Overview of Artificial Intelligence (AI) in Mosquito Research, with Special Reference to the Future of Indian Fauna
Alphy Joseph, Krishnadas Ashok, P. Fijy Jose, Embalil Mathachan Aneesh, N. R. Mangalambal, Susanta Kumar Ghosh, Chaitali Ghosh, Abhijit Mazumdar, Edamana Pushpalatha, B.K. Tyagi · 2025
Artificial intelligence (AI)–based methods have been used to predict vector-borne illnesses. This study specifically looks at the numerous methodologies, parameters, variables, dataset kinds, and performance measures utilized in earlier studies, including individual and ensemble methods. AI is an emerging computational science, and its utility in the case of mosquito research is very recent. In India, there are hardly any conclusive investigations, and therefore, its application to the Indian fauna has been abysmally performed. On the contrary, in the Western world, a lot of systemic AI research on various aspects of mosquito biology has been carried out – for example, mosquito species identification, mosquito surveillance, and population mapping and control. This review demonstrates how AI techniques excel at disease recognition, categorization, identification, and assessment of control measure efficacy. In this chapter, we investigate how to classify and identify mosquitoes using machine learning and neural networking approaches. The study contrasts the standard method with deep learning–based disease recognition.