Enhancing River Monitoring Embedded System using Time Redundancy Fault Tolerance to Resolve Transient Sensor Fault

M. Ichsan, Muhammad Adinura Julian Habibie, Wijaya Kurniawan
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Abstract

Reading data from sensors in the context of the Internet of Things (IoT) is one of the main parameters of a high-reliability system. Data reading by sensors is prone to errors due to various variables that the problem cannot accommodate. One method to overcome this problem is the time redundancy algorithm, where the sensor takes data and its best value several times. In this study, the sensors used to calculate the water levels are ultrasonic sensors and resistance. At the river monitoring point, data is sent using the UDP (User Datagram Protocol) protocol that previous studies have used. This research has been done as a prototype with a maximum distance between sensor nodes of one meter. The results of sending data using UDP were successful, with an average delay of 3293 microseconds. And the ultrasonic sensor that has been tested based on transient fault against time redundancy has an accuracy of 94.5% based on a sampling delay of 1000ms.
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利用时间冗余容错增强河流监测嵌入式系统解决瞬态传感器故障
在物联网(IoT)的背景下从传感器读取数据是高可靠性系统的主要参数之一。由于问题无法容纳的各种变量,传感器读取的数据容易出错。克服这个问题的一种方法是时间冗余算法,其中传感器多次获取数据及其最佳值。在本研究中,用于计算水位的传感器是超声波传感器和电阻。在河流监测点,使用先前研究使用的UDP(用户数据报协议)协议发送数据。这项研究是作为传感器节点之间最大距离为一米的原型进行的。使用UDP发送数据的结果是成功的,平均延迟为3293微秒。基于瞬态故障和时间冗余测试的超声波传感器在1000ms的采样延迟下的准确率为94.5%。
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审稿时长
20 weeks
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