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Energy consumption minimization on LoRaWAN sensor network by using an Artificial Neural Network based application

机译:基于人工神经网络的应用,Lorawan传感器网络的能耗最小化

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In this paper we use an application approach to minimize the energy consumption and increase the lifetime of a LoRaWAN sensor network. In this sensor network the nodes transmission cycles are controlled by an Artificial Neural Network (ANN) based algorithm. The algorithm predicts the data of nodes and by this method the nodes can avoid data transmission and stay more in Idle mode. For implementing this algorithm and for controlling the network we use the middleware MQTT, which is compatible with The Things Network public LoRaWAN server. With this control, the nodes can, for the best case, save up to 58.91% transmissions and extend their lifetime.
机译:在本文中,我们使用应用方法来最小化能量消耗,并增加洛拉瓦传感器网络的寿命。在该传感器网络中,节点传输周期由基于人工神经网络(ANN)的算法控制。该算法预测节点的数据和通过该方法,节点可以避免数据传输并保持更多的空闲模式。用于实现该算法和用于控制网络,我们使用中间件MQTT,该MQTT与网络公共LoraWan服务器兼容。通过此控件,节点可以为最佳情况下节省高达58.91%的传输并延长寿命。

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