Publication:
A System to Notify Real-Time Radio Signal Failures and Predict the Possibility of Failures - LOST TRANSMISSION

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Article

Date

2022-03-31

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University Of Bahrain

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Abstract

The 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.

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Radio Signal Failure, Iot, Machine Learning, Logistic Regression, Nodemcu Esp32, Mobile App

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