With the improvement of the degree of aging,the traditional pension model can no longer meet the growing needs of the elderly.Therefore,it is necessary to use the intelligent means of information technology to improve...With the improvement of the degree of aging,the traditional pension model can no longer meet the growing needs of the elderly.Therefore,it is necessary to use the intelligent means of information technology to improve the level of pension services.This paper will integrate multi-sensor fusion technology,NB-IoT communication technology and cloud platform technology to develop and design a smart pension online monitoring system to realize real-time collection of human health and motion status information and realize monitoring platform management.In this system,STM32 microcontroller will be used as the main control module,and MAX30102,ADXL345 and DS18B20 sensors will be used to collect the heart rate,blood oxygen,displacement and body temperature of the human body in real time.On the one hand,the communication part is completed by the BC20 Internet of Things module.The data transmission between the terminal detection device and the cloud platform,on the other hand,the HC-42 Bluetooth module is used to complete the data communication with the mobile phone.The test results show that the system can collect and process data accurately in real time and maintain good communication with the cloud platform and mobile phone.The designed system has strong pertinence,easy operation,high reliability and broad development prospects.展开更多
The adoption of Internet of Things(IoT)sensing devices is growing rapidly due to their ability to provide realtime services.However,it is constrained by limited data storage and processing power.It offloads its massiv...The adoption of Internet of Things(IoT)sensing devices is growing rapidly due to their ability to provide realtime services.However,it is constrained by limited data storage and processing power.It offloads its massive data stream to edge devices and the cloud for adequate storage and processing.This further leads to the challenges of data outliers,data redundancies,and cloud resource load balancing that would affect the execution and outcome of data streams.This paper presents a review of existing analytics algorithms deployed on IoT-enabled edge cloud infrastructure that resolved the challenges of data outliers,data redundancies,and cloud resource load balancing.The review highlights the problems solved,the results,the weaknesses of the existing algorithms,and the physical and virtual cloud storage servers for resource load balancing.In addition,it discusses the adoption of network protocols that govern the interaction between the three-layer architecture of IoT sensing devices enabled edge cloud and its prevailing challenges.A total of 72 algorithms covering the categories of classification,regression,clustering,deep learning,and optimization have been reviewed.The classification approach has been widely adopted to solve the problem of redundant data,while clustering and optimization approaches are more used for outlier detection and cloud resource allocation.展开更多
针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Nar...针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Narrow Band Internet of Things)上传至OneNET云平台。经数据分析后以可视化方式呈现,对异常数据触发报警实时响应。通过手机APP实现数据实时监测及一键处置。经测试,监控系统报警准确率高于97.2%,数据延迟低于50 ms,表明该系统能够实现消防火警的无线远程监控,并做出快速反应,满足中小微企业和普通家庭用户的消防监控需要。展开更多
基金supported by Jiangsu Provincial Natural Science Fund(BK20150247)the Fundamental Research Funds for Postgraduate Research&Practice Innovation Program of Jiangsu Province(XSJCX22_36,XSJCX22_44,SJCX22_1479)
文摘With the improvement of the degree of aging,the traditional pension model can no longer meet the growing needs of the elderly.Therefore,it is necessary to use the intelligent means of information technology to improve the level of pension services.This paper will integrate multi-sensor fusion technology,NB-IoT communication technology and cloud platform technology to develop and design a smart pension online monitoring system to realize real-time collection of human health and motion status information and realize monitoring platform management.In this system,STM32 microcontroller will be used as the main control module,and MAX30102,ADXL345 and DS18B20 sensors will be used to collect the heart rate,blood oxygen,displacement and body temperature of the human body in real time.On the one hand,the communication part is completed by the BC20 Internet of Things module.The data transmission between the terminal detection device and the cloud platform,on the other hand,the HC-42 Bluetooth module is used to complete the data communication with the mobile phone.The test results show that the system can collect and process data accurately in real time and maintain good communication with the cloud platform and mobile phone.The designed system has strong pertinence,easy operation,high reliability and broad development prospects.
文摘The adoption of Internet of Things(IoT)sensing devices is growing rapidly due to their ability to provide realtime services.However,it is constrained by limited data storage and processing power.It offloads its massive data stream to edge devices and the cloud for adequate storage and processing.This further leads to the challenges of data outliers,data redundancies,and cloud resource load balancing that would affect the execution and outcome of data streams.This paper presents a review of existing analytics algorithms deployed on IoT-enabled edge cloud infrastructure that resolved the challenges of data outliers,data redundancies,and cloud resource load balancing.The review highlights the problems solved,the results,the weaknesses of the existing algorithms,and the physical and virtual cloud storage servers for resource load balancing.In addition,it discusses the adoption of network protocols that govern the interaction between the three-layer architecture of IoT sensing devices enabled edge cloud and its prevailing challenges.A total of 72 algorithms covering the categories of classification,regression,clustering,deep learning,and optimization have been reviewed.The classification approach has been widely adopted to solve the problem of redundant data,while clustering and optimization approaches are more used for outlier detection and cloud resource allocation.
文摘针对传统消防监控系统存在开发成本高、误警率高、实时监控不便的问题,提出一种基于物联网云平台的智慧消防远程监控系统。采用STM32单片机作为中枢控制芯片,经多传感器采集温度、湿度、烟雾、火焰等环境数据,通过窄带物联网(NB-IoT,Narrow Band Internet of Things)上传至OneNET云平台。经数据分析后以可视化方式呈现,对异常数据触发报警实时响应。通过手机APP实现数据实时监测及一键处置。经测试,监控系统报警准确率高于97.2%,数据延迟低于50 ms,表明该系统能够实现消防火警的无线远程监控,并做出快速反应,满足中小微企业和普通家庭用户的消防监控需要。
