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Optimal Placement for Opportunistic Cameras Using Genetic Algorithm

机译:基于遗传算法的机会相机最优位置

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Oppurtunistic Information Fusion (OIF) is introduced to enable the same sensors to provide data for multiple applications. Sensor location plays a crucial rule to get the maximum amount of useful information. This paper examines the optimal placement of cameras for a Networked Sensing Systems (NSS) that are designed to monitor a pre defined region to have as much coverage as possible with the purpose of serving multiple applications. This can be rephrased as a camera location optimization problem with multiple objective functions. Multi-Objective Genetic Algorithms (MOGA) is used with camera coverage as the two objective functions to be maximised
机译:引入了光信息融合(OIF),以使相同的传感器能​​够为多种应用提供数据。传感器位置是获取最大量有用信息的关键规则。本文研究了用于网络传感系统(NSS)的摄像机的最佳放置位置,该系统旨在监视预定义区域,以具有尽可能多的覆盖范围,以服务多个应用程序。可以将其重新表述为具有多个目标函数的相机位置优化问题。多目标遗传算法(MOGA)与摄像机覆盖范围配合使用,作为要最大化的两个目标函数

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