The pilgrimage takes place in several countries around the world. The pilgrimage includes the simultaneous movement of a huge crowd of pilgrims which leads to many challenges for the pilgrimage authorities to track, monitor, and manage the crowd to minimize the chance of overcrowding’s accidents. Therefore, there is a need for an efficient monitoring and tracking system for pilgrims. This paper proposes powerful pilgrims tracking and monitoring system based on three Internet of Things (IoT) technologies; namely: Radio Frequency Identification (RFID), ZigBee, and Internet Protocol version 6 (IPv6). In addition, it requires low-cost, low-power-consumption implementation. The proposed system can efficiently handle the pilgrimage challenges; namely: the language barrier, identifying of injured or dead pilgrims, directing lost pilgrims, knowing medical records of pilgrims, and the crowd management. Finally, another paramount characteristic of the proposed IoT-based system is allowing the authorities, the heath-givers, and the pilgrim’s family for real-time tracking and monitoring of pilgrim during the pilgrimage anytime, anywhere.
The subgrade soil is the foundation plate form of the roadway; it should sustain its structural characteristics throughout the design life of the roadway with minimal requirements for maintenance. When Gypseous soil is implemented in the construction of subgrade, problems regarding collapsibility and poor structural capacity usually occur when the subgrade came in touch with excess water. Asphalt stabilization could furnish a proper solution to such problems. In this investigation, an attempt has been made to monitor the variations in compressibility characteristics of asphalt stabilized subgrade soil subjected to 30 cycles of (freezing-thawing) and (heating-cooling). Data have been observed after each 10 cycles, and compared with that of r
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One of the most significant environmental issues facing the planet today is air pollution. Due to development in industry and population density, air pollution has lately gotten worse. Like many developing nations, Iraq suffers from air pollution, particularly in its urban areas with heavy industry. Our research was carried out in Baghdad's Al-Nahrawan neighbourhood. Recently, ground surveys and remote sensing were used to study the monitoring of air pollution. In order to extract different gaseous and particle data, Earth Data source, Google Earth Engine (GEE), and Geographic Information Systems (GIS) software were all employed. The findings demonstrated that there is a significant positive connection between data collected by ground-ba
... Show MoreBackground: Chronic cigarette smoking is one of the major risk factors for coronary artery disease. However, it has additional cardiac adverse effects independent of coronary atherosclerosis. Patient and Methods: After informed consent and perm- ission from the review board of the hospital, 80 healthy subjects who were classified as smokers or non-smokers were included in the study. They were examined by standard echocardiography protocol which was followed by two-dimensional speckle tracking to assess the functions of the right ventricle. Results: The tricuspid annular plane systolic excursion (TAPSE) was significantly reduced in smokers as compared to non-smokers (P < 0.05). The tricuspid flow peak late diastolic velocity (A wave) was sig
... Show MoreAn attempt was made to evaluate the PV performance of one-axis daily tracking and fixed system for Baghdad, Iraq. Two experimental simulations were conducted on a PV module for that purpose. Measurements included incident solar radiation, load voltage and load current. The first experiment was carried out for six months of winter half of year to simulate the one-axis daily tracking. The azimuth angle was due south while the tilt angle was being set to optimum according to each day of simulation. The second experiment was done at one day to simulate the PV module of fixed angles. It is found that there is a significant power gain of 29.6% for the tracking system in respect to the fixed one. The one-axis daily tracking was much more effect
... Show MoreThe object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.
Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order PIaDb (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of
... Show MoreA Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
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