Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation

Area of Science:

• Computer Science
• Internet of Things (IoT)
• Data Analytics

Background:

• Existing context-aware systems for IoT lack practical implementation details or are too context-specific.
• There is a need for adaptable and reusable solutions for context-aware data analytics in smart environments.

Purpose of the Study:

• To provide an open-source reference implementation for context-aware data analytics in IoT-based smart environments.
• To offer an agnostic, end-to-end solution covering the complete data lifecycle.
• To demonstrate the adaptability of the implementation across various application fields.

Main Methods:

• Leveraging the FIWARE ecosystem and the NGSI data standard.
• Developing an agnostic, end-to-end solution for data acquisition, modeling, reasoning, and dissemination.
• Implementing and showcasing the solution through two distinct use cases.

Main Results:

• An open-source, context-aware data analytics reference implementation for IoT environments.
• An agnostic solution operationalizable in any smart environment, irrespective of its application domain.
• Demonstrated versatility through practical use case examples.

Conclusions:

• The proposed reference implementation provides a flexible and non-context-specific solution for IoT data analytics.
• This agnostic approach facilitates the adoption and extension of context-aware capabilities across diverse smart environments.
• The open-source nature and FIWARE/NGSI foundation ensure broad applicability and future development.