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Penerapan Modul Wi-Fi ESP8266 Pada Sistem Deteksi Kebakaran Rumah Berbasis Internet of Things (IoT)

Authors: Raka Randika Marcelino, Insani Abdi Bangsa, Rahmat Hidayat;

Penerapan Modul Wi-Fi ESP8266 Pada Sistem Deteksi Kebakaran Rumah Berbasis Internet of Things (IoT)

Abstract

Fire is a type of non-natural disaster that has a significant impact on humans. Fires occur due to non-natural processes or events such as short circuits, system failure, human error and other causes. One of the measures to prevent fire is to install fire detection and extinguishing systems. The system is made in a device that can detect fire automatically. This research focuses on the application of the wi-fi module ESP8266 in an Internet of Things (IoT) based home fire detection system to assist users in monitoring the condition of their abandoned homes. The method used is descriptive and product development tools. The results of this study indicate that the design of the application of the wi-fi module ESP8266 in the home fire detection system based on internet of things (IoT) uses the Arduino Mega2560 as a microcontroller, the ESP8266 module as a Wi-Fi module or as a link for data exchange between Arduino Mega2560 and Blynk and Blynk application as monitoring or output. From the results of testing the average speed of internet data, packet losses, delay (time difference) and the distance tested in 1 minute obtained a minimum value of 309bps and a maximum of 21kbps, 0% of packets are lost, the average minimum delay is 0.153s and maximum 2.147s and the distance value obtained with a minimum of 0 meters and a maximum of 145 meters.

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Keywords

Fire, Internet of Things (IoT), Arduino Mega2560, ESP8266 Wi-Fi Module

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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