Farm Assistant Counts Sheep

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Small livestock farming in our country is mostly based on pasture. The most important advantage of this situation is that it reduces feed expenses and increases our profitability within the farm. However, the most important problem is in the counting of animals when they come from the pasture to the pen and when they go from the pen to the pasture. This situation depends on the shepherd's attention and follow-up. However, finding experienced shepherds in our country is becoming more and more difficult every day. It may be difficult or even impossible for a sheep giving birth in the pasture to follow the herd when the geographical conditions become difficult. Quick counting of sheep and lambs as the animals enter and exit the pen depends on the shepherd's practice and experience. In order for this situation to be more realistic and to prevent personal mistakes, different alternatives should be considered. For this reason, a system has been developed using deep learning techniques to automatically count the animals in the herd when entering the pen. This system will automatically count the animals at the entrance and exit of the farm, and in case of missing animals, the system users will automatically notify the system users via web and mobile applications. With the implementation of this system, it will be possible to determine the losses that will occur on the farm with an early warning system. In our study, animals will be detected with the deep learning-based YoloV8 pre-trained model on images taken from fixed cameras that will be placed at the entrance and exit of the pen. Counting results obtained from the developed system can be used on different devices by providing multi-platform support. By disseminating this practice, losses of sheep and lambs in the pasture can be prevented.