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Mosquito-borne diseases remain a major global public health challenge, particularly in tropical and subtropical regions where environmental conditions favor vector proliferation. Diseases such as malaria, dengue, and Zika continue to impose a significant health and socio-economic burden worldwide. In this context, reliable and continuous surveillance systems are essential to anticipate outbreaks and support effective vector control strategies. However, conventional monitoring approaches often rely on manual inspections or periodic sampling, which are costly, labor-intensive, and difficult to scale. These limitations highlight the need for automated, real-time surveillance solutions capable of operating under diverse environmental conditions, thereby motivating the development of intelligent systems based on advanced sensing and data-driven techniques. |