The issue of energy balancing in Wireless Sensor Networks is a pivotal one, crucial in their deployment. This problem can be subdivided in three areas: (i) energy conservation techniques, usually implying minimizing the cost of communication at the nodes since it is known that the radio is the biggest consumer of the available energy; (ii) energy-harvesting techniques, converting energy from not full-time available environmental sources and usually storing it; and (iii) energy transfer techniques, sharing energy resources from one node (either specialized or not) to another one. In this article, we survey the main contributions in these three areas and identify the main trending topics in recent research. A discussion and some future directions are also included.

In this study, as the last step of a longitudinal study of the impact of social learning and gamification methodologies on learning results in higher education, we have recorded the activity in a software platform based on Moodle, specially built for encouraging online participation of the students to design, carry out and evaluate a set of learning tasks and games, during two consecutive editions of an undergraduate course. Our aim is to confirm the relationships between the patterns of accomplishment of the gamified activities and the network structure of the social graphs associated with the online forums with knowledge acquisition and final outcomes. For this purpose, we have offered two learning paths, traditional and novel, to our students. We have identified course variables that quantitatively explain the improvements reported when using the innovative methodologies integrated into the course design, and we have applied techniques from the social network analysis (SNA) and the machine learning/deep learning (ML/DL) domains to conduct success/failure classification methods finding that, generally, very good results are obtained when an ensemble approach is used, that is, when we blend the predictions made by different classifiers. The proposed methodology can be used over reduced datasets and variable time windows for having early estimates that allow pedagogical interventions. Finally, we have applied other statistical tests to our datasets, that confirm the influence of the learning path on learning results.

Badges are non fungible tokens used to document or certify achievements in academics or in any other domain. Besides their utility as proof of achievement, badges are of interest in higher education as pure incentives to push the students and learners in general toward pursuing well-defined goals and skills. In this respect, badges can be naturally incorporated into digital learning platforms also as part of informal learning activities, and stimulate participation, merit, and visibility for the students. However, the level of engagement of learners into these learning activities depends crucially on how the system of badges and rewards has been designed and on how it is applied, if it is to be used effectively. In this paper, we report on the design and implementation of a smart badges system, and an example of its use inside a gamification methodology for informal learning in a master level course, and discuss the benefits and the observed gains in learning performance that can be obtained.