3D environment for continuous adaptation using meta-learning methods, that are applied and tested in diverse spatial context. The 3D environments are constructed through Sverchok nodes, that allows the geometries to be parametrically defined, and visually programmed. Requires Python 3.6 or higher. Dynamic environment and Meta-Learning model is transferred through the OSC from Pure Data extended.
In: Anthropologic: Architecture and Fabrication in the Cognitive Age.Proceedings of the 38th eCAADe Conference - Volume 2. Berlín: Berlin Technical University, 2020. p. 219-231. ISSN 2684-1843. ISBN 9789491207211.
While the theoretical possibilities and implications of interactive architecture are promising, much still is unknown how these can be practically translated towards purposeful deployments. To understand the true dynamic qualities of interactive architecture, the only method is experiencing its hedonic qualities firsthand. To this end, working prototypes need to be realised and their actual impact measured. In this paper, we compare two potential experimental strategies for interactive architecture prototype evaluation, as we benchmark the conceptual, technological and methodological differences between a life-size, physical prototype and an immersive virtual reality simulation. By presenting the preliminary findings of each strategy, we discuss how their unique strengths and weaknesses could complement each other in future research endeavours.
In: Anthropologic: Architecture and Fabrication in the Cognitive Age.Proceedings of the 38th eCAADe Conference - Volume 2. Berlín: Berlin Technical University, 2020. p. 527-534. ISSN 2684-1843. ISBN 9789491207211.
Scientific output has well-established methods for comparing and scoring the quality and quantity of the work. For artistic output this matter is not settled at all and a subject of much debate. We present a method which has been developed in Czech republic since 2011. This method is used to compare and score the artistic output of all schools of arts in the country (for example, music, performative arts, architecture, literature, sculpture, painting). The system presented in this paper is based on the Saaty-method (also known as Analytic Hierarchy Process). After almost eight years of development and use, the system has proven as a valuable asset to assess in an objective way output between many different forms of artistic works. In 2016 the system was incorporated in the Higher Education Act. In the paper we present a brief history of the development and the principles of AHP applied in the system. In particular, we will focus on the findings in architecture derived from the system. Finally, we will discuss possible implications for architectural education in general.
Mechanická ruka pro upevnění chytrého reproduktoru Amazon Echo Dot ke zdravot- nímu lůžku byla vyvinuta pro pilotní projekt “Využití hlasového asistenta pro pacienty s poraněním míchy” Spinální jednotky FN Motol. Je vytisknuta z recyklovaného filamentu R-PET.
The increasing demand for data and smart solutions is one of the fastest growing sectors of human activity. In recent decades smartphones and mobile phones have become a significant and stable source of data. Architects and urban planners have used them in various cases to identify urban patterns. This paper focuses on data gathered by fitness tracker applications which collect information about the movement of their users. The applications record the trajectory of the movement and detect the mode of transport. They require some basic information about the user (age, weight, height and sex) to calculate their caloric consumption. The data from activity tracking smartphone applications create a data lake that can be transformed into a new data source for the designing of healthier and more liveable cities. Combining the data layers and analysing them further could reveal properties and qualities of life in a given location that would not be apparent without processing these data. By analysing the data, we can observe the current state as well as tendencies in human behaviour over longer periods of time. Through the observation and comparison of physical activity in different urban contexts (topography, size of settlement, density of population, density of infrastructure, quality of public spaces, location, etc.), we can develop new alternatives and better knowledge of the influence the above-mentioned factors have on the life in cities. This paper describes data layer combinations that bring novel insights into the connection of physical activity and urban contexts by using data mining technology based on smartphone applications. The theoretical framework can be subsequently applied to various data sets with certain properties.
Matějka, P. - Cajthaml, J. - Cikrle, P. - Čada, V. - Fošumpaur, P. - Hromada, E. - Koutná, H. - Kristek, J. - Kuda, F. - Machotka, R. - Marek, A. - Matějovská, D. - Motyčka, V. - Nový, A. - Nývlt, V. - Pešková, Z. - Pruška, J. - Remeš, J. - Růžička, J. - Schneiderová Heralová, R. - et al.
Cílem zprávy je na obecné úrovni zmapovat situaci výuky BIM na českých veřejných vysokých školách se stavebním zaměřením. Zpráva tak reaguje na ne vždy zcela jasné představy praxe o tom, zda a jakým způsobem se BIM na vysokých školách vyučuje. Uvedený přehled je důležitý nejen pro případnou spolupráci akademického, veřejného a soukromého sektoru, ale také pro praxi, která je v roli zaměstnavatele absolventů vysokých škol. Cílem zprávy v žádném případě není vytvářet srovnání jednotlivých oslovených institucí, protože charakter zprávy je spíše informativní a jakékoliv kvantifikované hodnocení by vzhledem ke struktuře vstupních dat mohlo být zavádějící nebo velmi subjektivní.
Increasing demands on big data and smart solutions are visible in most branches of human activity. This movement is also present in the field of architecture and urban design. To build proper tools and information structures, which deliver the required information to architects and urban designers, the further use of big data is necessary. The focus of this paper is the description of how architects use the big data report in the design process of the medium-scale public space renewal projects. We analyzed the usage of big data analysis during the design processes of two public space renewal projects. The Prague Institute of Planning and Development commissioned two pilot studies for Klárov square and Revoluční street, where the big data report was a part of the project bases. The provided report was extracted from the agent-based simulation model of multimodal mobility of Prague. We combined in this agent-based model the data from mobile phone traces, statistical offices, open street maps, public transport timetables, travel diary surveys, foursquare and cadastral offices. The big data report contains data about residents and passersby – about their quantity, education, financial income, gender, age, marital status, number of children and household members, economic activity, mode of transport and type of activity. We also visualized the spatial distribution of paths and destinations. The experiences of both architecture teams had many common points. They considered the reported sociologic structure of the residents and tourists for the public space design as irrelevant. They would appreciate more detailed information about the transportation flow dependent on time of day. Furthermore, they would expect the possibility to test different transportation scenarios in big data-based models as a part of the design process. Both teams would prefer to cooperate with data specialists as direct members of the design team instead of receiving passive reports.