Academy & Industry Research Collaboration Center (AIRCC)

Volume 12, Number 16, September 2022

User Repairable and Customizable Buzzer System using Machine Learning and IoT System


Leheng Huang1 and Yu Sun2, 1USA, 2California State Polytechnic University, USA


The creation and sustainability of academic teams have long been unnecessarily difficult due to the exorbitant costs of purchasing and maintaining equipment [1][2]. These costs serve as a major barrier, especially in poorer areas where securing the funds for this equipment is difficult [3]. In addition, when the equipment eventually breaks, it is often difficult to repair, forcing academic teams to purchase a new set of equipment. This project attempts to provide a product that can drastically lower the equipment's costs and allow the user to modify and repair it as necessary. This project resulted in the development of the Argo Buzzer System which was created with input from experienced academic team members and it has proven that it is comparable to modern buzzer systems for a fraction of the cost [4]


Electronics, Machine learning, IoT system.