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Over the last decade, wearable technology has seen significant developments, making it possible to enhance our lives. One of the areas in which wearable technology can cause large changes is education, where it can be used to make educational experiences intrinsicallymotivating and more relevant to youth culture. In this paper, we focus on the use of wearable technology to improve the educational environment. The quantity of electronic assets used in the learning environment is rising, which presents a managerial problem when these devices are nonfunctioning. Therefore, we present a mobile application to solve this problem. The suggested approach consists of creating a mobile application named classroom clinic (CRC) to help faculty members and students locate the closest maintenance technician via wearable radio frequency identification (RFID) technology and to provide fast responses to the problems alerted to in the classroom, thereby avoiding any disturbances or delays during the lecture. Moreover, this application allows the maintenance service to efficiently manage any malfunctions of classroom electronic devices. To evaluate the CRC application, a pilot study was conducted at the College of Computer and Information Sciences, female campus of King Saud University, with 15 faculty members and students and 5 clinic members. The results showed high usability rates and generally positive attitudes towards using the app. [ABSTRACT FROM AUTHOR]

In this article, to monitor the fields with square and circular geometries, three energy-efficient routing protocols are proposed for underwater wireless sensor networks. First one is sparsity-aware energy-efficient clustering, second one is circular sparsity-aware energy-efficient clustering, and the third one is circular depth–based sparsity-aware energy-efficient clustering routing protocol. All three protocols are proposed to minimize the energy consumption of sparse regions, whereas sparsity search algorithm is proposed to find sparse regions and density search algorithm is used to find dense regions of the network field. Moreover, clustering is performed in dense regions to minimize redundant transmissions of a data packet, while sink mobility is exploited to collect data from sensor nodes with an objective of minimum energy consumption. A depth threshold ( d th ) value is also used to minimize number of hops between source and destination for less energy consumption. Simulation results show that our schemes perform better than their counter-part schemes (depth-based routing and energy-efficient depth-based routing) in terms of energy efficiency. [ABSTRACT FROM AUTHOR]