Abstract
In this paper we describe a novel proposal in the field of smart cities: using an ontology matching algorithm to guarantee the automatic information exchange between the agents and the smart city. A smart city is composed by different types of agents that behave as producers and/or consumers of the information in the smart city. In our proposal, the data from the context is obtained by sensor and device agents while users interact with the smart city by means of user or system agents. The knowledge of each agent, as well as the smart city's knowledge, is semantically represented using different ontologies. To have an open city, that is fully accessible to any agent and therefore to provide enhanced services to the users, there is the need to ensure a seamless communication between agents and the city, regardless of their inner knowledge representations, i.e., ontologies. To meet this goal we use ontology matching techniques, specifically we have defined a new ontology matching algorithm called OntoPhil to be deployed within a smart city, which has never been done before. OntoPhil was tested on the benchmarks provided by the well known evaluation initiative, Ontology Alignment Evaluation Initiative, and also compared to other matching algorithms, although these algorithms were not specifically designed for smart cities. Additionally, specific tests involving a smart city's ontology and different types of agents were conducted to validate the usefulness of OntoPhil in the smart city environment.
Highlights
The last decades have born witness to a sharp increase in the number of initiatives related to Internet of Things and Smart Cities
Ontologies by themselves are not enough to guarantee the interoperability of the different parties, the approach we propose is to explore ontology matching techniques [17,18] as a possible solution for knowledge matching in smart cities
As usual in the field, we have used the precision, recall and f-measure metrics to assess the accuracy of our algorithm and compared our results with those provided by the algorithms that took part in several tracks of the Ontology Alignment Evaluation Initiative 2013 (OAEI-13), the benchmark, conference and anatomy tracks
Summary
The last decades have born witness to a sharp increase in the number of initiatives related to Internet of Things and Smart Cities. These initiatives are grounded in the idea that the Internet and e-related services can reach anywhere and improve users’ lives with new types of services and comfort. The proper infrastructure must be deployed, including different types of sensors, smart devices and actuators, and the networks that allow the communication among the different devices and systems. On top of this infrastructure different applications are placed. The field of Ambient Intelligence (AmI) can be directly linked to smart cities, as AmI is devoted to proposing new and innovative ways of interaction between people and ICT [3]
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