Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/13606
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMohammed, Abubakar Saddiq-
dc.contributor.authorMohammed, Yakub-
dc.contributor.authorDanladi, Clement-
dc.contributor.authorVictor, Aduh-
dc.contributor.authorAbdulkarim, Hauwa Talatu-
dc.contributor.authorEdoka, Romanus-
dc.date.accessioned2021-08-17T09:15:15Z-
dc.date.available2021-08-17T09:15:15Z-
dc.date.issued2019-
dc.identifier.citationAbubakar Saddiq Mohammeden_US
dc.identifier.urihttps://ieeexplore.ieee.org/xpl/conhome/904467/proceeding-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/13606-
dc.description.abstractWeb-based solutions that employs the use of Internet of Things (IoT), is continuously creating new application areas, including healthcare. This shows that, iHealth, real-time monitoring as well as remote patients monitoring, are expected to revolutionize the healthcare sector. IoT is nothing but communication between devices that contain embedded technology with existing internet infrastructure. This research work employs a smart data gathering method using a fuzzy logic assisted approach. The fuzzy scheme employed, helps make the system smart by helping the device make decisions on when and what data is to be sent depending on the inference made on various inputs from the physiological sensors. Performance analysis was carried out on the energy consumption pattern of the nodes which indicate that throughout the monitoring period of Ten (10) hours each day, for three days. The average energy consumed by the device when fuzzy assisted logic is used is 90.78 milli Watt (mW), while the average energy consumed when the conventional method is used is 128.5 mW. From the results, it was observed that power consumption is substantially reduced by about 37.72 mW (29.35%), when using the fuzzy assisted method as compared to when using the normal/conventional method.. It was equally observed that while using the fuzzy assisted logic, energy consumption only increased whenever there is an anomaly in the sensor reading.en_US
dc.description.sponsorshipNigerian Communications Commission (NCC)en_US
dc.language.isoenen_US
dc.publisherNile University of Nigeriaen_US
dc.relation.ispartofseriesICECCO 2019 IEEE;-
dc.subjectInternet of things (IoT)en_US
dc.subjectiHealthen_US
dc.subjectremote monitoringen_US
dc.subjectfuzzy logicen_US
dc.subjectenergy consumptionen_US
dc.titleDevelopment and Implementation of an Internet of Things (IOT) Based Remote Patient Monitoring Systemen_US
dc.title.alternative15th International Conference on Electronics Computer and Computation IEEE (ICECCO 2019)en_US
dc.typeArticleen_US
Appears in Collections:Telecommunication Engineering

Files in This Item:
File Description SizeFormat 
CPN1 IOT.pdfINTERNET OF THINGS (IOT) BASED REMOTE PATIENT MONITORING SYSTEM292.77 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.