ZUKOWO

The nationwide housing shortage is particularly evident in urban centres such as Leipzig. In addition to the emerging or intensifying social challenges, the housing shortage also makes it difficult to meet climate targets.

The ZUKOWO project is investigating how the concept of housing mobilisation in urban areas can contribute to affordable and sustainable housing. The aim is to reduce housing shortages and CO2 emissions through the optimised use of existing housing stock, whilst at the same time ensuring housing security for people facing changes in their household circumstances.

The approach of the collaborative project involves the investigation and reallocation of housing owned by housing cooperatives, in which residents hold lifelong tenancy rights through cooperative shares. ZUKOWO’s cooperation partners are the Chair of Measurement Technology at the Faculty of Engineering at HTWK Leipzig, the Chair of Sociology at TU Chemnitz, and the Office for Statistics and Elections of the City of Leipzig. The participating colleges and universities will develop solutions for more efficient use of housing, with HTWK Leipzig focusing on the technical aspects and TU Chemnitz on the social science aspects. The Office for Statistics and Elections of the City of Leipzig is analysing the need for and potential of reallocating housing.

The project aims to produce an open-source programme for managing building and household data, which will be used to reconcile housing needs, thereby creating a win-win situation. Furthermore, this is intended to increase the long-term energy efficiency of buildings and social integration in the sociological sense within urban housing complexes.

The Faculty of Engineering at HTWK Leipzig will develop a (fuzzy) classification model, distinguishing between a learning phase and a working phase. During the learning phase, a fuzzy classification model will be constructed in a multidimensional feature space (to describe the housing supply). Either a data-driven or an expert-based approach is possible here. In the data collection required to build the classification model, including the definition of various states, the focus is on capturing the subjectively and objectively justified uncertainties present in the (linguistic and numerical) description of housing offers. In the operational phase, the optimal housing offers for a given requirement are identified on the basis of the classification model developed in the learning phase, taking uncertainties into account. The integration of the classification model into a software environment, as well as its technical implementation as an ‘embedded system’ for transfer to a practical setting, takes place in close cooperation with the project partners and end-users. The work is finalised through prototype application studies for practical validation, as well as the identification and implementation of optimisations, also in close cooperation with the project partners and end users.