Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
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A Study for Remote Monitoring of Water Points in Mauritania Based on IoT (LoRa) Technology
Get PDFWetlands in Mauritania contain the most important water sources necessary for the survival of rural communities in the country. In these areas, the main rural activities such as animal husbandry, agriculture, and fishing take place. Lack of water or flooding must be monitored to plan solutions in advance. After a comparative study of IoT wireless technologies, we proposed that LoRa technology is the most suitable for our field of application. However, in certain areas where access to the cellular network is difficult, we propose the addition of satellite communication in the LoRamonitoring system to achieve information collected at any point in the world via the cloud and the Internet. We carried out a practical case for the areas covered by the UMTS (3G) cellular network using devices integrating LoRaWAN to evaluate the performance of this technology. The results show the success of the communication over a distance of 14 km
Bone fracture detection through X-ray using Edge detection Algorithms
Get PDFHuman beings are highly prone to bone fractures, to a great extent as an outcome of accidents or other factors such as bone cancer. Manual fracture detection takes a lengthy time and comes with a considerable chance of error. As a result, establishing a computer-based method to reduce fracture bone diagnosis time and risk of error is critical. The most common method for segmenting images based on sharp changes in intensity is edge detection. Sobel, Robert, Canny, Prewitt, and LoG (Laplacian of Gaussian) are some of the edge detection approaches that are examined for the study of bone fracture detection. The focal point of this paper is an endeavor to study, analyze and compare the Sobel, Canny, and Prewitt Techniques for detecting edges and identifying the fracture
Detection of Bundle Branch Blocks using Machine Learning Techniques
Get PDFThe most effective method used for the diagnosis of heart diseases is the Electrocardiogram (ECG). The shape of the ECG signal and the time interval between its various components gives useful details about any underlying heart disease. Any dysfunction of the heart is called as cardiac arrhythmia. The electrical impulses of the heart are blocked due to the cardiac arrhythmia called Bundle Branch Block (BBB) which can be observed as an irregular ECG wave. The BBB beats can indicate serious heart disease. The precise and quick detection of cardiac arrhythmias from the ECG signal can save lives and can also reduce the diagnostics cost. This study presents a machine learning technique for the automatic detection of BBB. In this method both morphological and statistical features were calculated from the ECG signals available in the standard MIT BIH database to classify them as normal, Left Bundle Branch Block (LBBB) and Right Bundle Branch Block (RBBB). ECG records in the MIT- BIH arrhythmia database containing Normal sinus rhythm, RBBB, and LBBB were used in the study. The suitability of the features extracted was evaluated using three classifiers, support vector machine, k-nearest neighbours and linear discriminant analysis. The accuracy of the technique is highly promising for all the three classifiers with k-nearest neighbours giving the highest accuracy of 98.2%. Since the ECG waveforms of patients with the same cardiac disorder is similar in shape, the proposed method is subject independent. The proposed technique is thus a reliable and simple method involving less computational complexity for the automatic detection of bundle branch block. This system can reduce the effort of cardiologists thereby enabling them to concentrate more on treatment of the patients
Closed-Loop Tuning of Cascade Controller for Load Frequency Control of Multi-Area Distributed Generation Resources Optimized by ASOS Algorithm
Get PDFThis paper provides closed loop tuning of cascaded-tilted integral derivative controller (CC-TID) for load frequency control (LFC) of micro grid system. A micro grid system is the arrangement of distributed generation resources such as wind turbine generator (WTG), fuel cell (FC), aqua electrolyser (AE), diesel engine generator (DEG) and battery energy storage system (BESS). Different controllers such as proportional integral derivative (PID), two degree of freedom (2DOFPID), three degree of freedom (3DOFPID) and tilted integral derivative (TID) are used not only to sustain the disparity between real power generation and load demand but also accomplish zero steady state error to enrich the frequency and tie power regulations. The anticipated controller encompasses both the value of cascade (CC) and fractional order (FO) controls for better elimination of system instabilities. In the proposed CC-3DOFPID-TID controller, TID controller is castoff as a slave controller and 3DOFPID controller aided the role of dominant controller. The controlled parameters are optimized by adaptive symbiotic organism search (ASOS) algorithm for keen results of difficulties in LFC. To persist in ecosystem, symbiotic relations are predictable by organism through imitators. Further the dynamic behaviours of controller optimized by ASOS, teaching learning based optimization (TLBO) and differential evolution particle swarm optimization (DEPSO) are compared by extensive simulations in MATLAB/SIMULINK. Moreover the supremacy of proposed controller is performed through system dynamics comparison among PID, 2DOFPID, 3DOF-PID and CC-3DOFPID-TID controllers. Finally sensitivity of proposed controller has proven though random load perturbation
Multimodal Based Audio-Visual Speech Recognition for Hard-of-Hearing: State of the Art Techniques and Challenges
Get PDFMultimodal Integration (MI) is the study of merging the knowledge acquired by the nervous system using sensory modalities such as speech, vision, touch, and gesture. The applications of MI expand over the areas of Audio-Visual Speech Recognition (AVSR), Sign Language Recognition (SLR), Emotion Recognition (ER), Bio Metrics Applications (BMA), Affect Recognition (AR), Multimedia Retrieval (MR), etc. The fusion of modalities such as hand gestures- facial, lip- hand position, etc., are mainly used sensory modalities for the development of hearing-impaired multimodal systems. This paper encapsulates an overview of multimodal systems available within literature towards hearing impaired studies. This paper also discusses some of the studies related to hearing-impaired acoustic analysis. It is observed that very less algorithms have been developed for hearing impaired AVSR as compared to normal hearing. Thus, the study of audio-visual based speech recognition systems for the hearing impaired is highly demanded for the people who are trying to communicate with natively speaking languages. This paper also highlights the state-of-the-art techniques in AVSR and the challenges faced by the researchers for the development of AVSR systems
