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Intelligent tools to vector control and population orientation against dengue fever


Dengue is the most important viral disease transmitted by mosquitoes and one of the major public health concerns in Brazil and most of the tropical and subtropical countries in of the world. Dengue epidemics are also responsible for a significant economic and social impact on the populations in which they occur. Currently, due to lack of an effective vaccine against dengue, epidemics can only be avoided by controlling the vector mosquito. Effective control is only possible with the support of government agencies and a high level of participation and support from the population, since unilateral solutions, such as the use of insecticides, has not proven effective in the long term. Unfortunately, practice has shown that mass media educational campaigns are not enough for public awareness. In addition, these campaigns do not allow tracking the results of the actions of each individual, guide them and motivate them prior to the occurrence of epidemic outbreaks. Given the size of a country like Brazil, this task seems impossible, but that is exactly what we propose in this project. In this research project an innovative approach is presented to guide, motivate and evaluate individual actions to control the mosquito Aedes aegypti. Our proposal is to develop an intelligent trap, which can be marketed as consumer electronics. The trap is able to attract and capture mosquitoes and automatically recognize and count the Aedes aegypti mosquitoes. Using local population estimates of dengue mosquitoes, we can evaluate and suggest custom control activities for the user of the trap via a mobile app that connects to the trap. Thus, the trap allows promoting dengue vector control measures prior to the occurrence of disease outbreaks. Besides being an immediate and environmentally safe solution for the capture of adult mosquitoes, it aims to make each user of the technology a control agent to combat dengue. In addition, the information collected by different traps can be used to build a collaborative map of population density of mosquitoes, allowing more effective and timely actions by government agencies in the regions with the highest incidence of dengue mosquitoes. (AU)

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(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SOUZA, VINICIUS M. A.; BELTRANCASTANON, C; NYSTROM, I; FAMILI, F. Identifying Aedes aegypti Mosquitoes by Sensors and One-Class Classifiers. PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2016, v. 10125, p. 9-pg., . (11/17698-5, 15/16004-0)

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