Graph Neuron based approach to smart roads solutions using wireless sensor networks

Victor Welikhe, Jayakumar Vaidhyashankar, A. Amin
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引用次数: 11

Abstract

The ability for the network to effectively differentiate between event and non-event is instrumental in the classification process. Graph Neuron employs an associative memory, network-centric technique that provides for instantaneous recall/recognizing of patterns and high levels of scalability. Implementations of Graph Neuron (GN) for the purposes of event detection in wireless sensor networks (WSN) used in transportation systems has not thoroughly been explored. This paper aims to discuss the possible implementations of the GN algorithm in a WSN for a road safety traffic support system being deployed at black-spots with a high likelihood of motor accidents.
基于图神经元的无线传感器网络智能道路解决方案
网络有效区分事件和非事件的能力在分类过程中很有帮助。Graph Neuron采用了一种以网络为中心的联想记忆技术,提供了对模式的即时回忆/识别和高水平的可扩展性。图神经元(GN)在交通系统无线传感器网络(WSN)中用于事件检测的实现尚未得到充分的探讨。本文旨在讨论GN算法在道路安全交通支持系统的WSN中可能的实现,该系统部署在具有高可能性的交通事故黑点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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