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
为保障机场助航灯光系统稳定运行,提升突发故障响应能力,文章设计并实现了一种基于物联网(Internet of Things,IoT)技术的助航灯光站内设备报警平台。该平台通过在灯光站内设备间、机坪与低压供电系统中部署多种传感器,实时采集温湿度...为保障机场助航灯光系统稳定运行,提升突发故障响应能力,文章设计并实现了一种基于物联网(Internet of Things,IoT)技术的助航灯光站内设备报警平台。该平台通过在灯光站内设备间、机坪与低压供电系统中部署多种传感器,实时采集温湿度、电气参数、电缆沟水位及机坪照度等数据,经边缘节点初步处理后,通过无线网络上传至数据传输单元(Data Transfer Unit,DTU)云平台。云平台对数据进行存储、分析与智能诊断,结合阈值模型实现故障分类与精准报警。该平台显著提升故障检测的及时性与准确性,降低人工巡检成本,增强系统安全裕度,具备良好的实用性与推广价值。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
Cloud internet of things(IoT)is an emerging technology that is already impelling the daily activities of our lives.However,the enormous resources(data and physical features of things)generated from Cloud-enabled IoT s...Cloud internet of things(IoT)is an emerging technology that is already impelling the daily activities of our lives.However,the enormous resources(data and physical features of things)generated from Cloud-enabled IoT sensing devices are lacking suitable managerial approaches.Existing research surveys on Cloud IoT mainly focused on its fundamentals,definitions and layered architecture as well as security challenges.Going by the current literature,none of the existing researches is yet to provide a detailed analysis on the approaches deployed to manage the heterogeneous and dynamic resource data generated by sensor devices in the cloud-enabled IoT paradigm.Hence,to bridge this gap,the existing algorithms designed to manage resource data on various CloudloT application domains are investigated and analyzed.The emergence of CloudloT,followed by previous related survey articles in this field,which motivated the current study is presented.Furthermore,the utilization of simulation environment,highlighting the programming languages and a brief description of the simulation pack-ages adopted to design and evaluate the performance of the algorithms are examined.The utilization of diverse network communication protocols and gateways to aid resource dissemina-tion in the cloud-enabled IoT network infrastructure are also discussed.The future work as discussed in previous researches,which pave the way for future research directions in this field is also presented,and ends with concluding remarks.展开更多
This survey paper provides a general overview on Cloud Computing. The topics that are discussed include characteristics, deployment and service models as well drawbacks. Major aspects of Cloud Computing are explained ...This survey paper provides a general overview on Cloud Computing. The topics that are discussed include characteristics, deployment and service models as well drawbacks. Major aspects of Cloud Computing are explained to give the reader a clearer understanding on the complexity of the platform. Following this, several security issues and countermeasures are also discussed to show the major issues and obstacles that Cloud Computing faces as it is being implemented further. The major part of countermeasures focuses on Intrusion Detection Systems. Moving towards Mobile Cloud Computing and Internet of Things, this survey paper gives a general explanation on the applications and potential that comes with the integration of Cloud Computing with any device that has Internet connectivity as well as the challenges that are before it.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.
文摘为保障机场助航灯光系统稳定运行,提升突发故障响应能力,文章设计并实现了一种基于物联网(Internet of Things,IoT)技术的助航灯光站内设备报警平台。该平台通过在灯光站内设备间、机坪与低压供电系统中部署多种传感器,实时采集温湿度、电气参数、电缆沟水位及机坪照度等数据,经边缘节点初步处理后,通过无线网络上传至数据传输单元(Data Transfer Unit,DTU)云平台。云平台对数据进行存储、分析与智能诊断,结合阈值模型实现故障分类与精准报警。该平台显著提升故障检测的及时性与准确性,降低人工巡检成本,增强系统安全裕度,具备良好的实用性与推广价值。
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.
基金support of the Research Management Centre(RMC)Universiti Teknologi Malaysia with the research grant(QJ 130000.2451.07G48)We would like to express our sincere thanks to all researchers who devoted their time and knowledge to the completeness of this research project。
文摘Cloud internet of things(IoT)is an emerging technology that is already impelling the daily activities of our lives.However,the enormous resources(data and physical features of things)generated from Cloud-enabled IoT sensing devices are lacking suitable managerial approaches.Existing research surveys on Cloud IoT mainly focused on its fundamentals,definitions and layered architecture as well as security challenges.Going by the current literature,none of the existing researches is yet to provide a detailed analysis on the approaches deployed to manage the heterogeneous and dynamic resource data generated by sensor devices in the cloud-enabled IoT paradigm.Hence,to bridge this gap,the existing algorithms designed to manage resource data on various CloudloT application domains are investigated and analyzed.The emergence of CloudloT,followed by previous related survey articles in this field,which motivated the current study is presented.Furthermore,the utilization of simulation environment,highlighting the programming languages and a brief description of the simulation pack-ages adopted to design and evaluate the performance of the algorithms are examined.The utilization of diverse network communication protocols and gateways to aid resource dissemina-tion in the cloud-enabled IoT network infrastructure are also discussed.The future work as discussed in previous researches,which pave the way for future research directions in this field is also presented,and ends with concluding remarks.
文摘This survey paper provides a general overview on Cloud Computing. The topics that are discussed include characteristics, deployment and service models as well drawbacks. Major aspects of Cloud Computing are explained to give the reader a clearer understanding on the complexity of the platform. Following this, several security issues and countermeasures are also discussed to show the major issues and obstacles that Cloud Computing faces as it is being implemented further. The major part of countermeasures focuses on Intrusion Detection Systems. Moving towards Mobile Cloud Computing and Internet of Things, this survey paper gives a general explanation on the applications and potential that comes with the integration of Cloud Computing with any device that has Internet connectivity as well as the challenges that are before it.
