European Journal of Technology

Smart Airtime Vending Machine: A Case of Nyamasheke District, Nyabitekeri Sector

Sun, 19 Feb 2023 00:00:00 +0300

Purpose: The aim of this paper was undertaking modern technology by designing and implementing a smart airtime vending machine known as a self-service airtime vendor machine that will come as an additional method apart from the current airtime selling and buying methods which are mobile money, banking, airtime agent that involves theft of money and airtime loading mistakes and errors. It will help rural citizens to buy airtime using a coin where a customer has to enter the mobile number using a keypad then inset coin in airtime vending machine, and automatically the machine dispenses the airtime equivalent to the amount inserted.

Methodology: The methodology used 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, 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 for recharging the battery. All transaction data are recorded and given date returns the day type between working days, weekends, and the session of the day.

Findings: The results of the research include an IoT system that is developed and implemented to help both airtime agents and customers to sell and buy airtime using coin-based self-service airtime vending machine and the model that analyse machine transaction data using Python programming and regression as a machine learning technique.

Unique contribution to practice: It improved the airtime vending system's efficiency and sustainable management of airtime agent. It facilitates safe selling and buying of airtime across the country especially in rural areas where getting airtime seemed to be a problem. The Internet is also used for linking cloud platform and application users.it indicates that the vending machine can provide positive impact in society including self-service of airtime to citizens from nearby vendors, the distribution of machines country wide can increase employability.

IoT and AI Based Student’s Attendance Monitoring System to Mitigate the Dropout in Non-boarding Secondary Schools of Rwanda: A Case Study of Wisdom School Musanze

Tue, 21 Mar 2023 00:00:00 +0300

Purpose: This project aimed to test an IoT and AI based system that monitor students from home to schools, during class hours and from school to home and notify parents and school administrators about the irregularity observed to their respective children.

Methodology: In this project, secondary data was used and was retrieved from the school’s record of Wisdom School Musanze located in Musanze District. The main data to consider were sex whether male or female. Another important data was orphanage,whether pupil is orphan or not orphan, and school fees payment by checking whether student paid school fees or had not paid. These mentioned data were taken randomly from senior one (S1) to senior six (S6) in academic year 2020-2021.

Findings: The system is equipped of a finger print sensor to register and verify students and staff attendance, a Passive Infrared (PIR) sensor to detect the presence of human to wake-up the device, a real time clock to synchronize each generated report with the local time. A web application is developed to allow students real-time monitoring for parents and school administrators and the system is be able to generate a daily, monthly and annually report.

Unique contribution to theory, practice and policy: Classification machine learning with decision-tree algorithm is used to analyze data and generate a model to evaluate the impact of monitoring attendance on preventing students to dropout. The generated model with accuracy of 91.4% shows that keeping students’ attendance at high percentage would reduce significantly the dropout rate in secondary schools of Rwanda.

Comparative Analysis of Encryption Algorithms

Agbelusi Olutola, Matthew Olumuyiwa — Wed, 04 Jan 2023 00:00:00 +0300

Purpose: Encryption algorithm allows users to extend the assurance found in the physical world to the electronic world in the carrying out of our day-to-day activities. This research attempts to make a comparative evaluation of two encryption algorithms (Advanced Encryption Standard (AES) and Rivest Shamir Algorithm (RSA) in order to ascertain the most reliable in terms of their encryption time, decryption time, Key length, and cipher length.

Methodology: Java programming was used for the development and Mongo Db to generate data parsing.

Findings: The results obtained from the development revealed that AES is considered more efficient because it uses lesser time for encryption and decryption, reduces cipher and key length as compared with RSA which consumes longer encryption and decryption time, and increases cipher and key length. Excel package was also used to display the pictorial representation of the comparison between these algorithms.

Recommendation: Advanced encryption standard is recommended for security-based application developers because of the small time of encryption and decryption.