Professor & Head,
Department of Plant Sciences
School of Biological Sciences,
Madurai Kamaraj University, Madurai
Title of the project [Artificial Intelligence (AI), surveillance, remote sensing, digital platform for surveillance, GIS nodes]: To develop an AI assisted personalized smart trap and surveillance system for anopheline malaria vectors.
Summary:
Background: Mosquitoes are huge menace, spread diseases like Malaria, Dengue, Chikungunya, Japanese encephalitis and other vector-borne diseases. According to WHO’s World Malaria Report-2021, malaria caused 241 million cases and 62.7 million deaths globally. People use mosquito repellents, vapourizers, sophisticated mosquito traps and other methods to avoid annoying mosquito bites, but the problem is not fully rectified. Governmental and non-governmental organizations conduct mosquito vector surveillance based on disease outbreaks. However, such surveillances are laborious, non-comprehensive and need expertise for vector identification.
Novelty: We propose an out-of-box solution, in which Artificial Intelligence (AI) enabled personalized smart trap would be fabricated to trap mosquitoes and identify malaria vectors.
Objectives:This project’s main objective is to develop an AI modulated personalized smart trap and surveillance system to identify mosquito malarial vectors.
Methods: Field collected malaria vector species would be maintained under controlled conditions. Then, the smart personalized mosquito trap would be designed with i) Trapping system, ii) Imager and identification system would be fabricated. The images collected from the smart trap would be used to AI algorithm for malaria vector species identification for identification purpose. Then, the AI model would be integrated with cloud based online surveillance system. The personalized smart traps would be deployed for real-time surveillance of malaria vectors.
Expected outcomes: The real-time surveillance will be used to monitor the population dynamics of malaria vectors which in turn provide high resolution malaria outbreaks within the deployed regions.
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