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Smart Emergency Alert System Using Internet of Things and Linked Open Data for Chronic Disease Patients

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Advanced Intelligent Systems for Sustainable Development (AI2SD’2018) (AI2SD 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 914))

Abstract

Nowadays, the widespread deployment of more powerful devices (sensors, smartphones, tablets, etc.) has provided us with great number sources of sensing data that are exploited in several domains namely the healthcare domain. Chronic diseases are the most common causes of death and disability worldwide. These types of diseases require more and more studies to help patients and notify cases of crises that lead to death. Representing knowledge through building an ontology for emergency alert system is important to achieve semantic interoperability among health information, predict the patient real-time context and to better execute decision notification. Linked Open Data services are used in our paper in order to provide with the semantic description of collected data from different sources (wearable sensors, environmental sensors, etc.).

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Notes

  1. 1.

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Author information

Authors and Affiliations

  1. Mathematics and Computer Science Department, Faculty of Sciences and Techniques, Hassan I University, Settat, Morocco

    Hajar Khallouki & Mohamed Bahaj

  2. LIUPPA – T2I, 2 Allée du Parc Montaury, 64600, Anglet, France

    Philippe Roose

Authors
  1. Hajar Khallouki
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  2. Mohamed Bahaj
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  3. Philippe Roose
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Corresponding author

Correspondence to Hajar Khallouki .

Editor information

Editors and Affiliations

  1. Computer Sciences Department, Faculty of Sciences and Techniques of Tangier, Abdelmalek Essaâdi University, Souani Tangier, Morocco

    Mostafa Ezziyyani

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Khallouki, H., Bahaj, M., Roose, P. (2019). Smart Emergency Alert System Using Internet of Things and Linked Open Data for Chronic Disease Patients. In: Ezziyyani, M. (eds) Advanced Intelligent Systems for Sustainable Development (AI2SD’2018). AI2SD 2018. Advances in Intelligent Systems and Computing, vol 914. Springer, Cham. https://doi.org/10.1007/978-3-030-11884-6_17

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