Abstract

Worldwide 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.

Highlights

  • Over the last decades, we have witnessed a profound digitalization of society helped by the emergence of the Internet of Things (IoT)

  • Scanning the location and the IoT device code Quick Response code (QR) code creates the information needed for the backend to auto-configure

  • In order to handle metadata related to location and devices, dynamic QR codes are proposed and link to a database

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Summary

Introduction

We have witnessed a profound digitalization of society helped by the emergence of the Internet of Things (IoT). The challenges in enabling IoT sensing technology into a building are the complexity of integration and the compatibility of different communication protocols, as well as data security (Vavra, 2018). It increases the complexity to control and manage large-scale IoT solutions, which over the years are becoming more decentralized, heterogeneous, and harder to configure manually.

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