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With the growing demand for infrastructure and transportation facilities, the need for advanced structural health monitoring (SHM) systems is critical. This study introduces two innovative, cost-effective, standalone, and open-source data acquisition devices designed to enhance SHM through the latest sensing technologies. The first device, termed CEDAS_acc, integrates the ADXL355 MEMS accelerometer with a RaspberryPi mini-computer, ideal for measuring strong ground motions and assessing structural modal properties during forced vibration tests and structural monitoring of mid-rise buildings.

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Streamline Intelligent Crowd Monitoring with IoT Cloud Computing Middleware.

Sensors (Basel)

June 2024

Department of Electrical and Computer Engineering, School of Engineering, Democritus University of Thrace, 67100 Xanthi, Greece.

This article introduces a novel middleware that utilizes cost-effective, low-power computing devices like Raspberry Pi to analyze data from wireless sensor networks (WSNs). It is designed for indoor settings like historical buildings and museums, tracking visitors and identifying points of interest. It serves as an evacuation aid by monitoring occupancy and gauging the popularity of specific areas, subjects, or art exhibitions.

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Statement Of Problem: Whether the use of an external graphics processing unit (eGPU) and a handheld computer prolongs the operation time for 3-dimensional (3D) intraoral scanning or produces clinically unacceptable scans is unclear.

Purpose: The purpose of this in vitro study was to compare the 3D intraoral scan accuracy and scan time of a small portable device and an eGPU with desktop-grade workstations.

Material And Methods: A handheld computer, a laptop, a desktop workstation, and an external graphics card were used to scan a 3D printed set of maxillary and mandibular casts 10 consecutive times using an intraoral scanner.

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Design and Implementation of a Smart Wireless Controlled Visual Acuity Measurement System.

J Med Signals Sens

August 2023

Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

In this article, a smart visual acuity measurement (VAM) system is designed and implemented. Hardware of the proposed VAM system consists of two parts: a wireless remote controller, and a high-resolution LCD controlled through a Raspberry-Pi mini-computer. In the remote controller, a 3.

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Background: Antibiotics are over-used for patients with respiratory tract infections (RTIs) in primary care, especially in the rural areas of China.

Methods: A cluster randomized controlled trial (RCT) will be carried out to estimate the effectiveness of a tailored message package for educating patients to reduce antibiotic use for symptomatic respiratory tract infections (RTIs). In the intervention group, patients will receive 12 short messages in 12 consecutive days.

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