Towards a Characterisation of Smart Systems: A Systematic Literature Review - Romero, Marcelo; Guédria, Wided; Panetto, Hervé; Barafort, Béatrix (Computers in industry, 2020)
•Systematic Literature Review on Smartness and Smart Systems.•Definitions of Smartness and Smart Systems extracted from 123 papers.•Text mining methods applied to analyse the definitions extracted from the papers.•Characteristics of Smart Systems are defined and formally represented. Enterprises and governments are focusing their efforts on reducing the gap between the physical and the digital world to address various challenges. This digital transformation is also characterised by a change of paradigm, based on moving from computer-aided technologies to Smart Systems, which are present in several domains such as Smart Cities, Smart Manufacturing, or Smart Services. In this scenario, the exploration of the conceptualisation of Smart Systems has been addressed in the scientific literature with the objective to understand the characteristics of such systems and the implications of their use. However, there is a lack of a generic view of the concept since most studies focus on specific domains. This view is necessary to provide common ground for the development or implementation of Smart Systems within various domains, specially for those that have not been tackled yet. This work aims at addressing this issue through the exploration and analysis of conceptualisations of Smart Systems and Smartness within the scientific literature. For this purpose, a Systematic Literature Review is performed aiming at gathering papers including definitions of Smart Systems, regardless of the application domain. Text mining processing techniques are applied to obtain insights from the definitions extracted from the collected papers. Considering the findings of the literature review and the analysis of the extracted definitions, we enumerate and describe a set of characteristics of Smart Systems. We also provide a diagrammatic view of the elements of a Smart System and their relationships through a meta-model.