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Optimization Of Sugeno Fuzzy Logic Based On Wireless Sensor Network In Forest Fire Monitoring System

机译:基于无线传感器网络在森林火灾监控系统中的Sugeno模糊逻辑优化

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Forest fires are a phenomenon of natural disasters that often occur in Indonesia and are a local and global concern. Forest fires that occur today are caused by two main factors namely natural factors and uncontrolled human activity factors. Therefore in this research is to find ways to reduce forest fires that often occur today. Therefore, a fire detection system with dual sensor based wireless sensor network based with Sugeno FIS (Fuzzy Inference System) algorithm is designed that can be accessed through the Internet network. The purpose of this research is to create a forest fire monitoring system for a wide area of fire-prone areas using WSN (Wireless Sensor Network). In this study also used the FIS (Fuzzy Inference System) method as a method of decision making with mathematical calculations that can improve accuracy in the fire detection system so that the output of this method is the level of fire status. Internet of Things technology is also used so that information can be received by users in real-time through the Internet network. Based on the test results on the system that has been designed, Sugeno FIS (Fuzzy Inference System) calculations on SN1 and SN2 have 100% accuracy when compared to manual calculations. The average speed of sending data on SN1 is 1.67 seconds and on SN2 is 1.52 seconds. Testing the detection status of the fire sensor with a distance of 10 to 100 cm has results that correspond to a predetermined threshold.
机译:森林火灾是在印度尼西亚经常发生的自然灾害的现象,是当地和全球担忧。今天发生的森林火灾是由两个主要因素引起的,即自然因素和不受控制的人类活动因素。因此,在这项研究中,可以找到减少常常发生的森林火灾的方法。因此,设计了一种基于Sugeno FIS(模糊推理系统)算法的双传感器无线传感器网络的火灾检测系统,可以通过互联网网络访问。本研究的目的是使用WSN(无线传感器网络)为广泛的火灾地区创建森林火灾监控系统。在本研究中,还使用了FIS(模糊推理系统)方法作为决策方法,其数学计算可以提高火灾探测系统中的准确性,以便该方法的输出是火灾状态的水平。还使用了物联网技术,以便用户通过互联网网络实时地通过用户收到信息。根据设计的测试结果,与手动计算相比,SUGENO FIS(模糊推理系统)计算SN1和SN2的计算具有100%的准确性。在SN1上发送数据的平均速度为1.67秒,SN2为1.52秒。测试具有10至100cm的距离的火传感器的检测状态具有对应于预定阈值的结果。

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