The monitoring and managing application of cloud computing based on Internet of Things

Luo, Shiliang; Ren, Bin

doi:10.1016/j.cmpb.2016.03.024

Cited by 56 publications

(19 citation statements)

References 7 publications

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“…The patient health monitoring system creates aremote interaction between the patient and doctor. The tiny sensors like temperature, Heartbeat, Blood pressure are arranged in a manner to the patients to form an efficient Body sensor network [9].…”

Section: Literature Surveymentioning

confidence: 99%

Pervasive Patient Health Monitoring System

2017

IJIET

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Abstract-The exponentially growing health care cost and increasing patient have promoted a serious need to revolutionize health care systems. The need to bring health care cost into a sustainable range is urgent issue that needs to be addressed. One possible way to address the challenges facing the health care industry is by caring for patient in their environments such as their residences. A pervasive patient health monitoring (PPHM) system infrastructure is developed to provide remote monitoring of patients. PPHM is placed on integrated cloud computing and internet of things technology. Continuous monitoring is performed when an intensive monitoring is needed for patients. In this case, sensors continuously collect vital data and send it to the personal server. The on-demand monitoring occurs when a request from any authorized person within the system such as patients, doctors or nurses is generated. Experimental analysis have shown that the proposed frame work is efficient with very high classification accuracy. The database on patient's health is maintained and the data can be retrieved whenever needed. An alert system is provided in case of emergency.

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Section: Literature Surveymentioning

confidence: 99%

Pervasive Patient Health Monitoring System

2017

IJIET

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“…However, some challenges have rose from these developments and triggered the research attention in the up to date years which are unsolved by other researchers. Among the challenges, Energy awareness is considered as the foremost challenges under IoT [21]. In order to decrease the energy consumption in IoT, our projected technique uses OSEAP.…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Secure Energy Efficient Routing Protocol in Internet of Things

Reddy¹,

Babu²

2017

IJIES

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Abstract:Recently, Internet of Things (IoT) devices are highly utilized in diverse fields such as environmental monitoring, industries, smart home etc. Under such instance, a cluster head is selected among the diverse IoT devices of wireless Sensor Network (WSN) based IoT network to maintain the reliable network with efficient data transmission. To accomplish the efficient cluster head selection, we have used Fuzzy C-Means (FCM) clustering algorithm. Therefore, it is necessary to implement secure energy aware routing protocol in IoT. This paper proposed a novel method with the combination of Optimal Secured Energy Aware Protocol (OSEAP) and Improved Bacterial Foraging Optimization (IBFO) algorithm. The aforesaid challenges against the secure energy awareness objective under IoT are not yet dealt by any researchers. Furthermore, the Optimal Secured Energy Aware Protocol (OSEAP) and Improved Bacterial Foraging Optimization (IBFO) algorithm is one of the best methods to save more energy with security among the nodes. The performance analysis in terms of delay, throughput, and energy determined by comparing the proposed method with the existing method Secure Energy aware routing protocol (SEAP). Thus, the analysis of our implementation reveals the superior performance of the proposed method.

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“…As some network model arose at the historic moment, cloud computing as a new parallel computing technology also appeared on the network [2].As a new Internet, cloud computing is the further development of distributed computing, parallel computing and grid computing based computing model, is also the concept of computer science commercial implementation [3].…”

Section: Introductionmentioning

confidence: 99%

Study on Image Detection and Recognition based on Deep Neural Network under Cloud Computing Services

Liu¹,

Wang²,

Wang³

2017

Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

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Abstract. Deep learning model has the ability to extract image features independently, and also can extract abstract features. This paper studied on image detection and recognition based on deep neural network under cloud computing service. Firstly, the cloud computing service model was introduced. Secondly, the learning network was designed by the optimization method. Lastly, the test results were analyzed by recall rate and confusion Matrix, convergence performance and comparison of accuracy. The results show the deep neural network under cloud computing services is a valid method for image detection and recognition.

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The monitoring and managing application of cloud computing based on Internet of Things

Cited by 56 publications

References 7 publications

Pervasive Patient Health Monitoring System

Pervasive Patient Health Monitoring System

An Evolutionary Secure Energy Efficient Routing Protocol in Internet of Things

Study on Image Detection and Recognition based on Deep Neural Network under Cloud Computing Services

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