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作 者:Wonseok Jung Se-Han Kim Seng-Phil Hong Jeongwook Seo
机构地区:[1]Korea Electronics Technology Institute,Seongnam,13509,Korea [2]Electronics and Telecommunications Research Institute,Daejeon,34129,Korea [3]Hancom With Inc.,Seongnam,13493,Korea [4]Hanshin University,Osan-si,18101,Korea
出 处:《Computers, Materials & Continua》2021年第4期337-348,共12页计算机、材料和连续体(英文)
基 金:supported by Institute of Information&communications Technology Planning&Evaluation(IITP)Grant funded by the Korea government(MSIT)(No.2018-0-00387;Development of ICT based Intelligent Smart Welfare Housing System for the Prevention and Control of Livestock Disease).
摘 要:Pig farmers want to have an effective solution for automatically detecting and tracking multiple pigs and alerting their conditions in order to recognize disease risk factors quickly.In this paper,therefore,we propose a novel monitoring system using an Artificial Intelligence of Things(AIoT)technique combining artificial intelligence and Internet of Things(IoT).The proposed system consists of AIoT edge devices and a central monitoring server.First,an AIoT edge device extracts video frame images from a CCTV camera installed in a pig pen by a frame extraction method,detects multiple pigs in the images by a faster region-based convolutional neural network(RCNN)model,and tracks them by an object center-point tracking algorithm(OCTA)based on bounding box regression outputs of the faster RCNN.Finally,it sends multi-pig tracking images to the central monitoring server,which alerts them to pig farmers through a social networking service(SNS)agent in cooperation with an oneM2M-compliant IoT alerting method.Experimental results showed that the multi-pig tracking method achieved the multi-object tracking accuracy performance of about 77%.In addition,we verified alerting operation by confirming the images received in the SNS smartphone application.
关 键 词:Internet of Things multi-object tracking pig pen social network
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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