Data aggregation in precision agriculture for low-power and lossy networks

Yongjoo Kim, Puleum Bae, Jina Han, Young-Bae Ko
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引用次数: 8

Abstract

To provide best cultivation conditions, the agricultural environment monitoring systems are developed based on various wireless sensors. RPL routing, which is targeting the large-scale wireless sensor network, can work effectively in agriculture environment consisting of constrained sensor devices. Each sensor node can transmit sensing data to monitoring system using periodic inter-sensor multi-hop communication in RPL routing. However, the number of sensors increases and each sensor node generates large volume of time-series data periodically. Therefore, it can cause network overhead, bandwidth consumption, and transmission delay, etc. In this paper, we propose data aggregation scheme for low-power and lossy-networks to reduce such a big volume. We apply RPL routing protocol in agricultural system, especially in greenhouse. After that, we collect and analyze the sensing data and reduce the amounts of data. We evaluate the performance using Cooja simulator on the Sky mote sensors based on Contiki operating system.
面向低功耗有损网络的精准农业数据聚合
为了提供最佳的耕作条件,开发了基于各种无线传感器的农业环境监测系统。RPL路由是一种面向大规模无线传感器网络的路由算法,可以有效地应用于由受限传感器组成的农业环境中。在RPL路由中,每个传感器节点通过周期性传感器间多跳通信将传感数据传输到监控系统。然而,随着传感器数量的增加,每个传感器节点都会周期性地产生大量的时间序列数据。因此,它可能导致网络开销、带宽消耗和传输延迟等问题。本文提出了一种适用于低功耗、低损耗网络的数据聚合方案。我们将RPL路由协议应用于农业系统,特别是温室系统。然后对传感数据进行采集和分析,减少数据量。我们使用Cooja模拟器对基于Contiki操作系统的Sky移动传感器进行性能评估。
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