UAVs as a New Malacological Survey Instrument

An important aspect in the control and determination of Schistosomiasis risk areas is the mapping of the occurrence of Biomphalaria. This work proposes a malacological survey instrument using a small UAV (Unmanned Aerial Vehicle) for mapping Biomphalaria breeding. UAVs, popularly known as "drones" are vehicles that can reach difficult access places.

>They are equipped with environmental sensors and cameras. An UAV is able to identify (on the fly) the existence of the snail. The on-board system is self-controlled (no need for human control) and writes missions and transmits them in real time to agents near the flight area. The system maps the occurrence of Schistosomiasis areas and geospatial technology and satellite images from Geosere-UFRPE (www.dtr.ufrpe.br/geosere/) are integrated to the maps.

There are two categories of UAVs: (1) the fixed-wing and (2) the rotary-wing (or propeller, and a VANT with four of them is also called 4-engine drone). For this study a 4-engine one has been used, because good flight stability is required for obtaining the images. This is necessary for sharply identify the elements of the image. Rotary-wing UAVs are generally small ones. They have a motor for each screw and they use a cross structure where each motor is fixed to one end of this structure.

UAVs are equipped with on-board computer responsible for: (a) turning the control of the engines; (b) the execution of algorithms that stabilize the flight; (c) reading sensors; (d) data acquisition and (e) processing from the environment in which they are flying. Data is collected from various sensors attached to the vehicle.

The processing of the collected data by UAVs can be done in two different ways: (1) embedded processing, where the processing takes place along with the reading of runtime data and on-board; and (2) processing on a server, where the processing is done after collection in a different computer from the one that collects the data.

This work presents a new methodology to identify the Schistosomiasis intermediate host and a possible study of abiotic variables collected by the various sensors attached to the vehicle. The data from these sensors will feed a computer model that is able to store historical data. This model will be able to suggest locations for future analysis.