During the nesting season of the sea turtles, at certain hours, teams of 3-4 people walk along the beach regularly and observe the turtle tracks and nests. Such procedure is necessary both for observing the number of sea turtles crawled out of the sea and locating their nests. This manual process is demanding especially when the beach under inspection is very long. Today's technological opportunities allows us to observe the beach regularly, detect the sea turtle traces and GPS coordinates of their nests automatically. We believe that such an automatized application will help conservation of sea turtles in terms of making improvement in their breeding rate.
The primary aim of this project is to design and develop an unmanned aerial vehicle (UAV) that is capable of automatically fly over the beach and locate the tracks and nests of the sea turtles. In each inspection mission, the UAV will take pictures of the beach and 3D scan the beach surface. These data will be containing their GPS coordinates as well. Thus, when they are processed in a main computer, GPS coordinates of each nest will be returned. Also, it will be possible to determine the number of sea turtles crawled out of the sea between two consecutive inspection missions. As a result, some of the procedures within the field work will be carried out automatically, faster and more accurately. The vehicle will collect data with its camera and LIDAR scanner. These data will be transferred to a main computer through a high speed wireless data link hardware. The data from the camera will be processed with various image processing algorithms and the distribution of 3D point data from LIDAR will be analyzed separately using pattern recognition methods. The output from two different processing steps will be crosschecked to achieve a higher detection rate. Since all the data from the sensors will be tagged with their GPS coordinates, the exact location of the detected traces and nests will be provided to the user as well as other relevant information such as the number of traces, length of each trace, distance between two nests, and distance between a nest and the sea.
We assume that the tracks will not be swept away by wind or humans
1 - Objects on the soil (e.g. trashes, bushes, stones) will be a problem for automatically detecting the sea turtle traces. 2 - Amount of daylight during image acquisition may affect the accuracy of detection process. 3 - It may not be possible to use the vehicle when the wind is very strong.
1- Save time for people walking along the beaches for sea turtle track observation 2- Save lives of 500 sea turtles every year
The only need is funding.