Providing an Ontology-based Framework to Determine the High-Level Software Classes of a Smart City
Subject Areas : Creative City DesignHoubakht Attaran 1 , Esmaeil Kheirkhah 2 , hassan shakeri 3
1 - Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
2 - Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
3 - Department of computerEngineering, MashhadBranch, Islamic Azad University,Mashhad, Iran
Keywords: Smart City, Ontology, Software Classes, Software Requirements,
Abstract :
In any society, software designed for a smart city in an environment based on the Internet of Things (IoT), provide smart urban models and user requirements for a better life and citizens' interaction with this smart city. However, the existing requirements extracting methods, due to several reasons like integration, interoperability, preventing data redundancy, possible interference and lack of integration and semantic queries, are not suitable and the mentioned problems are usually visible in some of these software systems. This article presents a comprehensive ontology of the smart city at the level of the existing meta-classes along with the way of inheritance and cooperation of these classes to integrate, prevent data redundancy and semantic query capability by using the experts' opinions. The classes required for the construction of this ontology were first collected by the snowball method from the urban target community and then refined and finalized by the Delphi method using the opinions of experts including university professors, industrial and business owners, as well as city officials. For the first time, three major classes are embedded in this model as super classes that all classes can inherit from. Thus, the framework presented in this article, while covering various aspects of a smart city, can be used to determine the software classes of a smart city, including high level classes and most important sub-classes, along with the localization capability for each community based on priorities of that community.