Abstract
Efficient and reliable monitoring of wild animals in their natural habitat is essential. We develop a system to detect animals with automatic alerts as part of the project. Since there is a large number of different animals, manually identifying them can be a difficult task. Our algorithm classifies animals based on a DarkNet deep learning model, which allows us to monitor them more efficiently. Animal detection and classification can help to prevent animal- vehicle accidents and animals from destroying agricultural lands. This can be achieved by applying effective deep learning algorithms. Furthermore, GSM and GPS devices are used to detect and alert the presence of animals using Arduino embedded systems. Keywords: Wild animals, DarkNet, Deep Learning, Animal Detection, Animal vehicle accidents, Arduino, GSM, GPS.
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