Abstract
Buildings have an untapped efficiency potential, being, on many occasions, government buildings present the most significant potential for energy savings. With the help of building energy management systems, this potential can be exploited, but due to the high cost that represents the implementation of these systems are not used in many buildings. This article aims to present a low-cost building energy management system based on Internet of Things technologies that can help take advantage of the efficiency potential that buildings have. The system implemented in this investigation consisted of a monitoring system that monitored different variables in real-time such as temperature, humidity, air quality, luminous intensity, and energy consumption. This system was implemented in a government building in the Dominican Republic, where the results showed opportunities for improvement. Many of these opportunities for improvement were impossible to know before the system implementation because there was no practical way to monitor them.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
de la Cruz-Lovera, C., Perea-Moreno, A.-J., de la Cruz-Fernández, J.-L., Alvarez-Bermejo, J., Manzano-Agugliaro, F.: Worldwide research on energy efficiency and sustainability in public buildings. Sustainability 9(8), 1294 (2017). https://doi.org/10.3390/su9081294
Sheikhnejad, Y., Gonçalves, D., Oliveira, M., Martins, N.: Can buildings be more intelligent than users? - The role of intelligent supervision concept integrated into building predictive control. Energy Rep. 6, 409–416 (2020). https://doi.org/10.1016/j.egyr.2019.08.081
Sun, Y., Haghighat, F., Fung, B.C.M.: A review of the state-of-the-art in data-driven approaches for building energy prediction. Energy Build. 221, 110022 (2020). https://doi.org/10.1016/j.enbuild.2020.110022
Vishwanath, A., Chandan, V., Saurav, K.: An IoT-based data-driven precooling solution for electricity cost savings in commercial buildings. IEEE Internet Things J. 6(5), 7337–7347 (2019). https://doi.org/10.1109/JIOT.2019.2897988
Bonilla, D., Samaniego, M.G., Ramos, R., Campbell, H.: Practical and low-cost monitoring tool for building energy management systems using virtual instrumentation. Sustain. Cities Soc. 39, 155–162 (2018). https://doi.org/10.1016/j.scs.2018.02.009
Doukas, H., Patlitzianas, K.D., Iatropoulos, K., Psarras, J.: Intelligent building energy management system using rule sets. Build. Environ. 42(10), 3562–3569 (2007). https://doi.org/10.1016/j.buildenv.2006.10.024
Sheng, T.J., et al.: An Internet of Things based smart waste management system using LoRa and tensorflow deep learning model. IEEE Access 8, 148793–148811 (2020). https://doi.org/10.1109/ACCESS.2020.3016255
Al-Ali, A.R., Zualkernan, I.A., Rashid, M., Gupta, R., Alikarar, M.: A smart home energy management system using IoT and big data analytics approach. IEEE Trans. Consum. Electron. 63(4), 426–434 (2017). https://doi.org/10.1109/TCE.2017.015014
Hossain, M., Weng, Z., Schiano-Phan, R., Scott, D., Lau, B.: Application of IoT and BEMS to visualise the environmental performance of an educational building. Energies 13(15), 4009 (2020). https://doi.org/10.3390/en13154009
Linder, L., Vionnet, D., Bacher, J.-P., Hennebert, J.: Big building data - a big data platform for smart buildings. Energy Procedia 122, 589–594 (2017). https://doi.org/10.1016/j.egypro.2017.07.354
Bala, R., Aravind, S.: Towards the implementation of IoT for environmental vStatus Verification in homes. Indian J. Public Heal. Res. Dev. 10(8), 591 (2019). https://doi.org/10.5958/0976-5506.2019.01950.8
Stavropoulos, T.G., Tsioliaridou, A., Koutitas, G., Vrakas, D., Vlahavas, I.: System architecture for a smart university building. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds.) ICANN 2010. LNCS, vol. 6354, pp. 477–482. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15825-4_64
Lehrer, D., Vasudev, J.: Visualizing Energy Information in Commercial Buildings: A Study of Tools, Expert Users, and Building Occupants. Final Report to California Energy Commission Program, pp. 41-p (2011)
Rahman, A., Nasir, M.K., Rahman, Z., Mosavi, A., Shahab, S., Minaei-Bidgoli, B.: DistBlockBuilding: a distributed blockchain-based SDN-IoT network for smart building management. IEEE Access 8, 140008–140018 (2020). https://doi.org/10.1109/ACCESS.2020.3012435
Xing, L., Jiao, B., Du, Y., Tan, X., Wang, R.: Intelligent energy-saving supervision system of urban buildings based on the internet of things: a case study. IEEE Syst. J. 14(3), 4252–4261 (2020). https://doi.org/10.1109/JSYST.2020.2995199
AirNow: AQI Basics|AirNow.gov (2019)
Superintendencia de Electricidad, de la C. Calidad, I.D.: Codigo Eléctrico Nacional de la República Dominicana. SIE-056-2016-MEMI. Santo Domingo, Distrito Nacional (2016). https://sie.gob.do/images/sie-documentos-pdf/marco-legal/resoluciones-sie/2016/RESOLUCIONSIE-056-2016-MEMIEMISIONCODIGOELECTRICONACIONAL-1-_merged2_merged2.pdf
Acknowledgment
Ministerio de Trabajo (MT) of the Dominican Republic for allowing this case study to be carried out in one of its service areas, in addition to the complementary information on the selected area.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Aybar-Mejía, M., Mariano-Hernández, D., Marte, J.C., Contreras, A., Arias, J. (2022). Integration of Internet of Things Technologies in Government Buildings Through Low-Cost Solutions. In: Nesmachnow, S., Hernández Callejo, L. (eds) Smart Cities. ICSC-Cities 2021. Communications in Computer and Information Science, vol 1555. Springer, Cham. https://doi.org/10.1007/978-3-030-96753-6_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-96753-6_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96752-9
Online ISBN: 978-3-030-96753-6
eBook Packages: Computer ScienceComputer Science (R0)