用循环神经网络和长短期记忆实现灯具控制系统

Priscilya Inri Sasia, Muhammad Ary Murti, C. Setianingsih
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引用次数: 0

摘要

智能灯是一种为用户控制灯提供便利的技术。在此之前,已经有人在研究开发这一系统,但所提供的控制仍然基于Android,无法支持多平台。该系统采用循环神经网络(RNN)和长短期记忆(LSTM)算法。此外,本系统还进行了利用物联网系统对灯具进行控制和监控的试验。从本研究中,测试结果表明,在最小声强为60.6 dB的情况下,系统开启和关闭I灯的平均时间分别为3.3秒和3.28秒。II灯依次开启和关闭为3.43秒和3.61秒,最小声强为60.8 dB。同时,连续打开和关闭III灯的时间分别为3.32秒和3.39秒,声强至少为61.32 dB。三盏灯可控制,最远距离为1.2米。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of Lamp Control System by Reccurent Neural Network and Long-Short Term Memory
Smart lamp is a technology that offers convenience for users in controlling the lamp. Previously, there had been research developing this system, but the controls offered were still based on Android that can’t support a multiple platform. This system uses the Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM) algorithms. Besides that, this system also does a trial by using Internet of Things System for controlling and monitoring the lamps.From this research, the results of testing show that the average time required for the system to turn on and turn off Lamp I are 3.3 seconds and 3.28 seconds respectively with a minimum sound intensity of 60.6 dB. To turn on and turn off Lamp II in succession is 3.43 second and 3.61 second with a minimum sound intensity of 60.8 dB. Meanwhile, to turn on and turn off Lamp III in a row is 3.32 seconds and 3.39 seconds with a sound intensity of at least 61.32 dB. The three lamps can be controlled with the furthest distance is 1.2 meters.
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