Data Exchange Interoperability in IoT Ecosystem for Smart Parking and EV Charging.

Area of Science:

• Computer Science
• Engineering
• Information Technology

Background:

• The Internet of Things (IoT) ecosystem faces significant interoperability challenges due to diverse, domain-specific standards.
• Vertical communication models in IoT limit data sharing across different ecosystems, hindering smart city initiatives.
• Existing IoT standards often lack compatibility, preventing seamless device communication.

Purpose of the Study:

• To address IoT interoperability issues using domain-independent messaging standards.
• To showcase the practical application of O-MI and O-DF standards in a smart city context.
• To facilitate horizontal data sharing across disparate IoT applications.

Main Methods:

• Utilized O-MI (Open Messaging Interface) and O-DF (Open Data Format) standards for IoT communication.
• Developed a proof-of-concept mobile application for a smart electric vehicle (EV) charging ecosystem.
• Focused on the Smart Mobility domain within a smart city initiative.

Main Results:

• Successfully demonstrated the practical use of O-MI/O-DF for achieving interoperability.
• Enabled seamless communication and data sharing in a smart EV charging use case.
• Validated the effectiveness of the proposed standards in a real-world mobile application context.

Conclusions:

• O-MI/O-DF standards offer a viable solution to the IoT interoperability problem.
• The developed proof-of-concept highlights the potential for enhanced smart city services through standardized IoT integration.
• This approach supports horizontal data integration, crucial for future IoT ecosystems.