Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2809
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dc.contributor.authorSumithraarachchi, G-
dc.contributor.authorAhamed, R-
dc.contributor.authorVithana, N-
dc.date.accessioned2022-07-20T05:37:58Z-
dc.date.available2022-07-20T05:37:58Z-
dc.date.issued2022-03-31-
dc.identifier.issn(2210-142X-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/2809-
dc.description.abstractThe focal point of this work was to build a troubleshooting mobile application, which provides an alert notification when RT (Radio Transmission) failures happen at radio outstations and enables predicting the possibilities of radio signal failures based on weather components. The current radio signal failure notifying process is being done half-manual at most of the radio stations while not providing immediate notifications to the radio station staff. A cloud platform, IoT (Internet of Things) technology, and machine learning technique are combined with the aforementioned system to provide fast service to the radio station end-users. The IoT-based Wi-Fi module distinguishes RT failures of each outstation. When weather data is detected, the predictive model displays the possibilities of radio signal failures. The cloud-based functionalities push instant notifications which make the system highly reliable. A key benefit of this system is that even though the users are out of the radio station, the system will be one notification away from the users to notify sudden RT failures.en_US
dc.language.isoenen_US
dc.publisherUniversity Of Bahrainen_US
dc.relation.ispartofseriesInternational Journal of Computing and Digital Systems;11, No.1-
dc.subjectRadio Signal Failureen_US
dc.subjectIoten_US
dc.subjectMachine Learningen_US
dc.subjectLogistic Regressionen_US
dc.subjectNodemcu Esp32en_US
dc.subjectMobile Appen_US
dc.titleA System to Notify Real-Time Radio Signal Failures and Predict the Possibility of Failures - LOST TRANSMISSIONen_US
dc.typeArticleen_US
dc.identifier.doihttps://dx.doi.org/10.12785/ijcds/110187en_US
Appears in Collections:Research Papers - Open Access Research
Research Publications -Dept of Information Technology

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