Smart city and smart home concepts have become increasingly popular, especially in the last decade. Many people have positive notions of living in a smart city or smart home, but not too many users can really define what these concepts mean. One of the reasons lies in the fact that smart city and smart home concepts are very broad and include elements from different domains of science and innovation. Together with the upcoming era of big data and changes in the assessment and evaluation of our built environment, we may find ourselves with a seemingly endless source of data describing our surroundings. The question arises if all these data could be turned on into information and knowledge (which leads to making the right decision) so that we know how to design and develop our cities and dwellings in the future? Or would it be the other way around, meaning that excessive amounts of data, and the redundancy thereof, make the whole concept of smart home and smart cities less clear for people to understand? One of the possibilities that are available for practice is the use of so-called decision support systems (DSSs), which can help users to manage all elements included in a given analysis and predict potential effects of actions of decision makers, in order to avoid unfavourable scenarios of future development.