Remote Lab Access: A Powerful Tool Beyond the Pandemic

The access to the tools used in laboratory sessions outside official teaching hours is difficult for students. For that purpose, a remote access architecture has been deployed. The proposed solution has three main tools: a management tool developed by the authors, a web-based remote desktop application based on Apache Guacamole and a monitoring and control tool based on the Veyon software with which teachers are able to full monitor students' screens or even remote-control them. The architecture allows both remote teaching and a way for students to access lab resources from home. Even though the solution has been mainly used for the exceptional situation of the COVID-19 pandemic, these tools provide a powerful way to use learning resources in traditional teaching scenarios. © 2022 IEEE.

Raspberry Pi-based cluster network for the emulation of sensor networks in remote teaching

Due to their versatility, sensor networks and Internet of Things (IoT) have become technologies of a great importance in many modern applications in so-diverse ambits such as environmental monitoring and smart cities. Therefore, these are included in the contents of the subject 'Advanced Sensor Network Infrastructure' of the Master on Intelligent Systems on Energy and Transport of the University of Seville. This subject serves as an introduction to sensor networks, their applications, and their operating principles. Its schedule includes laboratory lessons in which the students use various sensor devices for learning about the existing communication and processing methods. The health crisis caused by the COVID-19 has made difficult that all the students have physical access to the laboratory at the same time, which forced to adapt the existing materials and facilities. In this sense, to solve this problem, a Raspberry Pi-based computer network has been deployed to allow the emulation of a sensor network while providing external remote access to the students for them to perform their laboratory tasks. At the same time, this proposal has expanded the subject contents to cover several data processing layers and architectures. © 2022 IEEE.