Abstract
This research presents a novel approach to combating dengue by integrating Biological Control methods with Artificial Intelligence (AI). The objective of the study is to reduce the Aedes aegypti mosquito population and decrease dengue transmission through sustainable strategies. A comprehensive research methodology was used, involving extensive literature review, case studies, and data analysis to identify the main factors driving the high incidence of dengue in Brazil. The research applied AI tools to analyze epidemiological, meteorological, and environmental data, allowing for early outbreak predictions and targeted interventions. AI-enhanced surveillance systems were also employed to monitor mosquito populations and identify breeding sites more accurately. These strategies were combined with biological control methods, such as using natural predators and genetically modified mosquitoes, to manage mosquito populations effectively. The study demonstrate that the integration of AI and biological control can significantly improve the efficiency, accuracy, and sustainability of dengue control measures. The study concludes that this data-driven approach, when adapted to local contexts, can reduce reliance on chemical pesticides and offer a more resilient framework for long-term dengue management.
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