New master’s degrees in computer engineering, designed according to Spanish government requirements, include both technical and business subjects to provide advanced knowledge compared to undergraduate studies. In spite of acquiring this advanced knowledge, our students are not always aware of the significant added value and the positive elements the master’s degree provides for their future professional careers. Moreover, we have observed that students regard the different subjects as isolated blocks of knowledge. To tackle these problems, we have carried out a learning experience based on the creation of a technology-based enterprise (TBE) through the development of a common project (CP). Drawing on project-based learning (PBL) methodology, the CP consists of the identification, development, and final oral presentation of a business model. It aims to utilize sensor data and analysis in different domains. The experience has been highly positive, reducing the gap between studies and business practice, and increasing coordination among teachers. A key issue is that all the subjects of the master’s degree are involved in this learning experience. In addition, results show a high level of satisfaction with the master’s degree, compared to other similar courses.

Over the past few years, we have witnessed the widespread deployment of wireless sensor networks and distributed data management facilities: two main building blocks of the Internet of things (IoT) technology. Due to the spectacular increase on the demand for novel information services, the IoT-based infrastructures are more and more characterized by their geographical sparsity and increasing demands giving rise to the need of moving from a cloud to a fog model: a novel deployment paradigm characterized by the provisioning of elastic resources geographically located as close as possible to the end user. Despite the large number of wireless sensor networks already available in the market, there are still many issues to be addressed on the design and deployment of robust network platforms capable of meeting the demand and quality of fog-based systems. In this paper, we undertake the design and development of a wireless sensor node for fog computing platforms addressing two of the main issues towards the development and deployment of robust communication services, namely, energy consumption and network resilience provisioning. Our design is guided by examining the relevant macroarchitecture features and operational constraints to be faced by the network platform. We based our solution on the integration of network hardware platforms already available on the market supplemented by smart power management and network resilience mechanisms.