Kennedy Edemacu, Jong Wook Kim, Beakcheol Jang, H. Park
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Poacher Detection in African Game Parks and Reserves with IoT: Machine Learning Approach
Extinction of wildlife animals is one of the well-documented problems the world is battling with currently. Africa which harbors a good number of these species is one of the regions most hit by this problem. To a greater extent, this is due to the continuous poaching practices in various African countries. The emergency of Internet-of-Things (IoT) technology has had a number of promising solutions to problems in many areas such as; environmental monitoring, traffic monitoring, smart health, waste management, e.t.c. Thus in this work, we design an IoT framework to curb the poaching practice in Africa. To improve the effectiveness of our system, we integrate a machine learning model to perform image analysis and classification task for the poacher detection purpose. A trial implementation of the framework is carried out and the results show a significant potential of IoT being used to enhance surveillance in game parks and reserves and hence, control the poaching problem.