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Y F Hu
Faculty of Engineering and Informatics, University of Bradford, BD7 1DP, United Kingdom
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Engineering Industrial & Manufacturing Engineering

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Energy Efficient Healthcare Monitoring System using 5G Task Offloading: Energy Efficient Healthcare Monitoring System using 5G Task Offloading T Sigwele; A Naveed; Misfa Susanto; M Ali; Y F Hu
Journal of Engineering and Scientific Research Vol. 1 No. 2 (2019)
Publisher : Faculty of Engineering, Universitas Lampung Jl. Soemantri Brojonegoro No.1 Bandar Lampung, Indonesia 35141

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (818.874 KB) | DOI: 10.23960/jesr.v1i2.12

Abstract

Healthcare expenses can be significantly reduced, and lives saved by enabling the continuous monitoring of patient health remotely using Wireless Body Sensor Networks (WBSN). However, an energy efficient mobile gateway (e.g. 5G smartphone) is required which moves with the patient in real time to process the data from the bio sensors without depleting the battery. Thispaper proposes a 5G based healthcare cardiovascular disease Remote Monitoring system called 5GREM using Electrocardiogram (ECG) bio sensor as a BSN device. The aim is to monitor and analyse the patient’s heart rhythms and send emergency alerts during irregularities to the nearest caregivers, ambulance or physician to minimize heart attacks and heart failures while saving energy. Since ECG signal execution is computer intensive, requests from the ECG sensor are either executed locally on thegateway, offloaded to nearby mobile devices or to the 5G edge while considering the battery level, CPU level, transmission power, delays and task fail rate.
Similarity Analyzer for Semantic Interoperability of Electronic Health Records Using Artificial Intelligence (AI) A Naveed; Y F Hu; T Sigwele; G Mohi-Ud-Din; Misfa Susanto
Journal of Engineering and Scientific Research Vol. 1 No. 2 (2019)
Publisher : Faculty of Engineering, Universitas Lampung Jl. Soemantri Brojonegoro No.1 Bandar Lampung, Indonesia 35141

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.041 KB) | DOI: 10.23960/jesr.v1i2.13

Abstract

The introduction of Electronic Health Records (EHR) has opened possibilities for solving interoperability issues within the healthcare sector. However, even with the introduction of EHRs, healthcare systems like hospitals and pharmacies remain isolated with no sharing of EHRs due to semantic interoperability issues. This paper extends our previous work in which we proposed a framework that dealt with semantic interoperability and security of EHR. The extension is the proposal of a cloud-based similarity analyzer for data structuring, data mapping, data modeling and conflict removal using Word2vec Artificial Intelligence (AI) technique. Different types of conflicts are removed from data in order to model data into common data types which can be interpreted by different stakeholders
Co-Authors A Naveed G Mohi-Ud-Din M Ali Misfa Susanto T Sigwele