Smart Airtime Vending Machine: A Case of Nyamasheke District, Nyabitekeri Sector
DOI:
https://doi.org/10.47672/ejt.1355Keywords:
IoT, Air time, Vending Machine, Machine LearningAbstract
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.
Downloads
References
Alharbe, N., Atkins, A. S., & Akbari, A. S. (2013, December). Application of ZigBee and RFID Technologies in Healthcare in Conjunction with the Internet of Things. In Proceedings of International Conference on Advances in Mobile Computing & Multimedia (pp. 191-195).
Ali, B. (2016). Internet of Things Based Smart Homes: Security Risk Assessment and Recommendations.
Alrehily, A., Fallatah, R., & Thayananthan, V. (2015). Design of Vending Machine using Finite State Machine and Visual Automata Simulator. International Journal of Computer Applications, 115(18)
Amin, R., & Rahman, M. (2018). Artificial Intelligence and IoT in Dairy Farm. Malaysian Journal of Medical and Biological Research, 5(2), 131-140.
Benezeth, Y., Emile, B., Laurent, H., & Rosenberger, C. (2008, July). A real time human detection system based on far infrared vision. In International Conference on Image and Signal Processing (pp. 76-84). Springer, Berlin, Heidelberg.
Bihlmayr, W. (2007). OLEO Display Driver for the HCS08 Family. Freescale Semiconductor Application Note, 1-42.
Chen, X. Y., & Jin, Z. G. (2012). Research on key technology and applications for internet of things. Physics Procedia, 33, 561-566.
Desai, P., Jadhav, M., Maruti, S., Patil, M., Shivaji, P., Giri, M., & Sambhaji, N. (2017). Automatic chocolate vending machine by using Arduino Uno. International Journal of Innovative Research in Computer Science &Technology (IJIRCST), ISSN, 2347-5552.
Dua, A., Rustagi, C., & Bhardawaj, A. (2014). A novel approach to designing intelligent vending machines. International Journal in IT & Engineering, 2(12), 38-50.
Eckert, M. (2014). Fpga-based system virtual machines (Doctoral dissertation, Universitätsbibliothek der HSU/UniBwH).
Ekşioǧlu, M., Kiriş, E., Çakir, T., Güvendik, M., Koyutürk, E. D., & Yilmaz, M. (2013). Design, User Experience, and Usability. Web, Mobile, and Product Design. Lect. Notes Comput. Sci.(including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), 8015, 173-82.
Goddard, W., & Melville, S. (2004). Research methodology: An introduction. Juta and Company Ltd
Gruber, S., BUBER, R., RUSO, B., & GADNER, J. (2005). The commodity vending machine. InForum Ware International, 2, 32-42.
Hall, A. (2015). Vending Machines.
Husain, B. M., & Monnet, W. M. A. (2017, February). An internet of things Application through GPRS. In 3rd International Engineering Conference on Developments in Civil & Computer Engineering Applications (p. 153).
Jadhv, R., Jejurkar, M., Kave, P., & Chaudhari, H. P. (2017). Smart coffee vending machine using RFID. Instrumentation Engineering department, Advances in Wireless and Mobile Communications, 10, 793-800.
Karthika, M. V., Jagadeesh, S., Karthick, R. A., & Teja, K. S. (2019). Smart Computerized Vending Machine Enhanced With IOT Technology
Kim, K., Park, D. H., Bang, H., Hong, G., & Jin, S. I. (2014, January). Smart coffee vending machine using sensor and actuator networks. In 2014 IEEE International Conference on Consumer Electronics (ICCE) (pp. 71-72). IEEE.
Kisan, B., & Bhise, S. K. (2017). Zigbee and RFID Based Student Attendance Monitoring System with Energy Saving.
Kocurek, C. A. (2014). Rendering Novelty Mundane: Technical Manuals in the Golden Age of Coin-Op Computer Games. Computer Games and Technical Communication: Critical Methods and Applications at the Intersection, 55-67.
Lin, Y. B., Rao, H. C. H., & Chlamtac, I. (2001). General Packet Radio Service (GPRS): architecture, interfaces, and deployment. Wireless Communications and Mobile Computing, 1(1), 77-92.
Manmohan, M. H., Ankitha, N. B., Aishwarya, G., & Trupti, K. (2019). A review based on milk and it's vending. Int J Res Eng Sci Manag Res, 2, 346-348.
Maulud, D., & Abdulazeez, A. M. (2020). A review on linear regression comprehensive in machine learning. Journal of Applied Science and Technology Trends, 1(4), 140-147.
Mbongue, J., Hategekimana, F., Kwadjo, D. T., Andrews, D., & Bobda, C. (2018, July). Fpgavirt: A novel virtualization framework for fpgas in the cloud. In 2018 IEEE 11th International Conference on Cloud Computing (CLOUD) (pp. 862-865). IEEE.
Megel, M. E., & Heermann, J. A. (1994). Methods of data collection. Plastic surgical nursing: official journal of the American Society of Plastic and Reconstructive Surgical Nurses, 14(2), 109-110.
Murena, E., Sibanda, V., Sibanda, S., & Mpofu, K. (2020). Design of a control system for a vending machine. Procedia CIRP, 91, 758-763.
Patel, K. K., Patel, S. M., & Scholar, P. (2016). Internet of things-IOT: definition, characteristics, architecture, enabling technologies, application & future challenges. International journal of engineering science and computing, 6(5).
Plaha, B., & Singh, B. (2012). Design and Development of Vending Machine using AVR ATmega 8515 Microcontroller. International Journal of Advanced Research in Computer Science, 3(3).
Pongswatd, S., Smerpitak, K., & Thepmanee, T. (2020). Smart coffee vending machine based on IoT concept. International Journal of Innovative Computing, Information and Control, 16(4), 1441-1448.
Ramzan, A., Rehman, S., & Perwaiz, A. (2017, April). RFID technology: Beyond cash-based methods in vending machine. In 2017 2nd International Conference on Control and Robotics Engineering (ICCRE) (pp. 189-193). IEEE.
Ratnasri, N., & Sharmilan, T. (2021). Vending Machine Technologies: A Review Article. International Journal of Sciences: Basic and Applied Research (IJSBAR), 58(2), 160-166.
Sibanda, V., Munetsi, L., Mpofu, K., Murena, E., & Trimble, J. (2020). Design of a high-tech vending machine. Procedia CIRP, 91, 678-683.
Vijayaragavan, M., Rajendirakumar, R., & Nakkeeran, R. (2020). Automatic milk ATM machine for rural area people. Int J Innov Technol Explor Eng, 9(2), 1201-1203.
Yang, Z. L., Zhao, L. Y., & Gu, L. T. (2015). The Internet of things coffee vending machine. In Applied Mechanics and Materials (Vol. 734, pp. 340-344). Trans Tech Publications Ltd.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Habumugisha Fulgence, Gasana James Madson, Ineza Yves, Shumbusho Jean Pierre, Uwantege Stellah Prossy, Habyarimana Projecte
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
