Mosquito-borne diseases such as dengue fever, malaria, and chikungunya has always been one of the leading causes of morbidity in the Philippines \cite{dohLeadingMorbidity}. In fact, the Global Dengue Initiative identifies dengue fever as one of the national notifiable diseases in any country \cite{whoGlobalStrategy}. More than that, the country’s Department of Health created priority control prevention programs for the aforementioned diseases \cite{dohDengueControl,dohMalariaControl}. Despite these measures, the country still continues to face outbreaks of these mosquito-borne diseases. In fact, in 2014, it was reported that there is a surge in mosquito population \cite{dohMosquitoElimination,dohChikungunyaOutbreaks,philstarDogProbing}. To prevent outbreaks of dengue, effective vector control measures should be in place.

A report from the Asia-Pacific and Americas Dengue Prevention Boards has identified that an initial step to combat dengue is to improve surveillance systems \cite{whoGlobalStrategy}. A particular aspect of such a system requires enhanced mosquito-vector surveillance. Despite these suggestions, only a handful of research endeavors are currently implementing such schemes properly integrated to their mosquito-borne diseases surveillance systems \cite{Beatty_2010}.

In the Philippines an initiative by the Department of Science and Technology focused on ovitraps supplemented with manual landing rate counts, these are still in their infancies and are rather insufficient \cite{dohIntegratedDiseaseSurveillance,noah,dostPredictAbundance}. While several literatures have established the importance of entomological surveillance in supplementing disease surveillance and response, only pupal and adult vector counts are considered reliable because of their high correlation with actual disease cases. Moreover, many studies have identified that ovicyte and larval indices offer little value with respect to surveillance because of the low survival rates of eggs and larvae \cite{focks2003review}.

Thus, this project proposes a cost-effective tool that is able to automatically collect, identify, and count adult mosquitoes. The automation feature of the tool allows data collection with minimal human intervention and is suitable even at remote areas where resources are limited. It provides a solution for generating reliable entomological indices which in turn, strengthens the disease surveillance system.