{"title":"为不活动的人设计智能家居原型:基于脑电图/ mqtt的脑物通信","authors":"D. Zubov, M. S. Qureshi, U. Köse, A. Kupin","doi":"10.15588/1607-3274-2022-2-9","DOIUrl":null,"url":null,"abstract":"Context. Immobilized people face additional barriers in almost all areas of life, including simple operations like turning the light on/off and controlling the air conditioner. The object of the study was to develop the brain-to-thin communication of affordable priceto control the smart home appliances by immobilized people from neck to toes.\nObjective. The goal of the work is to manage smart home appliances via brain-to-thing communication with EEG non-invasive electrodes, edge IoT devices, and MQTT protocol if the brain and eye control of the disabled work normally.\nMethod. A non-invasive Sichiray TGAM brainwave EEG sensor kit captures signals and then transmit them via Bluetooth to the HC-05 module connected to the Arduino Mega microcontroller. Information about edge IoT devices is presented to the disabled on the LCD 1602 display wired to the same Arduino Mega. The disabled person chooses the option shown on display via the double blink that is detected if the quality of signal equals zero and low/mid gamma waves are less than ten in three consecutive Bluetooth packets. Control commands are sent from Arduino Mega (MQTT publisher) to the edge IoT devices (MQTT subscribers) that analyze them and start a specific operation like opening a door and turning the alarm on/off.\nResults. Five females and five males of different ages from 8 to 59 years old examined the control of smart home appliances with the Sichiray TGAM brainwave sensor kit. Everyone successfully handled the Sichiray headset and showed satisfaction with the brain-to-thing system.\nConclusions. In this work, a smart home concept for immobilized people was developed using the brain-to-thing approach and the MQTT communication between the MQTT publisher, Sichiray TGAM brainwave EEG sensor kit connected via Bluetooth to the Arduino Mega microcontroller, and edge IoT devices total priced at USD 150. The most likely prospect of the presented work is to produce the sample that is ready to market.","PeriodicalId":43783,"journal":{"name":"Radio Electronics Computer Science Control","volume":"5 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2022-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PROTOTYPING SMART HOME FOR IMMOBILIZED PEOPLE: EEG/MQTT-BASED BRAIN-TO-THING COMMUNICATION\",\"authors\":\"D. Zubov, M. S. Qureshi, U. Köse, A. Kupin\",\"doi\":\"10.15588/1607-3274-2022-2-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Context. Immobilized people face additional barriers in almost all areas of life, including simple operations like turning the light on/off and controlling the air conditioner. The object of the study was to develop the brain-to-thin communication of affordable priceto control the smart home appliances by immobilized people from neck to toes.\\nObjective. The goal of the work is to manage smart home appliances via brain-to-thing communication with EEG non-invasive electrodes, edge IoT devices, and MQTT protocol if the brain and eye control of the disabled work normally.\\nMethod. A non-invasive Sichiray TGAM brainwave EEG sensor kit captures signals and then transmit them via Bluetooth to the HC-05 module connected to the Arduino Mega microcontroller. Information about edge IoT devices is presented to the disabled on the LCD 1602 display wired to the same Arduino Mega. The disabled person chooses the option shown on display via the double blink that is detected if the quality of signal equals zero and low/mid gamma waves are less than ten in three consecutive Bluetooth packets. Control commands are sent from Arduino Mega (MQTT publisher) to the edge IoT devices (MQTT subscribers) that analyze them and start a specific operation like opening a door and turning the alarm on/off.