Smart airtime vending machine
The proposed methodology consists of an IoT system where the customer will access the vending machine by inserting it into a coin to buy airtime. This research consists of three main parts, the first part is the interconnection of IoT hardware components that build the entire circuit and are linked to the cloud via GPRS/GSM communication technology, this part involves sensing components, data processing components, and actuators components.
The second part consists of coding using Arduino IDE that makes IoT system hardware operational and the last part is data processing and analytics using python programming and regression as a machine learning technique. The system monitoring is done through wireless radio, and the cloud data storage is secured and can be easily accessible by authorized users via a web interface. The battery is used for powering the system and the solar panel is for recharging the battery. All transaction data are recorded and the given date returns the day type between working days, weekends, and the session of the day.
The expected results of this research include an IoT system that is developed and implemented to help both airtime agents and customers to sell and buy airtime using a coin-based self-service airtime vending machine and the model that analyzes machine transaction data using Python programming and regression as a machine learning technique.
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