## 2 Background  
Augmented reality is undoubtedly one of the technologies that will transform the way human beings interact with their environment. This technology essentially consists of superimposing virtual elements over real objects on the screen, to give added value and enrich the interaction with reality. There are different fields where AR is currently applied allowing the user to have a more real experience, that is, video-game, museums, and education. Furthermore, AR has grown up enough to have been successfully applied in distinct industrial and commercial environments, such in smart factories [5], building management systems (BMS) [6], aerospace, and automobile industry [7]. AR has also been employed in power system substation environments in the works of [8; 9]; in both papers, AR is used in simulation-based training. Applications applying AR to support data visualization in the infrastructure sector are spreading [7]. One reason is that AR annotations are one of the most efficient and intuitive ways to provide contextualized information about objects in real environments, as they appear in the same place as the object in question [8]. The most determining aspects of the design of an industrial AR system for the Industry 4.0 shipyard case were studied in the work of [10], including the ultimate technologies and the most relevant research and developments for the shipbuilding industry. A report on functional requirements for AR suppliers was recently published in order to improve performance and efficiency in different activities related to operation and maintenance engineering [11]. These guidelines will help develop products for industrial users, thus accelerating tasks by enabling the immediate access in the field to real-time data, maintenance manuals, instructions guide, schemes, and so on.  
On the other hand, MAR can provide \"emotional fit\" as the ability to provide an aesthetically pleasing experience for specific shopping behaviors [12]. In a recent paper, MAR enables people to compare the embodied carbon footprints in cereals and bottled water at a grocery store [13]. However, none of the mentioned papers are related to the visualization aspects of energy information for customers. In this work, the aim is to raise a MAR system for users to visualize, in near real-time, the energy consumption of their household appliances as well as additional power quality (PQ) parameters. This application will provide users with a powerful tool to understand their residential energy consumption, helping them follow different strategies to reduce electricity consumption and, therefore, to reduce the bill. The recently published paper [14] presents a user-friendly monitoring system for power awareness based on IoT and AR, however, their measurements come from a traditional smart meter, without performing any measurement related to PQ, nor considering submetering. Having information about PQ can be a determining factor in saving energy and increasing system power capacity. Moreover, in the work of [15], compared with the indicated paper, our great contribution is to make possible the \"granularity\" in the measure of the energy that is offered to the user. So far, the lack of submetering or recording energy consumption \"behind the meter\", for example, at system-level or into individual appliances, has been an insurmountable barrier that prevented knowing how energy was consumed in detail. This work solves this issue by a novel, low-cost IoT sensor for measuring and analyzing PQ at the input of any individual alternating current (AC) appliance, providing an early detection and analysis system that controls those critical variables inside the facility and leads to anticipate faults with early-stage alerts based on treatment of on-time data streams. Moreover, the recorded PQ parameters that are processed in the cloud system can help to reduce energy consumption, as PQ disturbances can be automatically analyzed and even compared to standard values.