Implementation of participatory sensing approach in mobile vehicle based sensor networks

In this paper author describes his research with the goal to develop and experimentally verify specific data recording and processing methodologies based on participatory sensing approach implementation in mobile vehicle based sensor networks. To reach this goal, author performed study of literature, testing of hypothesis using general purpose computer devices, adaptation of smartphones for participatory sensing, development of special purpose embedded devices, practical experiments with selected technical equipment and software as well as gathering of experimental results and following statistical analysis. The result of this research are several data acquisition and processing methodologies based on participatory sensing approach and mobile vehicle based sensor networks as well as evaluation of these methodologies

Creation of three-dimensional object models using laser

Šajā darbā aprakstīts autora veikts pētījums par eksistējošām metodēm, kuras tiek izmantotas, lai iegūtu datus objektu trīsdimensiju modeļu izveidei. Kā darba mērķis tika izvirzīts uzdevums atrast vienu optimālu metodi vai vairāku atsevišķu metožu kombināciju, kuru būtu iespējams pielietot praktiska aparatūras/programmatūras modeļa būvē, izmantojot plaši pieejamas komponentes. Mērķa sasniegšanai izmantotas literatūras studijas, kā arī praktiski eksperimenti ar tehnoloģiskajām iekārtām un programmatūru. Darba rezultāts ir oriģinālas objektu trīsdimensiju skenēšanas sistēmas projekts un uz šī projekta bāzes veikta sistēmas praktiskā implementācija.In this paper author describes his research about existing methods used to gather data for the creation of three-dimensional object models. The goal of this research was to find one optimal method or the combination of several different methods, best suited for development of a real hardware/software model using general-purpose components. To reach this goal, author performed study of literature as well as some practical experiments with technical equipment and software. The result of this research is a project of original three-dimensional object scanning system, upon which practical implementation of the system were realised

Recording and processing of vehicles motion parameters using distributed systems

Šajā darbā aprakstīti autora veikti pētījumi ar mērķi izstrādāt un eksperimentāli pārbaudīt atsevišķas datu ieguves un apstrādes metodikas, kas balstītas uz kolektīvo mērījumu pieejas implementāciju mobilos, uz transporta līdzekļiem bāzētos sensoru tīklos. Mērķa sasniegšanai izmantotas literatūras avotu studijas, hipotēžu pārbaude, izmantojot plaša pielietojuma datortehniku, viedtālruņu adaptācija specifisku kolektīvo mērījumu vajadzībām, speciāla pielietojuma iegultu iekārtu izstrāde, praktiski eksperimenti ar izvēlētajām tehnoloģiskajām iekārtām un programmatūru, kā arī eksperimentu rezultātu apkopošana un statistiskā analīze. Darba rezultāts ir vairākas datu ieguves un apstrādes metodikas, kas balstītas uz kolektīvo mērījumu pieeju un mobiliem, uz transporta līdzekļiem bāzētiem sensoru tīkliem un izstrādāto metodiku novērtējums. ATSLĒGVĀRDI: Kolektīvie mērījumi, mobili sensoru tīkli, metodikas, mikrofoni, akselerometri, pozīcijas noteikšana.In this paper author describes his research with the goal to develop and experimentally verify specific data recording and processing methodologies based on participatory sensing approach implementation in mobile vehicle based sensor networks. To reach this goal, author performed study of literature, testing of hypothesis using general purpose computer devices, adaptation of smartphones for participatory sensing, development of special purpose embedded devices, practical experiments with selected technical equipment and software as well as gathering of experimental results and following statistical analysis. The result of this research are several data acquisition and processing methodologies based on participatory sensing approach and mobile vehicle based sensor networks as well as evaluation of these methodologies. KEYWORDS: Participatory sensing, mobile sensor networks, methodologies, microphones, accelerometers, position determination

Use of Augmented and Virtual Reality in Remote Higher Education: A Systematic Umbrella Review

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 Definitive Guide to Actual Sensor Network Deployments in Research Studies from 2013–2017: A Systematic Review

The research community has been working on sensor networks for more that seven decades and altogether more than a million research articles on sensor networks have been published, with this number growing every day. In this article, we try to provide a thorough and complete systematic review on the sensor network field resulting from representative subset of more than 3000 articles which include actual sensor network deployments. After a thorough analysis of these data, we provide a definitive overview of the trends in sensor network deployment described in published research articles

The Definitive Guide to Actual Sensor Network Deployments in Research Studies from 2013–2017: A Systematic Review

The research community has been working on sensor networks for more that seven decades and altogether more than a million research articles on sensor networks have been published, with this number growing every day. In this article, we try to provide a thorough and complete systematic review on the sensor network field resulting from representative subset of more than 3000 articles which include actual sensor network deployments. After a thorough analysis of these data, we provide a definitive overview of the trends in sensor network deployment described in published research articles

Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017

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