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作 者:沈颂 沈国峰 Shen Song;Shen Guofeng(School of Information&Electronic Engineering(Sussex Artificial Intelligence Institute),Zhejiang Gongshang University,Hangzhou 310018,China)
机构地区:[1]浙江工商大学信息与电子工程学院(萨塞克斯人工智能学院),杭州310018
出 处:《计算机应用研究》2023年第4期1142-1147,共6页Application Research of Computers
摘 要:由于新冠病毒的高传染性,及早发现患者的密切接触者对于遏制疫情爆发至关重要。而受限于技术发展的水平,目前关于接触检测的方法和研究均需人工参与。提出了一种面向未来的自动化方法,利用加载在感知设备上的移动智能体和边缘协调器在街道上组成多智能体系统,基于对感染者的感知、跟踪和边缘计算,实现了感染者与行人之间的接触概率估算。系列仿真给出了应用部署中的参数比较。仿真结果表明,提出的街道征用模式及边缘计算算法可以进一步改善检测率。Because of the high infectivity of COVID-19,it is essential to detect the close contacts of patients as soon as possible to contain the outbreak of the epidemic.However,due to the level of technological development,the current methods and research on contact detection require manual participation.This paper proposed a future oriented automation method,which used mobile agents loaded on sensing devices and edge coordinators to form a multi-agent system on the street.Based on perception,tracking and edge-computing,the contact probability between infected people and pedestrians was estimated.A series of simulations provided the comparison of parameters in application deployment.The simulation results show that the proposed street expropriation mode and edge-computing algorithm can further improve the detection rate.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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