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

Andres Munoz-Arcentales1, Sonsoles López-Pernas2, Javier Conde1

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Summary
This summary is machine-generated.

This study presents an open-source, context-aware data analytics solution for IoT smart environments. It offers an agnostic, end-to-end implementation adaptable to any application field, unlike previous context-specific approaches.

Keywords:
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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.