The importance of the road infrastructure for the society could be compared with importance of blood vessels for humans. To ensure road surface quality it should be monitored continuously and repaired as necessary. The optimal distribution of resources for road repairs is possible providing the availability of comprehensive and objective real time data about the state of the roads. Participatory sensing is a promising approach for such data collection. The paper is describing a mobile sensing system for road irregularity detection using Android OS based smart-phones. Selected data processing algorithms are discussed and their evaluation presented with true positive rate as high as 90% using real world data. The optimal parameters for the algorithms are determined as well as recommendations for their application.

In this systematic umbrella review we aggregate the current knowledge of how virtual and augmented reality technologies are applicable to and impact remote learning in higher education; specifically, how they impact such learning outcomes as performance and engagement in all stages of higher education from course preparation to student evaluation and grading. This review was done as part of a state wide research effort of Latvia, to mitigate the impact of COVID-19 and specifically to provide a framework for a technological transformation of education in this context. In this work we search the Scopus and Web of Science databases for articles describing the use of virtual and/or augmented reality technologies in remote learning for higher education and their impact on learning outcomes. We identified 68 articles from which, after multiple screening and eligibility phases, nine review articles were left for extraction phase in which 30 structural elements with corresponding interventions and measured effects were extracted. Of these, 24 interventions had a measured effect on student performance (11 positive, seven negative, six no impact) and six interventions had a measured effect on student engagement (all six positive).

The advantages of vehicular sensor networks over common wireless sensor networks include the possibility to cover wide measurement area using relatively small number of sensor nodes as well as not so strong limitations according device dimensions, weight and power consumption. These attractive features are reason for expansion of vehicular sensor networks for various environmental monitoring tasks - from defects of road surface to air quality in urban areas. The contribution of this paper is a customized embedded device dedicated for monitoring of road surface using microphone and accelerometer sensors as well as collection of meteorogical data for creation of detailed road meteorology maps. Selected hardware and software aspects are discussed and the implementation of previously developed method for road surface monitoring using accelerometer data is presented.

Technologies, such as Wireless Sensor Networks (WSN) and Internet of Things (IoT), have captured the imagination of researchers, businesses, and general public, due to breakthroughs in embedded system development, sensing technologies, and ubiquitous connectivity in recent years. That resulted in the emergence of an enormous, difficult-to-navigate body of work related to WSN and IoT. In an ongoing research effort to highlight trends and developments in these technologies and to see whether they are actually deployed rather than subjects of theoretical research with presumed potential use cases, we gathered and codified a dataset of scientific publications from a five-year period from 2013 to 2017 involving actual sensor network deployments, which will serve as a basis for future in-depth analysis of the field. In the first iteration, 15,010 potentially relevant articles were identified in SCOPUS and Web of Science databases; after two iterations, 3059 actual sensor network deployments were extracted from those articles and classified in a consistent way according to different categories, such as type of nodes, field of application, communication types, etc. We publish the resulting dataset with the intent that its further analysis may identify prospective research fields and future trends in WSN and IoT.

Safety is an important aspect of transportation systems for both, the drivers and pedestrians. Significant part of road accidents are related to driver inability to react in time on sudden hazardous situations, such as pedestrians or wild animals on the road, a car stopped in case of emergency, or a slippery pavement segment. In this paper we propose an embedded system for driver visual notification in case of a hazard. The system can be unobtrusively added to existing road infrastructure, it is solar-powered and can function autonomously without human intervention. The evaluation shows, that proposed solution is able to detect several types of hazardous situations and report them to drivers.