Cloud Based Fuzzy Healthcare System

Sundharakumar, K.B.; Dhivya, S.; Mohanavalli, S.; Chander, R. P. V.

doi:10.1016/j.procs.2015.04.076

Cited by 19 publications

(6 citation statements)

References 4 publications

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“…It was designed to obtain feedback from the patient’s previous health record, where the decision for constructing rules was processed by the FIS [23, 37, 44, 46]. The PHD were classified into low, normal, and high risk using fuzzy membership functions and fuzzy rules defined in FIS [47, 48]. Next, RL identified the best outcome of the action to maximize its total reward and the performance of the algorithm in a given time.…”

Section: Methodsmentioning

confidence: 99%

An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment

et al. 2019

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Fog computing (FC) is an evolving computing technology that operates in a distributed environment. FC aims to bring cloud computing features close to edge devices. The approach is expected to fulfill the minimum latency requirement for healthcare Internet-of-Things (IoT) devices. Healthcare IoT devices generate various volumes of healthcare data. This large volume of data results in high data traffic that causes network congestion and high latency. An increase in round-trip time delay owing to large data transmission and large hop counts between IoTs and cloud servers render healthcare data meaningless and inadequate for end-users. Time-sensitive healthcare applications require real-time data. Traditional cloud servers cannot fulfill the minimum latency demands of healthcare IoT devices and end-users. Therefore, communication latency, computation latency, and network latency must be reduced for IoT data transmission. FC affords the storage, processing, and analysis of data from cloud computing to a network edge to reduce high latency. A novel solution for the abovementioned problem is proposed herein. It includes an analytical model and a hybrid fuzzy-based reinforcement learning algorithm in an FC environment. The aim is to reduce high latency among healthcare IoTs, end-users, and cloud servers. The proposed intelligent FC analytical model and algorithm use a fuzzy inference system combined with reinforcement learning and neural network evolution strategies for data packet allocation and selection in an IoT–FC environment. The approach is tested on simulators iFogSim (Net-Beans) and Spyder (Python). The obtained results indicated the better performance of the proposed approach compared with existing methods.

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Section: Methodsmentioning

confidence: 99%

An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment

et al. 2019

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“…Perancangan desain suatu produk atau jasa dengan menggunakan pendekatan rumah kualitas atau Quality Function Deployment (QFD) yang mampu membawa proses desain ke proses produk secara baik dan efisien sesuai dengan yang diinginkan pelanggan. Aplikasi QFD untuk meningkatkan kualitas di sektor jasa atau pelayanan sudah diteliti di beberapa bidang, diantaranya pada sektor jasa transportasi publik (Deveci et al, 2019), jasa layanan kesehatan (Lee et al, 2015;Sundharakumar, 2015), layanan perpustakaan (Chen & Chou, 2011), dan pelayanan pariwisata (Djunaedi, 2015). Hingga saat ini belum ditemukan riset yang mengkaji bagaimana implementasi QFD pada pelayanan sertifikasi pertanahan.…”

Section: Pendahuluanunclassified

Usulan perbaikan kualitas pelayanan penerbitan sertifikat tanah dengan pendekatan Quality Function Deployment

Martia¹

2020

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Quality Function Deployment uses a very different approach because it adds value to the product by maximizing positive quality, such as ease of use, pleasure, and luxury. Visible or invisible customer needs will be handled by Quality Function Deployment. Research analysis found 31 service quality attributes, consisting of 10 variables of simplicity, clarity, time certainty, accuracy, security, responsibility, completeness of infrastructure, ease of access, friendly discipline, comfort. There were still 23 House of Quality results that did not meet customer satisfaction that was prioritized for improvement. The priority order of improvement is most important to the requirements of the customers, namely the responsibility of the officer in the work with a relative importance of 26,225 in stage 1 and Making an assessment of the performance of the officer with a relative importance of 18,424 is the highest value for QFD stage 2.

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“…For that reason, fuzzy logic is a suitable way to provide the doctors with the support needed for handling of linguistic concepts and avoiding such loss of precision. Fuzzy logic technologies are applied across many areas of healthcare, and they have been approved as quite effective [14,15]. For example, in [16], a fuzzy medical diagnosis expert system based on quantiles of diagnostic measures was presented, while the work presented in [17] focuses on coronary heart disease risk determination based on cholesterol measurements.…”

Section: A Fuzzy Logicmentioning

confidence: 99%

Tackling the COVID-19 Conspiracies: The Data-Driven Approach

Petrović

2020

2020 55th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)

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Apart from obvious impact on many aspects of our everyday lives, the current COVID-19 pandemic has led to occurrence many conspiracy theories as side-effect, especially via social media. However, in such confusion among population, the situation becomes even more difficult to handle, which could potentially have even more dramatic consequences on global economy and increase the number of lives lost. In this paper, a data-driven framework for analysis of the facts related to COVID-19 disease is proposed. The proposed implementation leverages semantic knowledge representation, fuzzy reasoning and correlation analysis.

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Cloud Based Fuzzy Healthcare System

Cited by 19 publications

References 4 publications

An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment

An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment

Usulan perbaikan kualitas pelayanan penerbitan sertifikat tanah dengan pendekatan Quality Function Deployment

Tackling the COVID-19 Conspiracies: The Data-Driven Approach

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