Unmanned aerial vehicles (UAVs) play a primary role in a plethora of technical and scientific fields owing to their wide range of applications. In particular, the provision of emergency services during the occurrence of a crisis event is a vital application domain where such aerial robots can contribute, sending out valuable assistance to both distressed humans and rescue teams. Bearing in mind that time constraints constitute a crucial parameter in search and rescue (SAR) missions, the punctual and precise detection of humans in peril is of paramount importance. The paper in hand deals with real-time human detection onboard a fully autonomous rescue UAV. Using deep learning techniques, the implemented embedded system was capable of detecting open water swimmers. This allowed the UAV to provide assistance accurately in a fully unsupervised manner, thus enhancing first responder operational capabilities. The novelty of the proposed system is the combination of global navigation satellite system (GNSS) techniques and computer vision algorithms for both precise human detection and rescue apparatus release. Details about hardware configuration as well as the system’s performance evaluation are fully discussed.
A three-phase synchronous machine was, and still is, one of the most important element in today’s power generation systems (operating as a generator) or in distribution–load systems (operating as a motor). Thus, a suitable and detailed model is required to be used by students and future engineers in order to deal with transient stability analyses. For this purpose, the paper presents and analyses a procedure by which the mathematical modelling of a three-phase, four-pole, synchronous machine can be implemented in the LabVIEW environment. A suitable graphics user interface is proposed and case studies under different machine operating conditions are shown. The corresponding results illustrate the validity and accuracy of the model. Furthermore, a reactive power PI controller is also implemented. The overall graphics user interface/simulation model is applied to an undergraduate course as a teaching tool and assessed thoroughly. It is shown that the proposed tool may be utilized in under/post-graduate studies as well as in power utilities practician engineers courses.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.