Short description of the project
The Bauhaus.MobilityLab project aims to generate innovation in the areas of mobility, energy and logistics for the Smart City. To this end, a real laboratory is being set up in the Brühl district of Erfurt. Here, data from the areas of mobility, energy and logistics will be collected and analysed using artificial intelligence technologies. Central challenges in the technical design of the real lab are the complex and dynamic structure of the systems to be integrated, the management of data and services and the implementation of individual solutions. In the real lab, providers and users of new services should be able to interact from the very beginning and innovative solutions should be developed and tested. The developed concept should be scalable and transferable to other municipalities.
The Bauhaus.MobilityLab (BML) stands for the development of an open ICT ecosystem (BML-EcoSys), which is to be demonstrated using the example of a real laboratory with a focus on mobility, logistics and energy. The use of AI technologies makes it unique in terms of flexibility and system integration. The coupling of data from the three areas of energy, mobility and logistics is intended to enable cross-sector products and services and thus promote an intelligent mobility and energy transition. The scalable and transferable approach of the project offers a distinct economic potential to support disruptive innovations in different sectors and enables the establishment of reallabs in a sustainable way.
The project is currently designing and implementing the architecture of the laboratory platform. For this purpose, a first use case is being set up, which involves the recording of air pollutants such as nitrogen oxides and particulate matter using measurement boxes from Robert Bosch GmbH, a partner in the project. For this purpose, the sensor data will be stored in the FROST server of Fraunhofer IOSB and processed and made available for AI services. These will be used to forecast the probable development of air pollutant concentrations. This forecast then represents the starting point for adjusting public transport fares at short notice and "controlling" the use of different forms of mobility via incentives. This task is carried out in the project by the partners highQ Computerlösungen GmbH and BPV Consult GmbH. Further use cases from the areas of energy and logistics will follow.