Design and Construction of a Web-Based Communication Interface for Home Automation

IF 2.6 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Big Data Pub Date : 2023-08-03 DOI:10.1109/icABCD59051.2023.10220488

Lesetja S. Mabunda, T. S. Hlalele

引用次数: 0

Abstract

A web-based communication interface for home automation enables users to remotely control and monitor their home appliances and devices using a web browser. This technology has the potential to improve energy efficiency and convenience of homes, but also raises security and privacy concerns. This paper focus on the development of a web-based home automation communication interface employing the ThingSpeak platform as the cloud interfacing service, an Arduino board as the microcontroller, and the ESP8266 as the internet module. The subsystem components were tested using hardware testing circuits and a software code written using Arduino IDE to determine the standard operating procedure and results show that they all conform to the operating standards. When the PIR sensor was tested a voltage of 0 V was measured on the digital pin 2 of the Arduino when no motion is detected and a voltage of 3.25 V when motion is detected. The MQ7 sensor gave a reading of 1.73 V on the analog data pin when not exposed to CO (carbon monoxide) and a reading of 3.25 V when exposed to CO.

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基于web的家庭自动化通信接口的设计与实现

基于网络的家庭自动化通信接口使用户可以使用网络浏览器远程控制和监控他们的家用电器和设备。这项技术有可能提高能源效率和家庭的便利性，但也引起了安全和隐私方面的担忧。本文以ThingSpeak平台为云接口服务，以Arduino板为微控制器，以ESP8266为互联网模块，重点开发基于web的家庭自动化通信接口。采用硬件测试电路和Arduino IDE编写的软件代码对子系统组件进行了测试，确定了标准的操作程序，结果表明它们都符合操作标准。在测试PIR传感器时，Arduino的数字引脚2在没有检测到运动时测量到0 V电压，在检测到运动时测量到3.25 V电压。当不暴露于CO(一氧化碳)时，MQ7传感器在模拟数据引脚上的读数为1.73 V，暴露于CO时的读数为3.25 V。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.