## 1 Introduction  
The increasing impacts of climate change have caused a global awakening of individuals and governments, resulting in a necessary commitment to search for and implement solutions capable of combating them. In Western societies, the prosperity of the adopted economic model of consumption is highly dependent on energy resources, placing high pressure on their exploitation. The global report of the International Energy Agency pointed out an increase in global energy demand by 4.6% in 2021 compared to 2020, exceeding the pre-COVID-19 pandemic levels. Global economic growth was also revised upwards and pointed to a 6.0% increase, with CO\({}_{2}\) emission levels rising by nearly 4.8% due to the demand for primary energy resources, such as coal, oil, and natural gas [1]. In this context, it is understood that energy consumption is inherent to economic growth and, nowadays, the consequent emission of greenhouse gases into the atmosphere somehow seems inevitable. These results, illustrating a growing demand for energy, place serious questions on the environmental goals set for the coming years, namely the decarbonization of society by 2050. Nevertheless, the objectives are clear and the impacts are positive, involving a transition to greener society, based on three pillars: renewable electricity production, electric mobility, and energy efficiency [2]. Renewable production has been around for several years, but photovoltaic and wind production have only gained importance in the last 10 years with the technological evolution of photovoltaic panels and wind turbines. For example, in Portugal, according to data from the Portuguese Renewable Energy Association, renewable generation was responsible for supplying 65.4% of the energy consumed in 2021, avoiding the emission of 11.6 MtCO\({}_{2}\)eq (megatonnes of Carbon Dioxide Equivalent) [3]. Electric mobility is also a reality these days, with substantial growth in the mobility market share each passing year [4]. People's acceptance of these vehicles is partly due to the development of charging infrastructures, the greater reliability of batteries, and the increase in autonomy, which is beginning to be comparable, and even in certain models superior, to vehicles powered by combustion engines [5; 6]. Finally, in our list, is energy efficiency, associated with the optimization of its use, i.e., consuming less and generating more. Much has been invested into improving the energy efficiency of buildings, which represent 30-45% of global energy consumption [7] and in the integration of building management systems, i.e., systems that monitor buildings and optimize the resources for their exploration. In the latter context, the reduction in consumption through the detection of anomalies is one area of study in which there is great interest in energy management, because anomalous consumption often represents additional losses, reflected by higher costs and environmental pollution. Several intelligent solutions have been proposed that aim to perform the early detection of defects and thus mitigate their effects [8; 9; 10], but this is not a closed issue. The case study presented here aims specifically to describe the steps taken in the implementation of an intelligent system capable of performing the detection of non-normal consumption levels for hotel units. One of the biggest challenges in developing these solutions for hotel units is the difficult characterization of the building's consumption patterns. Sometimes, the dependence on factors such as outside temperature, solar intensity, the day of the week, the hour of the day, the building occupancy, the provision of external services (e.g., events, conferences), and unplanned occupancy, among others, cause randomness and unpredictability in the way that consumption is processed, making the task of anomaly detection algorithms very challenging [11; 12].