用物联网检测非洲野生动物公园和保护区的偷猎者:机器学习方法

Kennedy Edemacu, Jong Wook Kim, Beakcheol Jang, H. Park
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引用次数: 2

摘要

野生动物的灭绝是目前世界正在与之斗争的一个有充分记录的问题。非洲拥有大量的这些物种,是受这一问题影响最严重的地区之一。在更大程度上,这是由于非洲各国持续不断的偷猎行为。物联网(IoT)技术的兴起为许多领域的问题提供了许多有希望的解决方案,例如;环境监测、交通监测、智能健康、废物管理等。因此,在这项工作中,我们设计了一个物联网框架来遏制非洲的偷猎行为。为了提高系统的有效性,我们集成了一个机器学习模型来执行偷猎者检测的图像分析和分类任务。对该框架进行了试点,结果显示物联网在加强野生动物公园和保护区的监控,从而控制偷猎问题方面具有巨大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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