Energy routers are recent topics of interest for scientific community working on alternative energy.
Enabling technologies supporting installation and monitoring energy efficiency in building are discussed in
this paper, by focusing the attention on innovative aspects and on approaches to predict risks and failures
conditions of energy router devices. Infrared (IR) Thermography and Augmented Reality (AR) are
indicated in this work as potential technologies for the installation testing and tools for predictive
maintenance of energy networks, while thermal simulation, image post-processing and data mining
improve the analysis of the prediction process. Image post- processing has been applied on thermal images
and for WiFi AR. Concerning data mining we applied k-Means and Artificial Neural Network –ANNobtaining
outputs based on measured data. The paper proposes some tools procedure and methods
supporting the Building Information Modeling- BIM- in smart grid applications. Finally we provide some
ISO standards matching with the enabling technologies by completing the overview of scenario