Smart city model based on systems theory

Michal Lom and Ondrej Pribyl

International Journal of Information Management, 2021, vol. 56, issue C

Abstract: While there are several partial solutions to model some aspects of cities (e.g. transportation or energy), there is no framework allowing modelling of a complex system such as a city. This paper aims on providing a solution that can be used by practitioners to model impact of different scenarios and smart city projects encapsulating different subsystems, such as transportation, energetics or, for example, eGovernment. The term “smart cities” is classified into Systems Theory, particularly focusing on Cyber-Physical Systems. This classification is further elaborated to define a new term, so-called Smart City Agent (SCA). The SCA is considered as the main building block for modelling smart cities. The approach within this paper however stresses the interconnection of different systems within a city. Its’ strength is in better exchange of data and among heterogeneous agents. This information management approach is the missing key in the growing market of partial smart city solutions as it will allow simulation of solutions in complex systems such as a city. The suitability of usefulness of the proposed approach is demonstrated on a use case dealing with charging of electrical vehicles. The results show that the approach is suitable for modelling of dynamic behaviour.

Keywords: Modelling; Multi-Agent systems; SMACEF; Smart city; Intelligent agent (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0268401219301811
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:56:y:2021:i:c:s0268401219301811

DOI: 10.1016/j.ijinfomgt.2020.102092

Access Statistics for this article

International Journal of Information Management is currently edited by Yogesh K. Dwivedi

More articles in International Journal of Information Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().