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A Service-Oriented Middleware for Integrated Management of Crowdsourced and Sensor Data Streams in Disaster Management.

Luiz Fernando F G de AssisFlávio E A HoritaEdison Pignaton de FreitasJó UeyamaJoão Porto de Albuquerque
Published in: Sensors (Basel, Switzerland) (2018)
The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor networks are error-prone and difficult to maintain, the study highlights the emerging role of "citizens as sensors" as a complementary data source to increase public awareness. To this end, an interoperable, reusable middleware for managing spatial, temporal, and thematic data using Sensor Web Enablement initiative services and a processing engine was designed, implemented, and deployed. The study found that its approach provided effective sensor data-stream access, publication, and filtering in dynamic scenarios such as disaster management, as well as it enables batch and stream management integration. Also, an interoperability analytics testing of a flood citizen observatory highlighted even variable data such as those provided by the crowd can be integrated with sensor data stream. Our approach, thus, offers a mean to improve near-real-time applications.
Keyphrases
  • electronic health record
  • big data
  • healthcare
  • emergency department
  • primary care
  • machine learning
  • climate change
  • artificial intelligence
  • low cost
  • loop mediated isothermal amplification
  • sensitive detection