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利用 WSN 辅助的无人机进行动物监测的数据收集方案:面向 WSN 或面向无人机。

Data Collection Schemes for Animal Monitoring Using WSNs-Assisted by UAVs: WSNs-Oriented or UAV-Oriented.

机构信息

Instituto Politécnico Nacional-(SEPI-UPIITA-IPN), Mexico City 07740, Mexico.

Instituto Politécnico Nacional-(CIC-IPN), Mexico City 07738, Mexico.

出版信息

Sensors (Basel). 2020 Jan 2;20(1):262. doi: 10.3390/s20010262.

Abstract

Wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) have been used for monitoring animals but when their habitats have difficult access and are areas of a large expanse, remote monitoring by classic techniques becomes a difficult task. The use of traditional WSNs requires a restrictive number of hops in a multi-hoping routing scheme, traveling long distances to the sink node where data is stored by nodes and UAVs are used to collect data by visiting each node. However, the use of UAVs is not straightforward since the energy balance between the WSN and UAV has to be carefully calibrated. Building on this, we propose two data collection schemes in clustered based WSNs: (1) WSN oriented and (2) UAV oriented. In the former, nodes within each cluster member (CM), send information to their cluster head (CH) and for recollection, the UAV visits all CHs. As the UAV visits many CHs the flight time is increased. In the latter, all CHs send data from their CMs to a sink node, hence, the UAV only visits this node, reducing the flying time but with a higher system energy cost. To find the most suitable scheme for different monitoring conditions in terms of the average energy consumption and the buffer capacity of the system, we develop a mathematical model that considers both the dynamics of the WSN along with the UAV.

摘要

无线传感器网络 (WSN) 和无人机 (UAV) 已被用于监测动物,但当它们的栖息地难以进入且面积广阔时,经典技术的远程监测就变得困难。传统的 WSN 技术需要在多跳路由方案中限制跳数,通过节点和 UAV 传输到存储数据的汇聚节点,UAV 用于访问每个节点来收集数据。然而,使用 UAV 并不简单,因为必须仔细校准 WSN 和 UAV 之间的能量平衡。在此基础上,我们在基于簇的 WSN 中提出了两种数据收集方案:(1)面向 WSN,(2)面向 UAV。在前一种方案中,每个簇成员 (CM) 内的节点将信息发送到其簇头 (CH),而 UAV 用于收集所有 CH 的信息。由于 UAV 访问了许多 CH,因此飞行时间会增加。在后一种方案中,所有 CH 都将其 CM 的数据发送到一个汇聚节点,因此 UAV 仅访问该节点,虽然减少了飞行时间,但系统能耗更高。为了根据系统的平均能耗和缓冲区容量找到最适合不同监测条件的方案,我们开发了一个数学模型,该模型同时考虑了 WSN 和 UAV 的动态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d4c/6982891/bec606b7f5a8/sensors-20-00262-g001.jpg

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