Indoor Smart Design Algorithm Based on Smart Home Sensor

被引:4
作者
Zheng, Ruili [1 ]
机构
[1] Sch Art & Design Pingdingshan Univ, Pingdingshan 467000, Henan, Peoples R China
关键词
D O I
10.1155/2022/2251046
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Modern home furnishings have solved the most basic housing problems, but how to make homes more informatized and modern has become the focus of people's growing concern. With the rapid development of information technology, improving the intelligent level of family life and modern lifestyle is bound to be the trend of future development. This paper studies a smart home control system based on wireless sensor network positioning, which can perceive the home environment through the sensor module, and the control module can automatically control common electrical appliances to achieve real-time data monitoring and alarm functions. Specifically, it includes a positioning module, a communication module, and a server: the positioning module is connected to the server through the communication module, and the positioning module is used to obtain user location information in real time and report user location information to the server at intervals. The server receives the user reported at intervals through the communication module. Location information and remotely control smart home devices based on user location information. The research results show that the method proposed in this paper can separately monitor each part of the home and send it to the home appliance control module through the server to control the home appliance, optimize the living environment, and realize the remote control and monitoring of the smart home.
引用
收藏
页数:10
相关论文
共 29 条
[1]   Minimizing total interference in asymmetric sensor networks [J].
Abu-Affash, A. Karim ;
Carmi, Paz ;
Katz, Matthew J. .
THEORETICAL COMPUTER SCIENCE, 2021, 889 :171-181
[2]  
Brander JA, 2017, Q REV ECON FINANC, V65, P249, DOI 10.1016/j.qref.2017.01.010
[3]   An industrial IoT sensor system for high-temperature measurement [J].
Chang, Victor ;
Martin, Craig .
COMPUTERS & ELECTRICAL ENGINEERING, 2021, 95
[4]   Queue length estimation from connected vehicles with range measurement sensors at traffic signals [J].
Comert, Gurcan ;
Cetin, Mecit .
APPLIED MATHEMATICAL MODELLING, 2021, 99 :418-434
[5]  
Dhanusha C., 2021, IOP Conference Series: Materials Science and Engineering, V1074, DOI 10.1088/1757-899X/1074/1/012014
[6]   Predicting unusual energy consumption events from smart home sensor network by data stream mining with misclassified recall [J].
Fong, Simon ;
Li, Jiaxue ;
Song, Wei ;
Tian, Yifei ;
Wong, Raymond K. ;
Dey, Nilanjan .
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2018, 9 (04) :1197-1221
[7]  
Gengyi X, 2021, IOP C SERIES EARTH E, V769, P343
[8]   The Association Between the Single Leg Hop Test and Lower-Extremity Injuries in Female Athletes: A Critically Appraised Topic [J].
Guild, Paige ;
Lininger, Monica R. ;
Warren, Meghan .
JOURNAL OF SPORT REHABILITATION, 2021, 30 (02) :320-326
[9]   Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods [J].
Gupta, Prankit ;
McClatchey, Richard ;
Caleb-Solly, Praminda .
NEURAL COMPUTING & APPLICATIONS, 2020, 32 (16) :12351-12362
[10]   Approximation algorithms for the connected sensor cover problem [J].
Huang, Lingxiao ;
Li, Jian ;
Shi, Qicai .
THEORETICAL COMPUTER SCIENCE, 2020, 809 :563-574