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.
Energy Router, IR Thermography, Augmented Reality, Predictive Maintenance, Design Simulation, Data Mining, Neural Network,Building Information Modeling, Failure Conditions.