Towards Establishing Cross-Platform Interoperability for Sensors in Smart Cities.

Area of Science:

• Computer Science
• Data Science
• Internet of Things

Background:

• Smart city initiatives rely on complex distributed systems with numerous stakeholders and applications.
• Managing diverse time-series data from various sensor and IoT platforms, simulations, databases, and files presents significant integration challenges.
• Effective decision-making in smart cities necessitates robust data integration strategies for interoperable access to heterogeneous data sources.

Purpose of the Study:

• To introduce the InterSensor Service, a novel lightweight web service designed for seamless data integration in smart city environments.
• To enable connection to multiple IoT platforms, simulation data, databases, and files, abstracting away data storage and API complexities.
• To facilitate the on-the-fly encoding of observations according to standardized interfaces like OGC Sensor Observation Service and OGC SensorThings API for unified analysis.

Main Methods:

• Development of a Java-based implementation of the InterSensor Service.
• The service connects to heterogeneous data sources including IoT platforms, simulation data, databases, and files.
• Observations are encoded on-the-fly to comply with OGC Sensor Observation Service and OGC SensorThings API standards.

Main Results:

• The InterSensor Service successfully integrates data from diverse sources, enabling unified analysis and visualization.
• It simplifies the process for users to connect to different data sources and for providers to add interoperable interfaces.
• The service is offered as free, open-source software and is already in use in smart city projects, including an application for the Queen Elizabeth Olympic Park in London.

Conclusions:

• The InterSensor Service provides an effective and lightweight solution for data integration challenges in smart city projects.
• It promotes interoperability by encoding heterogeneous observations into standardized formats.
• The open-source nature and existing applications demonstrate its practical utility and potential for broader adoption in smart city ecosystems.