Educating on IoT and AI: An Automotive-Based Case Study

This paper, belonging to the Research-to-Practice category, presents a training experience within the 'Networks and Protocols for IoT' course of the master's degree program in electrical engineering aimed at integrating Artificial Intelligence (AI) and the Internet of Things (IoT) through an active teaching approach. The intervention focused on designing and implementing a prototype for autonomous driving with an obstacle detection system, allowing students to apply theoretical knowledge to a realistic and technically challenging problem. Established project-based, problem-based, and collaborative learning models inspired the experience. These approaches were implemented through a pathway that guided students, organized into a team, from problem analysis through development and experimentation. Two structured questionnaires were administered to assess the effectiveness of the experience: the first surveyed the perceived level of skills acquired in AI and IoT, and the second investigated the impact of the three teaching methodologies adopted. Analysis of the data, both quantitative and qualitative, showed significant results in improvement in AI skills, particularly in the design and training of deep learning models, while in IoT system design and sensor and boards integration, students, who were already starting from excellent basis, better contextualized their knowledge in the proposed case study.