About this Activity
This project aims to set up a health monitoring system based on the wireless sensor network. Health is one of the pillars that can help achieve the SDGs (Sustainable Development Goals). However,the strategies developed to ensure health well-being are much more oriented towards curative solutions than preventive ones. Environmental monitoring is essential for the development of adequate and effective health strategies. Malaria is one of the important public health problems, particularly in sub-Saharan Africa with 95% of the 274 million cases in 2021. Reducing the impact of malaria requires new surveillance approaches to target potential outbreaks and respond in a timely manner. However, current epidemiological analyses are for the most part based on clinical case data collected in the field. This poses problems of lack of precision, delayed availability of data and biased prediction.
The project I2HM proposes to use georeferenced connected sensors (IoT) to retrieve environmental data in near real-time. The devices we intend to deploy include temperature and humidity sensors for ambient air, sunlight level, precipitation rate, water pH sensors, mosquito traps, odor probes, and more. This system should be equipped with machine learning algorithms that, based on the georeferenced data collected in real-time, predict high-risk areas and make recommendations. Additionally, the proposed system ensures better support by deploying preventive solutions that can be reused for the surveillance of other diseases such as meningitis and respiratory pathologies related to particle matter (PM) pollution.
This project is funded by Open call to sustain the development and promotion of AI 2023. Didier Donsez is the coordinator.