Interdisciplinary Project Based Learning Approach for Machine Learning and Internet of Things

Abstract

This paper reports on the use of an interdisciplinary project-based learning approach for undergraduate engineering education in machine/deep learning, and the internet of things (IoT). Machine learning has evolved from pattern recognition and is an important element of artificial intelligence. IoT has also seen rapid growth in multiple application domains including embedded systems, wireless sensor networks, control systems, automation, and sensors. A challenge for traditional electrical/computer engineering curriculum is to effectively educate students in these areas through hands-on activities and projects. There is a need to develop a project-based learning approach to involve undergraduate students in real-world problem solving to develop use cases of machine learning and IoT. This paper reports on the implementation of an interdisciplinary project-based learning approach followed in the undergraduate electrical/computer engineering curriculum. The students were involved in solving real-world problems through machine/deep learning. They also developed IoT applications in multiple domains to address the limitations of existing systems and to go through the engineering design process. The qualitative results indicate that the PBL approach was highly effective in improving their learning outcomes.