\\nResults. Five females and five males of different ages from 8 to 59 years old examined the control of smart home appliances with the Sichiray TGAM brainwave sensor kit. Everyone successfully handled the Sichiray headset and showed satisfaction with the brain-to-thing system.\\nConclusions. In this work, a smart home concept for immobilized people was developed using the brain-to-thing approach and the MQTT communication between the MQTT publisher, Sichiray TGAM brainwave EEG sensor kit connected via Bluetooth to the Arduino Mega microcontroller, and edge IoT devices total priced at USD 150. The most likely prospect of the presented work is to produce the sample that is ready to market.\",\"PeriodicalId\":43783,\"journal\":{\"name\":\"Radio Electronics Computer Science Control\",\"volume\":\"5 1\",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2022-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radio Electronics Computer Science Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15588/1607-3274-2022-2-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radio Electronics Computer Science Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15588/1607-3274-2022-2-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 1
摘要
上下文。无法行动的人几乎在生活的所有领域都面临额外的障碍,包括开/关灯和控制空调等简单的操作。本研究的目的是开发可负担价格的脑对瘦通信,通过不活动的人从脖子到脚趾来控制智能家电。该工作的目标是在残疾人的大脑和眼睛控制正常工作的情况下,通过脑电图无创电极、边缘物联网设备和MQTT协议的脑对物通信来管理智能家电。一个非侵入性的Sichiray TGAM脑电波EEG传感器套件捕获信号,然后通过蓝牙将它们传输到连接到Arduino Mega微控制器的HC-05模块。有关边缘物联网设备的信息在连接到同一Arduino Mega的LCD 1602显示器上呈现给残疾人。如果连续三个蓝牙数据包的信号质量为零且低/中伽马波小于10,则通过双闪烁检测到残疾人选择显示的选项。控制命令从Arduino Mega (MQTT发布者)发送到边缘物联网设备(MQTT订阅者),分析它们并开始特定的操作,如开门和打开/关闭警报。结果。5名女性和5名男性,年龄在8岁至59岁之间,使用sihiray TGAM脑电波传感器套件检测智能家电的控制。每个人都成功地使用了Sichiray耳机,并对大脑对物系统表示满意。在这项工作中,使用脑对物方法和MQTT发布者之间的MQTT通信,Sichiray TGAM脑电波EEG传感器套件通过蓝牙连接到Arduino Mega微控制器,以及边缘物联网设备之间的MQTT通信,开发了一个面向固定人员的智能家居概念,总价格为150美元。所提出的工作最有可能的前景是生产出准备上市的样品。
PROTOTYPING SMART HOME FOR IMMOBILIZED PEOPLE: EEG/MQTT-BASED BRAIN-TO-THING COMMUNICATION
Context. Immobilized people face additional barriers in almost all areas of life, including simple operations like turning the light on/off and controlling the air conditioner. The object of the study was to develop the brain-to-thin communication of affordable priceto control the smart home appliances by immobilized people from neck to toes.
Objective. The goal of the work is to manage smart home appliances via brain-to-thing communication with EEG non-invasive electrodes, edge IoT devices, and MQTT protocol if the brain and eye control of the disabled work normally.
Method. A non-invasive Sichiray TGAM brainwave EEG sensor kit captures signals and then transmit them via Bluetooth to the HC-05 module connected to the Arduino Mega microcontroller. Information about edge IoT devices is presented to the disabled on the LCD 1602 display wired to the same Arduino Mega. The disabled person chooses the option shown on display via the double blink that is detected if the quality of signal equals zero and low/mid gamma waves are less than ten in three consecutive Bluetooth packets. Control commands are sent from Arduino Mega (MQTT publisher) to the edge IoT devices (MQTT subscribers) that analyze them and start a specific operation like opening a door and turning the alarm on/off.
Results. Five females and five males of different ages from 8 to 59 years old examined the control of smart home appliances with the Sichiray TGAM brainwave sensor kit. Everyone successfully handled the Sichiray headset and showed satisfaction with the brain-to-thing system.
Conclusions. In this work, a smart home concept for immobilized people was developed using the brain-to-thing approach and the MQTT communication between the MQTT publisher, Sichiray TGAM brainwave EEG sensor kit connected via Bluetooth to the Arduino Mega microcontroller, and edge IoT devices total priced at USD 150. The most likely prospect of the presented work is to produce the sample that is ready to market.