Characteristic Control of SWCNT-FET by Varying Its Chirality and Dimensions
Get PDFCarbon nanotube (CNT) has witnessed great importance due to its electronic and mechanical properties. The CNTFET was designed to provide high-performance electronic devices. Therefore, the carbon nanotube is representing a potential material for future microelectronic devices. In this paper, COMSOL Multiphysics was used to design and a simulate single-walled carbon nanotube field-effect transistor with a back gate. The insulation layer used in the model was silicon dioxide. The influence of changing its thickness on the drain current was discussed. In addition, the specification of carbon nanotubes was investigated in terms of changing their diameter and length. Moreover, this paper reveals the current transport of CNTFET for different applied gate voltage and drain voltage. In our work, the CNTFET behaves as n-type FET with transconductance gm≈1.25uA and electron mobility equal to 4.77×10-26cm2v-1s-1. To obtain semiconducting properties for the CNT material, it must consider the chirality when altering the carbon nanotubes diameter. In the proposed device, the diameter values range from 1nm to 4.5nm. It was found that increasing the diameter range resulted in decreasing bandgap from 0.497 eV to 0.110 eV and increasing drain current from 4.075 uA to 31.33 uA
Object Tracking in Augmented Reality: Enhancement Using Convolutional Neural Networks
No full textAugmented reality (AR) has been used in maintenance, simulation, and remote assistance, among other applications. In AR systems, one of the significant issues is the placement of objects in augmented physical environments. Given the importance of object placement in AR systems, we proposed deep learning-based object placement, covering both object detection and object segmentation, to address relevant issues. Deep learning can help users complete tasks by providing the right information effectively, with the method taking into account dynamically changing environments and users’ situations in real time. The problem is that it is rarely used in AR, thereby prompting the combination of deep learning-based object detection and instance segmentation with wearable AR technology to improve the performance of complex tasks. This challenge was addressed in this work through the use of convolutional neural networks in the detection and segmentation of objects in actual environments. We measured the performance of AR technology on the basis of detection accuracy under environmental conditions of different intensities. Experimental results showed satisfactory segmentation and accurate detectio
Cryptanalysis the SHA-256 Hash Function using Rainbow Tables
Get PDFThe research of the strength of a hashed message is of great importance in modern authentication systems. The hashing process is inextricably linked with the password system, since passwords are usually stored in the system not in clear text, but as hashes. The SHA-256 hash function was chosen to model the attack with rainbow tables. An algorithm for constructing a rainbow table for the SHA-256 hash function in the Java language is proposed. The conditions under which the use of rainbow tables will be effective are determined. This article aims to practically show the process of generating a password and rainbow tables to organize an attack on the SHA-256 hash function. As research shows, rainbow tables can reveal a three-character password in 3 seconds. As the password bit increases, the decryption time increases in direct proportion
An S-Band Microstrip Patch Antenna Design and Simulation for Wireless Communication Systems
Get PDFIn this paper, a 3.5 GHz microstrip patch antenna for the future of wireless communication is designed and studied. As a substrate, Rogers RT/Duroid5880 is utilized. This material has a thickness of 0.077mm and a dielectric loss of 2.2. The proposed antenna layout is simulated using the CST studio suite of software programs. This research aimed to achieve a lower return loss, higher gain, lower VSWR, directivity, and improved efficiency. The simulation revealed that the return loss, gain, VSWR, and directivity were correspondingly -13.772 dB, 7.55 dB, 1.5152, and 8.43dBi. The efficiency was 89.56%. This antenna has been developed and assessed for use in various wireless communication applications with a 3.5 GHz operating frequency, which is used as a reference antenna in communication satellites, weather radar, surface ship radar, wireless LAN-802.11b and 802.11g, multimedia applications in mobile TV and satellite radio, optical communications at 1460 to 1530 nm wavelength, and is utilized for other wireless fidelity applications
The Impact of Telemetry Received Signal Strength of IMU/GNSS Data Transmission on Autonomous Vehicle Navigation
Get PDFThis paper presents the effect of received signal strength on IMU/GNSS sensor data transmission for autonomous vehicle navigation. A pixhawk 2.1 flight controller is used to build the navigation system. Straight lines with back-and-forth routes were tested using two types of SiK telemetry: Holybro and RFD. The results of the tests show that when the RSSI value falls close to the receiver's sensitivity value, the readings of the gyro sensor data, accelerometer, magnetometer, and GNSS compass data are disturbed. When the RSSI signal collides with noise, the radio telemetry link is lost, affecting the accuracy of speed data and the orientation of autonomous vehicles. According to Cisco's conversion table, the highest RSSI on Holybro telemetry is -48 dBm, and the lowest is -103 dBm, with a receiver sensitivity of -117 and data reading at a distance of about 427 meters. While the highest RSSI value on RFD telemetry is -17 dBm and the lowest is -113 dBm, even the lowest value is above the receiver's sensitivity limit of -121 dBm with data readings at a distance of approximately 749.4 meters. RFD outperforms Holybro in terms of RSSI and sensitivity at low data rates. When reading distance data to reference distance data using Google Earth and ArcGIS, RFD telemetry has a higher accuracy, with an average accuracy of 98.8%