Conclusions
Novel and important applications are available with the development of data mining methods. Artificial intelligence techniques are an important field to be applied on the control of vector-borne diseases.
A complete and accurate identification of the 5000 mosquito’s species that were already identified should be tested in this model as well as other species groups, such as complex or cryptic species, and in different populations of the same species.Artificial intelligence could help to develop a system that anyone, who capture larvae or adult’s mosquitos in several regions, can identify the Aedes mosquito. In the near future, a complete identification of any insect or new nonclassified ones that exist in this world could be automatically classified by anyone using a smartphone. AI will never replace mankind but will help to keep memories and activities that humans have discovered in our millenarian existence.
Acknowledgements
This project received financial support from Fundagao de Amparo a Pesquisa do Estado da Bahia—FAPESB via scholarships. We are thankfull to Daniel Andre Dias Imperial Pereira and Alexandre Morais Cavalcanti, students at University Center SENAI/CIMATEC. We also thank Eduardo Oyama, entomologist from the Technology Institute of Health—SENAI CIMATEC, for supporting the work and sharing his experience. We are also in debt with the Department of Culicidae collection from Fiocruz Rio de Janeiro, especially Maycon Neves and Monique Motta from their staff.
Conflict of interest
We have no “conflict of interest”
Appendices and nomenclature
AI artificial intelligence
ML machine learning
DL deep learning
ILSVRC ImageNet large scale visual recognition challenge
WO PCI patents (world)
CNN convolutional neural networks
SVM support vector machine