Building Internet of Things-Enabled Digital Twins and Intelligent Applications Using a Real-time Linked Dataspace

Open Access


Smart environments have emerged in the form of smart cities, smart buildings, smart energy, smart water, and smart mobility. A key challenge in delivering smart environments is creating intelligent applications for end-users using the new digital infrastructures within the environment. In this chapter, we reflect on the experience of developing Internet of Things-based digital twins and intelligent applications within five different smart environments from an airport to a school. The goal has been to engage users within Internet of Things (IoT)-enabled smart environments to increase water and energy awareness, management, and conservation. The chapter covers the role of a Real-time Linked Dataspace to enable the creation of digital twins, and an evaluation of intelligent applications.


Decision support Internet of Things Intelligent systems Smart environments Energy management Water management Dataspaces 

Copyright information

© The Author(s) 2020

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Authors and Affiliations

  1. 1.National University of Ireland GalwayGalwayIreland
  2. 2.Insight Centre for Data AnalyticsNational University of IrelandGalwayIreland

Personalised recommendations