Abstract
The growing demand for data and smart solutions is one of the fastest growing sectors of human activity. This tendency is noticeable in the field of architecture and urban planning. In recent decades smartphones and mobile phones have become strong and stable data sources. Architects and urban planners already use them for gaining urban pattern in various cases. Public health is one of the branches where the application market can help gain and provide the required data about the tendencies in physical activity and well-being on a daily basis. Physical movement is one of the crucial elements for gaining and preserving both physical and mental health. Observing various factors of the activity of inhabitants of different settlements can help us to gain deeper understandings of the patterns of urban metabolism. Urban design and planning which takes the tendencies of society into consideration is the way to design a habitable and smart city. To make smartphones provide valuable data we have to develop a tool – an application, which provides attractive and beneficial information to the user. The paper focuses on the data gathered by sport-tester applications, which are collecting data about users movements. The applications mostly record the trajectory of the movement and detect the mode of transport. To calculate the caloric consumption of the movement it is necessary to get basic information about user’s condition – age, weight, height, and gender. The data from sport-tester smartphone applications create a data lake, that can be transformed to the novel data source for designing healthier and more habitable cities. There are already smartphone applications on the mobile market, which handle the required data. The data belong to private companies and at the same time they are protected by GBPR in EU or by national law in other countries. This makes them unavailable as open source at current. Thus we build a theoretical approach to combine this type of data and transform them to the information source for data driven decisions, which allow the creation of conditions for healthy urban lifestyles. We organise the data from smartphone sport-testers to the data layers. Combining the data layers and its further analysis could reveal properties of the life in locations, which are not apparent without the work with this data. Through the data analysis we can observe the current state and can also see tendencies in human behaviour over longer periods of time. Through the observation and comparison of the physical activity in differing urban contexts (topography, size of residence, density of population, density of infrastructure, quality of public spaces, location etc.) we can develop new alternatives and better knowledge about the influence of the above mentioned factors on the life of the cities. The paper describes the data layer combinations bringing novel insights on the connection of physical activity and urban contexts by using data mining technology based on smartphone applications. The paper describes the theoretical framework that can be subsequently applied to various data sets with certain properties.
