The concept of smart urban systems assumes tracking and analysing various signals generated in the environment surrounding inhabitants. The aim is to provide responses which are context-aware and pro-active and allow to increase the inhabitant's life comfort. Smart outdoor lighting solutions are common and mandatory components for modern urban spaces and municipalities offering considerably energy savings. On the other hand, inhabitants' behavioural fingerprints originating from cellular data streams, produced and stored in base transceiver stations (BTSs), are the most ‘democratic’ and ubiquitous information which might support modern solutions tuning/fitting lighting parameters to the current needs. This paper presents the fundamental problems of elicitation, classification and understanding of such signals/data for the development of smart systems operating in urban areas with the special focus put on smart outdoor lighting problems. Omnipresence of computing is strongly focused on providing on-line support to users/inhabitants of smart cities. Three important components underlying computational model are discussed in this paper: the method of analysing selected elements of mobile phone datasets through understanding inhabitants' behavioural fingerprints, the multi-agent system supporting the proposed logic and the formalism based on graphs that allows reasoning about inhabitant behaviours. Corresponding scenarios for public transport and outdoor lighting are outlined as well.