Mohammed Ali Yaseen; A. K. Abass
Volume 20, Issue 2 , April 2020, , Page 74-78
Abstract
In this paper, a fiber Bragg grating (FBG) strain sensor is simulated utilizing OptiGrating software. Then the proposed sensor is integrated into the wavelength division multiplexing (WDM) communication system via OptiSystem software in order to evaluate its performance as a strain sensor. The proposed ...
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In this paper, a fiber Bragg grating (FBG) strain sensor is simulated utilizing OptiGrating software. Then the proposed sensor is integrated into the wavelength division multiplexing (WDM) communication system via OptiSystem software in order to evaluate its performance as a strain sensor. The proposed WDM system has 4–channels with NRZ modulation format and 100 GHz frequency spacing. According to the results, the degradation in the receiving signal reaching the limitation value (6 for Q–factor and 10E–9 for BER) at applied strain ranging from 170 μ –to– 180 μ.
Hasan M. Qays; Bassim A. Jumaa; Ayman D. Salman
Volume 20, Issue 1 , January 2020, , Page 1-15
Abstract
In recent years Quadcopter has been used in many applications such as military, security & surveillance, service delivery, disaster rescue and much more due to its flexibility of flying. In this paper, Quadcopter will be used for mail delivery between many locations that is received from the end ...
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In recent years Quadcopter has been used in many applications such as military, security & surveillance, service delivery, disaster rescue and much more due to its flexibility of flying. In this paper, Quadcopter will be used for mail delivery between many locations that is received from the end user. The Quadcopter will execute an autonomous flight using the concept of companion PC. Raspberry PI 3 (RPI3) will control the Quadcopter by command the controller of the drone (Pixhawk) by using DroneKit-Python API to send MAVLink messages to the Ardupilot. This concept is useful to perform an additional task to the autopilot and provide such a smart capability like image processing and path planning which cannot be done by the flight controller alone. Basically, the idea has been stimulated and the code has been tested by using the SITL Simulator with MAVProxy under Ubuntu environment. The result of controlling the Quadcopter using Python script was excellent and give a motivation to implement the same script on a real Quadcopter. The implementation on real Quadcopter was perfect as it has given the same behavior as the SITL drone in the simulation.
Alaa Al-Obaidi; Satea H. Alnajjar; Mohamed Nsai; Hassan Sharabaty
Volume 20, Issue 2 , April 2020, , Page 14-22
Abstract
Electrocardiogram (ECG) examination via computer techniques that involve feature extraction, pre-processing and post-processing was implemented due to its significant advantages. Extracting ECG signal standard features that requires high processing operation level was the main focusing point for many ...
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Electrocardiogram (ECG) examination via computer techniques that involve feature extraction, pre-processing and post-processing was implemented due to its significant advantages. Extracting ECG signal standard features that requires high processing operation level was the main focusing point for many studies. In this paper, up to 6 different ECG signal classes are accurately predicted in the absence of ECG feature extraction. The corner stone of the proposed technique in this paper is the Linear predictive coding (LPC) technique that regress and normalize the signal during the pre-processing phase. Prior to the feature extraction using Wavelet energy (WE), a direct Wavelet transform (DWT) is implemented that converted ECG signal to frequency domain. In addition, the dataset was divided into two parts , one for training and the other for testing purposes Which have been classified in this proposed algorithm using support vector machine (SVM). Moreover, using MIT AI2 Companion was developed by MIT Center for Mobile Learning, the classification result was shared to the patient mobile phone that can call the ambulance and send the location in case of serious emergency. Finally, the confusion matrix values are used to measure the proposed classification performance. For 6 different ECG classes, an accuracy ration of about 98.15% was recorded. This ratio became 100% for 3 ECG signal classes and decreases to 97.95% by increasing ECG signal to 7 classes.
Hawraa R. Abdul Ameer; Hamid M. Hasan
Volume 20, Issue 1 , January 2020, , Page 53-67
Abstract
The MQTT protocol is one of the Internet of Things (loT) application protocols. It is based on publishing/subscribing messaging patterns. This protocol uses a broker to manage the communication between the subscribers and the publishers over the internet. There were two problems associated with the implementation ...
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The MQTT protocol is one of the Internet of Things (loT) application protocols. It is based on publishing/subscribing messaging patterns. This protocol uses a broker to manage the communication between the subscribers and the publishers over the internet. There were two problems associated with the implementation of this protocol. The first one, there are many sensors generating huge data using the very simple IoT architecture. These big data may lead to congestion on the internet and thus will cause several disadvantages such as decreasing throughput, packet loss, and delay, which in turn may affect the performance of the MQTT broker, thus affecting the mechanism of the performance of the IoT application. The second problem, the MQTT protocol does not contain a priority management algorithm which is considered a very important and special issue in health applications. In this paper, a smart gateway is designed to enhance the MQTT networks. This work introduced the smart e-health gateway used in MQTT based remote Electrocardiogram (ECG) monitoring system. A new architecture has been implemented that contains two new components, the local broker and the publisher /subscriber (pub/sub) models. The local broker works in the local network and the publisher /subscriber (pub/sub) model is responsible for the process of smart in the gateway. One of the smart applications was used is a filter application. We’ve taken the data filtering side and give it a priority, as an example in order to know the possibility of achieving the architecture of the gateway that was created in our work. And is this architecture valid to work or invalid. Therefore, we conducted a test using the application of ECG signal filtration and give priority to patients according to the case of an urgent for each patient. The R-peaks were calculated from the ECG signals-peaks for the identification of heart rate. The urgent level will be classified depending on the beats rate feature. The proposed smart gateway function is to manage the data rate that will pass through to the internet. In the case of high urgent level, all the packets will be passed, while in case of a low level, the least possible data will be passed. The proposed system scenarios are designed and evaluated by using the OMNET simulation environment and Inet4 framework. The simulation results are shown by the evaluation methods used (delay, throughput, packets sent, and packets received). These results proved the success of the architectural work that was implemented in the system.
Ahmed H. Hadi; Waleed F. Shareef
Volume 20, Issue 2 , April 2020, , Page 33-46
Abstract
Due to the recent advancements in the fields of Micro Electromechanical Sensors (MEMS), communication, and operating systems, wireless remote monitoring methods became easy to build and low cost option compared to the conventional methods such as wired cameras and vehicle patrols. Pipeline Monitoring ...
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Due to the recent advancements in the fields of Micro Electromechanical Sensors (MEMS), communication, and operating systems, wireless remote monitoring methods became easy to build and low cost option compared to the conventional methods such as wired cameras and vehicle patrols. Pipeline Monitoring Systems (PMS) benefit the most of such wireless remote monitoring since each pipeline would span for long distances up to hundreds of kilometers. However, precise monitoring requires moving large amounts of data between sensor nodes and base station for processing which require high bandwidth communication protocol. To overcome this problem, In-Situ processing can be practiced by processing the collected data locally at each node instead of the base station. This Paper presents the design and implementation of In-situ pipeline monitoring system for locating damaging activities based on wireless sensor network. The system built upon a WSN of several nodes. Each node contains high computational 1.2GHz Quad-Core ARM Cortex-A53 (64Bit) processor for In-Situ data processing and equipped in 3-axis accelerometer. The proposed system was tested on pipelines in Al-Mussaib gas turbine power plant. During test knocking events are applied at several distances relative to the nodes locations. Data collected at each node are filtered and processed locally in real time in each two adjacent nodes. The results of the estimation is then sent to the supervisor at base-station for display. The results show the proposed system ability to estimate the location of knocking event.
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