Proceedings of the 4th edition of the Computer Science Research Days, JRI 2021, 11-13 November 2021, Bobo-Dioulasso, Burkina Faso

Research Article

The design and implementation of an IoT-based health monitoring system in Burkina Faso

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  • @INPROCEEDINGS{10.4108/eai.11-11-2021.2317992,
        author={Manegaouinde Roland  TOUGMA and D\^{e}sir\^{e}  GUEL and Justin P.  KOURAOGO and Yann  SANOU and Boureima  ZERBO},
        title={The design and implementation of an IoT-based health monitoring system in Burkina Faso},
        proceedings={Proceedings of the 4th edition of the Computer Science Research Days, JRI 2021, 11-13 November 2021, Bobo-Dioulasso, Burkina Faso},
        publisher={EAI},
        proceedings_a={JRI},
        year={2022},
        month={5},
        keywords={internet of medical things (iomt) esp32 max30100 raspberry pi websockets},
        doi={10.4108/eai.11-11-2021.2317992}
    }
    
  • Manegaouinde Roland TOUGMA
    Désiré GUEL
    Justin P. KOURAOGO
    Yann SANOU
    Boureima ZERBO
    Year: 2022
    The design and implementation of an IoT-based health monitoring system in Burkina Faso
    JRI
    EAI
    DOI: 10.4108/eai.11-11-2021.2317992
Manegaouinde Roland TOUGMA1,*, Désiré GUEL1, Justin P. KOURAOGO1, Yann SANOU2, Boureima ZERBO3
  • 1: Université Joseph KI-ZERBO (U-JKZ), Ouagadougou, Burkina Faso
  • 2: Yeltech Technologies, Ouagadougou Burkina Faso
  • 3: Université Thomas Sankara, Ouagadougou, Burkina Faso
*Contact email: manegarodrol@gmail.com

Abstract

We present a health monitoring system for patients in Burkina Faso with the objective of preventing the spread of disease and obtaining a good diagnosis even at remote. An IoT application has been realized in three phases by: designing a web application; designing a digital records tracking system; and field testing. In order to locate the level of integration of the IoMT-based system in our health centers, a field survey was conducted. The system is based on a Raspberry Pi that has been deployed as a WiFi AP (Access Point). An ESP32 is associated with a MAX30100 sensor to create a saturometer with local resources. It has been developed in Python and implements websockets for real-time connection to allow automatic feedback of data from the oximeter to the application.