Naslov
Data Visualization Tool for Smart Buildings HVAC Systems

Autori
Matetić, Iva ; Štajduhar, Ivan ; Wolf, Igor ; Palaić, Darko ; Ljubić, Sandi

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
ICR 2022: Proceedings of the ICR'22 International Conference on Innovations in Computing Research / Daimi, Kevin ; Al Sadoon, Abeer - Cham : Springer, 2022, 444-453

ISBN
978-3-031-14053-2

Skup
2022 International Conference on Innovations in Computing Research (ICR'22)

Mjesto i datum
Atena, Grčka, 29.08.2022. - 31.08.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
HVAC systems ; Smart buildings ; Data analytics ; Monitoring tool

Sažetak
With the expected increase in world population and economic growth, the demand for energy is steadily increasing worldwide. To support the growing exploitation of energy resources, buildings must be made smart enough to use energy efficiently without wasting it. Heating, ventilation, and air conditioning (HVAC) systems consume a lot of energy and hence require effective control and analysis capabilities, which is one of the most important aspects of current smart buildings. If HVAC systems are not properly controlled, this can lead to poor user comfort, high utility bills due to excessive energy consumption, and a negative impact on the environment. This problem is aggravated in the context of hotel buildings. To support the overall energy consumption tracking, we propose a system integration with an analytical web application for data visualization that allows the user to perform an in-depth analysis of the sensory data measured. The motivation for developing the application is primarily to monitor the regulation of the HVAC system by providing an interactive analytical dashboard needed for future smart buildings. The data visualization tool provides a quick and easy way to visualize and compare time-series data. The visualizations provide insight into how different hotel rooms compare, deviations of room temperature from setpoint temperature, data distribution, correlations between sensory data parameters, and the degree of correlation of room temperature compared to other parameters. The application is aimed at a wide range of users, from lay people and hotel staff to data analysts and scientists conducting research in this area.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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