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Fi-Ona: Fire Warning Alarm System Using Internet of Things Based on Fuzzy Logic

机译:FI-ONA:防火警告报警系统使用基于模糊逻辑的东西互联网

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The system proposed in this paper comes in form of an alarm system designed to detect any fire that happen in nearby environment, using the principle of Internet of Things (IoT) and a machine learning logic called Fuzzy Logic. The IoT technology is used for sharing data between node-node of sensor in a network that connected to database from the main system. Sensors that have been used in this system is system is divided into 3 types, Termokopel-K for temperature sensor, MQ-2 for smoke sensor, and the last one is flame sensor. Each of this sensor will convert the input into analog voltage. After that, data from each sensor will be processed using Fuzzy Logic to determine the level of a fire before the already processed data will be sent into the owner the property where the fire is ignited or the firefighter officer using realtime database. The result of testing the system shown that there are 2 conditions that can triggered the alarm. The first one is when there is 2 "medium" state from 2 sensor, for example 31° degree from temperature sensor and 170 Part Per Million(PPM) from smoke sensor. The second one is when there is "extreme" state from the sensor, for example, flame sensor output is 115 ADC. The increasing number in integrated sensor will increased the accuracy and computing time for environment data while maintaning the reliability of the decision taking process.
机译:本文提出的系统采用了一个旨在检测在附近环境中发生的任何火灾的警报系统的形式,使用内容互联网(物联网)和称为模糊逻辑的机器学习逻辑。 IOT技术用于在从主系统连接到数据库的网络中的传感器节点之间的共享数据。在该系统中使用的传感器是系统分为3种类型,用于温度传感器的Termokopel-K,用于烟雾传感器的MQ-2,并且最后一个是火焰传感器。每个传感器都会将输入转换为模拟电压。之后,将使用模糊逻辑处理来自每个传感器的数据,以确定已经处理的数据之前的火灾级别的火灾级别,其中使用实时数据库点燃火灾或消防员官员。测试系统的结果显示有2条条件可以触发警报。第一个是当2个传感器有2个“培养基”状态时,例如从温度传感器的31°程度,从烟雾传感器的170分(PPM)。第二个是当来自传感器的“极端”状态时,例如,火焰传感器输出是115 ADC。集成传感器的越来越多的数量将提高环境数据的准确性和计算时间,同时保持拍摄过程的可靠性。

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