Towards a Characterisation of Smart Systems: A Systematic Literature Review

Abstract

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.

Systematic Review of Methodologies for the Development of Embedded Systems

“…Two of them (4,52) followed the development of the whole system, one article (42) proposed improvements by introducing agile methods in the software development process, and three articles (43,44,53) dealt with the hardware development process. Out of 14 articles that tried to optimize the partitioning process for hardware and software components, ten articles (3,10,11,12,21,27,39,41,45,47) considered the whole system, and four articles (57,60,61,62) the hardware part of the system. Finally, eight articles (7,15,16,50,51,56,58,59) tried to solve problems for special cases of these systems.…”

“…With further development of hardware technology, eight articles proposed the introduction of dynamic reconfiguration architecture as the hardware part of the system. Five of these articles (10,11,12,27,62) proposed improvements in the partitioning phase, two articles (48,49) suggested improved system models, and in one article (28), software tools that allowed selection of dynamic reconfiguration architecture, and thus, variability of the hardware part of the system, were used in the design phase. It is very important to test as soon as possible during the development process does the system in development satisfy preset requirements.…”

“…The problem of requirements engineering in embedded systems was studied in [11], where articles from 1970 to 2016 were reviewed. The use of special case of these systems, as well as their requirements, were reviewed in [12] and [13].…”

“…1,2,3,9,10,11,12,18,19,20,21,22,27,29,33,34,35,39,40,41,47,48,50,51,60,62,66,69).However, in 23 articles, scientists stated that these heterogeneous complex systems demand novel development methods. Therefore, 12 articles(5,6,8,17,23,28,46,49,54,55,56,61) proposed new approaches based on HW/SW Co-design methodology, 12 articles(4,14,31,32,42,43,44,57,63,64,65,…”

Connectors of smart design and smart systems

“…Systems equipped with this ability have been variously called self-adaptive systems, self-managing systems, or self-organizing systems. Often selfhealing systems and self-optimizing systems are also sorted in this category (Romero et al, 2020). Sabatucci et al (2018) proposed a meta-model that identifies four types of self-adaptive systems: (i) Type 1 (anticipating changes and possible reactions at design-time), (ii) Type 2 (equipped with alternative strategies for reacting to changes), (iii) Type 3 (aware of its objectives and operates with uncertain knowledge), and (iv) Type 4 (able of selfmodifying its specification as biological systems do).…”