Definition of an Ontology Matching Algorithm for Context Integration in Smart Cities

Area of Science:

• Computer Science
• Artificial Intelligence
• Urban Informatics

Background:

• Smart cities rely on diverse agents (sensors, devices, users) for data exchange.
• Semantic representation using ontologies enables agent knowledge sharing.
• Interoperability challenges arise from heterogeneous ontologies within smart cities.

Purpose of the Study:

• To propose a novel ontology matching algorithm, OntoPhil, for automatic information exchange in smart cities.
• To address the challenge of seamless communication between heterogeneous agents and the smart city infrastructure.
• To enhance the accessibility and service capabilities of open smart cities.

Main Methods:

• Development of a new ontology matching algorithm named OntoPhil.
• Deployment and testing of OntoPhil within a smart city context.
• Evaluation using benchmarks from the Ontology Alignment Evaluation Initiative (OAEI).
• Comparative analysis against existing ontology matching algorithms not specifically designed for smart cities.
• Specific validation tests with smart city ontologies and various agent types.

Main Results:

• OntoPhil demonstrated effectiveness in facilitating automatic information exchange between agents.
• The algorithm proved capable of handling heterogeneous ontologies within the smart city environment.
• Performance was validated through established OAEI benchmarks and specific smart city scenarios.

Conclusions:

• OntoPhil offers a viable solution for achieving interoperability in smart cities.
• The proposed algorithm enhances seamless communication, crucial for advanced smart city services.
• This research pioneers the application of dedicated ontology matching for smart city agent interactions.