基于人工智能技术的森林走廊野生动物入侵检测

J. J. Daniel Raj, C.N Sangeetha, Sarthak Ghorai, Subhajit Das, Manish, Shariq Ahmed
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引用次数: 0

摘要

最近几天有许多动物袭击人类的报道,特别是在森林地区,夺走了无辜的生命。为了减少此类事件,这项工作旨在识别动物并警告车辆使用物联网检测系统来降低事故率。如果检测被触发,报警系统将向驾驶员发出信号。因此,该系统将拯救动物,并减少丛林边高速公路上的事故数量。在这项工作中,树莓派3模型B用于检测动物和提醒车辆。该相机配置用于树莓派拍摄图像和动物的运动。它还采用基于物联网的图像检测系统,使用显示或声音警报系统。我们设法放慢车速以避免事故。我们使用了YOLO算法,该算法可以帮助我们处理系统,每秒45帧,该系统可以一次处理图像以预测目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wild Animals Intrusion Detection for Safe Commuting in Forest Corridors using AI Techniques
There are many animal attacks on human is being reported in the recent days particularly in the forest area which claims innocent lives. In order to reduce such incidents this work is aimed to identify animals and alert vehicles to slowdown accident rates using IOT detection system. If the detection is triggered, the alert system will give signals to driver. Hence, the system will save the animal and reduce number of accidents in the jungle side highways. In this work Raspberry Pi 3 Model B is used for detecting the animals and alerting the vehicles. The camera is configured for use in Raspberry Pi to take shoot images and movement of animals. It also employs IOT based image detection system using display or sound alert system. We try to slowdown the vehicle to avoid accidents. We have used YOLO algorithm which helps us to process the system which takes 45 frames per sec. This proposed system process the image to predict the object at once.
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