current models impact on the operations of the smart home. We then highlight the major challenges to the smart home architecture and why these exist. Finally, we attempt to discuss what possible solutions can mitigate identified challenges. A general framework is then proposed for the design of smart homes, which helps overcome identified drawbacks to the Smart Home architecture.

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“…It was caused by high prices for power resources as well as by the deterioration of environment " [1]- [5]".…”

Section: Introductionmentioning

confidence: 99%

Information Modelling of Engineering Systems as an Improvement Factor for the Energy Efficiency of Building

Shilov

Shilova

2017

MATEC Web Conf.

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Abstract.The article presents the analysis of the heat power of a heating system in accordance with valid normative documents. It also reveals some other factors influencing both the general heat balance of a building and its microclimate parameters but not taken into account in the analysis. The recommendations have been developed on the improvement of energy efficiency parameters of the buildings. The authors suggest some possible ways of solution of the problem of air-exchange disturbances due to the introduction of automation systems responsible for a continuous monitoring of climatic and micro-climatic conditions as well as for a combined regulation of heat-transfer agent and of fresh air inflow.

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Building heating technology in Smart Home using PI System management tools

Cited by 6 publications

References 6 publications

Using the IBM SPSS SW Tool with Wavelet Transformation for CO2 Prediction within IoT in Smart Home Care

Using the IBM SPSS SW Tool with Wavelet Transformation for CO2 Prediction within IoT in Smart Home Care

A PROPOSED FRAMEWORK FOR SMART HOME SYSTEMS DESIGN & ADOPTION

Information Modelling of Engineering Systems as an Improvement Factor for the Energy Efficiency of Building

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