# Exploiting the Value of Active and Multifunctional Facade Technology through the IoT and AI
## 1 Introduction  
The building sector is facing a period of deep transformation. On the one hand, it must adhere to the European Union's policies for decarbonization of the built environment [1, 2]. On the other hand, it must meet an increasing demand for high standards in indoor environmental quality (IEQ) to ensure the user's well-being and a healthier environment [3, 4]. To face both challenges, the EU has pinpointed the building facade sector as a perfect incubator for exploring transformative innovation for the entire construction domain [5, 6]. Indeed, the building facade plays a critical role in impacting a building's overall energy consumption [7] and carbon footprint [8], and simultaneously, it is strictly responsible for the IEQ and users' well-being [9, 10] by impacting thermal, acoustic, and visual comfort. Thus, several research projects have been funded by the EU for the years with the aim to develop innovative and high-performance building skins [5, 11]. In this context, one of the most interesting scenarios in balancing energy efficiency aspects and IEQ refers to the development of active and multifunctional facade (MF) systems [12]. Compared to a \"traditional\" building skin, a MF expands the facade's role by incorporating additional functionalities and enhancing performance, including aspects of modularity and prefabrication [13]. Various systems such as heating, ventilation, air conditioning (HVAC), automated blinds, solar panels, and photovoltaics technologies can be integrated into the building envelope to optimize energy efficiency, exploit renewable energy, enhance thermal insulation, improve indoor air quality, and assure high and responsive IEQ [14]. By transforming facades into active and adaptive building components, the system's ability to meet environmental and user comfort needs increases significantly. In this perspective, the MF system can adjust the visual, thermal, and acoustic performance of a building according to environmental conditions or specific users' needs. However, despite the significant technical advances in conceptualizing, designing, and prototyping complex MF systems, widespread adoption in the market is still limited [15; 16; 17]. Although the construction market is characterized by a certain latency in integrating innovative technologies and systems, some issues need to be addressed before MF is a ready-to-market technology. Aspects related to cost, the supply chain, design complexity, long-term benefits, system integration, and MF control are identified as the main obstacles that limit product scalability in the market [16; 17; 18]. This paper, starting by defining the state of the art of MF systems, aims to clarify how the Internet of Things (IoT) and Artificial Intelligence (AI) technologies can be integrated to address technical barriers and, consequently, foster market deployment. Indeed, recent advances in the field of IoT technologies and AI for the built environment are enabling a new situation-aware paradigm for decision making [19] needed to achieve higher levels of efficiency. The potential contribution of digital innovation is also recognized by the European Commission as a key strategy for enabling sustainable models and promoting the more rational use of resources [20]. In this paper, these benefits are assumed as potential innovative factors to exploit the value of MF systems. Although several theoretical studies have investigated topics of the facade sector [12; 21; 22], few real experiences have been carried out. This implies a gap in the research on the topic. As reported by [PERSON] et al. [11], further research in recognizing the added value of advanced facades provided by digital technologies is needed to address significant market segments. In this perspective, the development of prototypes is a key action to investigate the advantages and obstacles to be addressed to trigger the technology transfer from research to industry [23]. The novelty of the paper lies in a real case study used to address technical, managerial, and economic issues.