Author:
Madsen Simon Soele,Santos Athila Quaresma,Jørgensen Bo Nørregaard
Abstract
AbstractWorldwide buildings are responsible for about 40% of the overall consumption and contribute to an average of 30% percent of the global carbon emissions. Nevertheless, most current buildings lack efficient energy management systems because such solutions are very expensive, especially when necessary instrumentation needs to be installed after the building’s construction. As an alternative, we purpose the use of IoT sensor networks to retrofit existing medium and large-sized buildings to provide energy management capabilities in a cost-effective way. An IoT network auto-configuration platform for building energy management was developed. In order to efficiently manage metadata related to location and devices, a database using dynamic QR codes was created. Furthermore, we discuss the potential and shortcomings of different sensor-gateway pairing strategies that are applicable to an auto-configuring system. Lastly, we share our implementation of these concepts and demonstrate their use in a medium-sized building case study. The results show a trade-off between optimal configuration and total configuration time with a focus on the quality of the communication signal strength. The proposal provided the necessary automation for a cost-effective energy management system that can be deployed in both new constructions and existing buildings.
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Energy Engineering and Power Technology,Information Systems
Reference58 articles.
1. Agoulmine, N., Balasubramaniam, S., Botvitch, D., Strassner, J., Lehtihet, E., Donnelly, W.: Challenges for Autonomic Network Management, (2006). https://repository.wit.ie/744/1/MACE2006-final.pdf. [Online: Accessed 1 Apr 2021]
2. Alaya MB, Matoussi S, Monteil T, Drira K (2012) Autonomic computing system for self-management of machine-to-machine networks. In: Proceedings of the 2012 International Workshop on Self-Aware Internet of Things. Self-IoT, vol 12. Association for Computing Machinery, New York, pp 25–30. https://doi.org/10.1145/2378023.2378029
3. Alaya MB, Monteil T (2015) Frameself: an ontology-based framework for the self-management of machine-to-machine systems. Concurr Comput Pract Exper 27(6):1412–1426. https://doi.org/10.1002/cpe.3168
4. Amasyali K, El-Gohary NM (2018) A review of data-driven building energy consumption prediction studies. Renew Sust Energ Rev 81:1192–1205. https://doi.org/10.1016/j.rser.2017.04.095
5. Ashraf QM, Habaebi MH (2015) Introducing autonomy in internet of things, recent advances in computer science, pp 215–221, ISBN 9781618042972
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