Visible to the public Design of Intelligent Home Security Monitoring System Based on Android

TitleDesign of Intelligent Home Security Monitoring System Based on Android
Publication TypeConference Paper
Year of Publication2018
AuthorsWang, X., Li, J.
Conference Name2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC)
Date Publishedmay
KeywordsAndroid (operating system), Android remote operation, Androids, carrier transmission on power lines, compositionality, computerised monitoring, condition monitoring, control engineering computing, domestic appliances, embedded Linux, Embedded systems, health status monitoring, home computing, Humanoid robots, Intelligent Data and Security, Intelligent Data Security, intelligent devices, intelligent electrical appliances, Intelligent home, intelligent home condition monitoring, intelligent home drivers development, intelligent home safety assessment, intelligent home security monitoring system, intelligent home-based remote monitoring system, Internet, Internet of Things, Internet-based Internet-of-Things technology, internetworking, Linux, Logic gates, microcontrollers, MVP mode, MVP model, network congestion, network data model, network nodes, neural nets, Neural networks, Neurons, Operational Data, Power Line Communication, power line communication network, pubcrawl, remote monitoring, Resiliency, routing nodes, S3C2440A microcontrollers, safety monitoring, Scalability, security, system data, telecommunication network routing, Temperature distribution, Water heating
AbstractIn view of the problem that the health status and safety monitoring of the traditional intelligent home are mainly dependent on the manual inspection, this paper introduces the intelligent home-based remote monitoring system by introducing the Internet-based Internet of Things technology into the intelligent home condition monitoring and safety assessment. The system's Android remote operation based on the MVP model to develop applications, the use of neural networks to deal with users daily use of operational data to establish the network data model, combined with S3C2440A microcontrollers in the gateway to the embedded Linux to facilitate different intelligent home drivers development. Finally, the power line communication network is used to connect the intelligent electrical appliances to the gateway. By calculating the success rate of the routing nodes, the success rate of the network nodes of 15 intelligent devices is 98.33%. The system can intelligent home many electrical appliances at the same time monitoring, to solve the system data and network congestion caused by the problem can not he security monitoring.
Citation Keywang_design_2018