Research projects


Stochastic methods for estimation and prediction of moving objects postion

In this project, we analyse output data of the Multi-Static Primary Surveillance Radar (MSPSR) which can be used to obtain a detailed overview about aviation situation in the airspace, including targets designed to be hard to detect. Methods of analysis of such data are analysed with the goal of creating a knowledge-based system of probable corridors of usual flights. Such a knowledge-based system can be used as a basis of the determination of the most probable position of the target of interest or its classification from the unusual occurrence point of view. Further, methods of MSPSR data processing for the target classification purpose will be investigated, mainly by using methods of Bayesian Statistics, both parametric and nonparametric. In terms of problem formulation, it will be also interesting to use modern methods of Machine Learning (ML), especially Neural Networks (NN). The goal of this project is to explore a viable methods, analyse the suitability of each method for the target classification based on the output data of the MSPSR system.

Research team

Main Researcher: Pavel Kulmon
Other Members: Jiří Demel

Data Gathering, Analysis, and Retrieval from BIM Models for Management and Decision-Making

Project analyses processes in the field of design, construction and operation of buildings for the purpose of their optimisation by implementing informational modelling of buildings. Building information modelling is nowadays offering wide range of utilization possibilities to participants of building processes as well to facility management subjects. Nevertheless the overall efficiency of creation, sharing, processing and utilization of data from building information models including GIS data is not solved adequately in the matter of R&D due to actual industry demand, or activities are marginal. The aim of project is the analysis and the design, realisation and operation processes optimization. This is due to efficiency improvements of BIM data implementation within mentioned processes. Namely, it is about improvement of efficiency with BIM, furthermore about the semi-automatization of processes processing the BIM data, furthermore, the problematics of passive sensors for airspace monitoring data processing including fusion of these data with GIS data will be examined for the purpose of urban areas monitoring.

Research team

Main Researcher: Jiří Kaiser
Other Members: Dalibor Vytlačil, Jan Rádl, Kristýna Prušková

Process Modeling and Processing of Big Data for Support of Building Industry and Sustainable Building

The project deals with the methods of obtaining, processing and using BIM data to support processes in the construction industry. The project focuses on automation of data acquisition processes for creating BIM models of existing buildings. The possibilities of obtaining data from BIM models for computations in the field of fire protection will be explored - including the possibility of obtaining data from stored according to the IFC standard. The project also deal with the identification of data and information that are used as input, output or exchanged between the project proposal and the legislative operations and the necessary partial steps for the successful and effective implementation of the BIM into the Czech legislation. For purposes of maping of processes and expressing essential aspects in terms of passing on the necessary process information, the development of process modeling methods is also be part of the project.

Research team

Main Researcher: Filip Klimeš
Other Members: Jiří Demel, Jiří Kaiser, Kristýna Prušková, Martin Dědič, Josef Myslín

Dynamic Models for the Building Stock Management

The project goal is the design of the dynamic model for the assessment of the building stock parameters changes in the Czech Republic. The calculated parameters describe the energy consumption in the existing building stock. The solution is based on the system dynamics methodology that is the suitable tool for the complex problem solution in the technical-economic systems. The designed model can be used for strategy decision making concerning building energy consumption decreasing. It makes possible to test different strategies in the virtual world before implementation. The prediction of the future development on the basis of the dynamic model helps to improve decision making processes in the state institutions as well as it helps building owners.

Research team

Main Researcher: Dalibor Vytlačil
Other Members: Jana Kučerová, Tomáš Vaníček, Pavel Kresteš, Jan Kaňka, Martin Hotový

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