## 2 Literature
### Living Labs as Gap-Bridging Environments  
In the general sense, the term \"living lab\" (also \"living laboratory\") describes the concept of innovation within real-life contexts, with active participation from users, businesses, and governments [53; 54; 55]. The concept is applied across several domains, notably health and well-being, democracy and government, service and development, and energy [53]. A key feature of living labs that distinguishes them from test beds is that users are \"co-producers\" of the innovation, beyond being observed subjects [53; 54]. Furthermore, living labs operate in a live production environment, unlike test beds, which are run in isolated and controlled environments. Nevertheless, the term \"living lab\" is sometimes (erroneously) used to describe a test bed. In Germany, the equivalent term \"Reallabore (der Energiewende)\", as defined by the German Federal Ministry for Economic Affairs and Climate Action (Bundesministerium fur Wirtschaft und Klimaschutz, or BMWK) takes on an additional implication: the provisionof a \"legal sandbox\", in which selected laws are relaxed to facilitate ground-breaking research [56]. The \"Reallabore\" concept serves to accelerate the transfer of technology and innovation by enabling the implementation of sustainable energy technologies under real conditions on an industrial scale. These technologies include concepts that hold a large potential but are still not ready for market roll-out--as judged by the so-called _technology readiness level_ (TRL)--thereby bridging the critical phase between technology development and market roll-out [57]. Living labs make extensive use of ICT for data gathering and analysis, as well as for the deployment and interconnection of the components that comprise the solutions in question. From the stated characteristics of living labs, certain requirements for any deployment begin to emerge, among which are that the disruptions caused by the study have real-world implications and must be compensated for in advance. As will be discussed in detail in Section 3 below, the LLEC builds this fact into its very architecture via various techniques and approaches, such as the ability to switch comfortably between default and scientific operation mode (via the \"kill-switch\" concept), multi-modal user interactions with technology (e.g., manual vs. automatic room temperature control), and testing phases/limited trials (space-limited controllers, access-controlled dashboards, etc.). In the literature, there are examples of living labs and similar setups in the field of energy research. In [58], the implementation of an extensive sensor and control network in two real-life buildings at the Construction and Engineering Research Laboratory (CERL, USA) is shown. The authors assess the two existing buildings and their retrofitting potential in detail as well as sensors and technologies for instrumenting the buildings. Special emphasis was placed on retrofitting cost analysis and real-life implementation barriers of wireless devices. While they show the successful implementation of mode-based control of the buildings, user-building interactions and acceptance of the retrofit was not investigated. Additionally, by today's standards the instrumentation techniques described have been superseded. [PERSON] et al. [24] investigate a model-based control approach, minimizing the cost of energy based on i.a. human-in-the-loop data obtained through a mobile app. Their setup consists of an existing building, comprising a floor area of 465 m\({}^{2}\), controlling zone air temperature and AHU set-points for eight zones. They interface with facility management and provide a (software) \"kill switch\" to prevent BACS failure. On the user side, occupancy detection is performed with PIR sensors, and a Markov model is used to predict occupancy. They analyze and evaluate MPC performance using the _predicted mean vote_ (PMV) metric. The project ran for 20 days and for a single building.