Abstract
After the malaria, Schistosomiasis or Bilharzia is the second disease that calls for admission to hospital. In fact, the Schistosoma that transmits the illness lives in water points. The proposed Sensor-Based Schistosomiasis Detection (SBSD) architecture considers data collected by several sensors such as water temperature, water point pH, solar irradiation that are deployed in a natural environment, in order to develop more-sensitive disease-prediction and control-model. The main goal is to stop the transmission cycle of Bilharzia by forbidding the access of water point, for treatment, when the environmental factors are favourable.
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Acknowledgement
This work has been partially supported by the AUCC, now called Universities Canada, in the Sensor-Based Bilharzia Detection project. Also, the authors would like to thank other project partners.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Kassé, B., Diallo, M., Gueye, B., Elbiaze, H. (2018). SBSD: Towards a Proactive Sensor-Based Schistosomiasis Detection. In: M. F. Kebe, C., Gueye, A., Ndiaye, A. (eds) Innovation and Interdisciplinary Solutions for Underserved Areas. CNRIA InterSol 2017 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 204. Springer, Cham. https://doi.org/10.1007/978-3-319-72965-7_29
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DOI: https://doi.org/10.1007/978-3-319-72965-7_29
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