Bauhaus.MobilityLab: A Living Lab for the Development and Evaluation of AI-Assisted Services

Abstract

With the vision “Innovation by experiment” the Bauhaus.MobilityLab started in July 2020 as a living lab in the district Brühl of the city Erfurt, Thuringia, Germany. As a unique project, it is coupling the sectors mobility, logistics and energy into a unified living lab. It allows to design, develop and evaluate innovative services to increase the quality of life in the city. Bauhaus.MobilityLab offers access to live smart city data of different domains and provides a set of powerful artificial intelligence (AI) algorithms for data processing, analytics and forecasting. In contrast to existing platforms, its uniqueness is the available and integrated living lab. It allows directly rolling out new smart city services and to evaluate the impact in the real world. This paper describes the implementation of the technical platform supporting the Bauhaus.MobilityLab, realized according to the DIN SPEC 91357 as an open urban platform. It focuses on data sharing based on the concepts of the International Data Spaces and the integration of AI algorithms. The concepts are presented based on examples in the energy domain.

Responsible living labs: what can go wrong?

“…These challenges are particularly pertinent in the context of LL actions (Harbers and Overdiek, 2022), which are real-world settings for research and innovation that involve stakeholders in co-creation, experimentation and evaluation processes. The unique features of LLs, such as the involvement of end users and other stakeholders in the innovation process, create both opportunities and challenges for the implementation of AI-powered DT at all individual, organizational and societal levels (Frey et al , 2022; Harbers and Overdiek, 2022).…”

“…In addition, the researchers can also explore how this framework can be implemented in real-world LL activities and actions, particularly those that involve AI-driven solutions for DT processes. One of the key benefits of using an RLL is to ensure LL researchers and practitioners that their research is conducted in a way that is more aligned with RRI principles, which are becoming increasingly important in the development and use of advanced technologies such as AI (Frey et al, 2022;Nebeker et al, 2019). Another key benefit of using an RLL framework is that it can help LL practitioners create more inclusive and sustainable innovation processes.…”

Artificial Intelligence in the Smart City — A Literature Review

“…The impact of AI extends beyond smart homes, influencing broader domains, including mobility, logistics, energy, healthcare, and environmental management (Frey et al, 2022;Chang et al, 2020;López-Blanco et al, 2023;Zhi-Xian & Zhang, 2022;Hu et al, 2021;Alsamhi et al, 2019). A prime example of AI integration in urban development is the living lab concept, like the Bauhaus.MobilityLab, which facilitates data processing, analytics, and forecasting for innovative service development (Frey et al, 2022). Moreover, environmental forecasting and urban planning reap significant benefits from AI and IoT combined with big data, enabling the development of future environmental scenarios (López-Blanco et al, 2023).…”

Urbane Resilienz, Realexperimente und die Stadt als Labor: Zum paradoxen Zusammenhang von Beharrungsvermögen und Veränderung

“…Man plant zwar, Maß wird jedoch am Bau genommen und entsprechend muss gegebenenfalls umgeplant werden. Reallabore sind, so verstanden, urbane Möglichkeitsräume (Parodi und Beecroft 2021), Testzentren für Innovationen (Frey et al 2022) oder auch Freiraumgestaltungen (Räuchle 2021), die situationsspezifisch angepasst werden können.…”