Acquiring hands-on skills is nowadays key for engineers in the context of Industry 4.0. However, it is not always possible to achieve this in person. Therefore, it is essential to be able to conduct skill acquisition from a remote location. To support the development of remote labs for experimentation, this work proposes the development of an open Industry 4.0 remote platform that can be easily configured and scaled to develop new remote labs for IoT (Internet of Things), cybersecurity, perception systems, robotics, AI (artificial intelligence), etc. Over time, these capabilities will enable the development of sustainable Industry 4.0 remote labs. These labs will coexist on the same Industry 4.0 platform, as our proposed Industry 4.0 remote platform is capable of connecting multiple heterogeneous types of devices for remote programming. In this way, it is possible to easily design open remote labs for the digital transition to Industry 4.0 in a standardized way, which is the main research goal of our In4Labs project. Several users already conducted a series of IoT experiments on our remote Industry 4.0 platform, providing useful recommendations to be included in future versions of the platform.

Massive Open Online Courses (MOOCs) have established a new paradigm in education, enabling asynchronous, remote learning. Although MOOCs offer diverse educational content to students, comprehensive and realistic education requires hands‐on training. Therefore, we present our integration of remote laboratories within a MOOC focused on Industry 4.0, together with a mixed‐methods analysis combining demographic data, questionnaire responses, platform logs, and remote laboratory server records. The course incorporated seven distinct laboratories in two categories: remote Arduino‐based laboratories, which connected physical devices to the MOOC, and a virtual infrastructure based on JupyterHub to support practical activities. Our findings indicate that the majority of participants in our MOOC were actively employed, with a mean age of 46.9 years, and males representing 88%. The students were mainly motivated by personal and professional growth, and 66% of these learners had no prior remote laboratory experience. Learners reported generally positive perceptions of the laboratory experience, including high levels of interest, usefulness, and self‐efficacy, although engagement varied substantially across participants. Behavioral analyses revealed that students who ultimately pursued certification showed markedly higher participation and involvement in the remote laboratories than those who did not. At the same time, the course exhibited the substantial dropout patterns commonly reported in MOOCs, indicating that the inclusion of remote laboratories does not by itself eliminate persistence challenges. Our work provides an illustrative example of integrating remote laboratories into a MOOC and offers an analysis of enrolled students, delivering valuable findings for future researchers.

Distance learning imposes specific challenges to provide quality education. Technology is a great opportunity for educational improvement. In this work we analyze some challenges and we have shown that with the proper use of technology it is possible to overcome them. We introduce here a set of remote laboratories currently being used for control engineering education in our university, which contribute to teach several control engineering topics like perception systems and the use of sensors and actuators, cybersecurity and penetration testing of IoT smart sensors and similar devices that can be found in industry, computer system architecture and low-level programming of microprocessors to implement fast control algorithms. The value of this work lies not only in the utility of remote labs as learning tools but also in their implementation following IEEE standards and integrating modern devices and communication protocols with industrial application.