Bulletin of Electrical Engineering and Informatics
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Performance improvement of fuel cell and photovoltaic system
Get PDFThis article considers and studies a hybrid energy storage system as a potential replacement for a utility grid. It also examines its organisational structure. The hybrid energy storage technology is used to ensure a constant supply of convenient grid electricity that is sufficient to handle changing power spikes. Batteries are used to stabilise the surges with measurable variation, whereas a massive capacitor is utilised to stabilise the surges with fast variation. In isolated areas where connecting to the main utility grid is impractical, standalone renewable generation may provide the advantage of a reduced operational cost as well as a reduction in protection fees. In order to encourage non-conventional power production in the overall renewable energy system, advancements in solid oxide fuel-cell technology and solar photovoltaic (PV) technology have also been made. Grid-coupled solar PV energy producing systems are being extensively used worldwide, and solar PV modules are increasingly being used in residential applications linked to the electrical grid
Real-time monitoring tool for heart rate and oxygen saturation in young adults
Get PDFHealth monitoring is crucial to maintain optimal well-being, especially for young adults. Wearable sensors have become popular for collecting healthcare data, but there are concerns regarding their reliability and safety, particularly with wireless sensors that use radio-frequency (RF) based devices. Researchers have proposed real-time monitoring systems for measuring heart rate beats per minute (BPM) and blood oxygen saturation (SpO2) saturation levels, but more studies are needed to determine the accuracy and user acceptance of these tools among young adults. To address these concerns, this study proposes a real-time monitoring tool that incorporates MAX 30100 sensors to collect heart rate BPM and SpO2 data. The collected data is then connected to a visualization platform, i.e., InfluxDB and Grafana, to provide valuable insights of the body’s physiological state. By testing the feasibility and usability of the tool, we found motivating differences in resting heart rates and changes in heart rate after activity between male and female participants. By developing this real-time monitoring tool and investigating gender-specific differences in heart rate and activity-induced changes, our study contributes to the advancement of health monitoring technologies for young adults, ultimately promoting personalized healthcare and well-being
Harmonics mitigation technique for asymmetrical multilevel inverter fed by photovoltaic sources
Get PDFA multilevel inverter is an electrical device that converts a DC voltage into a higher AC voltage by generating a stepped waveform with several voltage levels. Unlike traditional inverters that produce a square wave or a pulse-width modulated (PWM) waveform with only two voltage levels, multilevel inverters can generate waveforms with three or more levels, resulting in reduced harmonic distortion, improved efficiency, and decreased electromagnetic interference. The design and control of multilevel inverters are active research areas that aim to enhance their performance, reliability, and scalability. In this research, a 31-level asymmetric cascaded multilevel inverter is suggested. The proposed multilevel inverter (MLI) system employs four photovoltaic cells as dc sources with structure of (1:2:4:8) Vdc. The system is modeled by MATLAB/Simulink and total harmonic distortion (THD) values of the output voltage and current are 1.106% for resistive load, and 1.35% and 0.403% for inductive load. These outcomes demonstrate the recommended circuit's efficacy and demonstrate its suitability for medium- and high-power applications
Skill optimization algorithm for solving optimal power flow problem
Get PDFThis research presents the implementation of a modern meta-heuristic algorithm called the skill optimization algorithm (SOA) to solve the optimal power flow problem (OPF). An IEEE 30-bus transmission system is selected to test the real performance of SOA. The main objective function of the study is to minimize the total fuel cost (TFC) of all thermal units. To clarify the high performance of SOA, a classical meta-heuristic named particle swarm optimization (PSO) is also applied for comparison. All results reached by SOA are compared with those of PSO on different criteria. Particularly, SOA has reached smaller cost than PSO by $1.04, equivalent to 0.13% of PSO’s TFC. Furthermore, SOA has reached a more stable performance by finding better average and maximum TFC over fifty runs. The evaluation of these criteria indicates that SOA completely outperforms PSO. Besides, the optimal solution reached by SOA satisfies all considered constraints with zero violation of the dependent variables. Therefore, SOA is highly suggested to handle the OPF problem
High capacity double precision image steganography based on chaotic maps
Get PDFSteganography is the process of hiding confidential information within non-secret multimedia such that the 3rd party cannot distinguish if there is a secret message in it or not. Whereas cryptography is the technique of using mathematical concepts to convert information into unreadable codes via a key. This paper will propose two approaches, lossless and lossy image steganography. Both of them will use cryptography and steganography based on three different chaotic maps to ensure information security. In the cryptography part, two chaotic maps will be used to encrypt the secret information, while in the steganography section, one chaotic map is used to embed the message. The secret information will be concealed in the least significant bits (LSBs) of the double-precision image’s pixels. The double precision image is a high-quality image and can be represented in 64 bits per pixel for grayscale images, leading to a very high redundant bit. Simulation results show a high embedding capacity of 60.938% and 400% for lossless and lossy approaches respectively with a peak signal to noise ratio (PSNR) reach of 69.964 dB. Furthermore, this system is extremely secure due to the use of 3 chaotic maps with key space 2448
Securing laboratories through internet of things networks: a comprehensive approach for ensuring safety and efficiency
Get PDFThe design of a secure, intelligent laboratory that incorporates internet of things (IoT) devices and applications is a complex process. One of the main goals is to create a process monitoring system that can collect and analyze data from connected devices such as temperature and pressure sensors, smart locks, and access control systems. This system must operate in real time to ensure that equipment is within reference values. This reduces the risk of contamination and increases reliability. In addition, computer network security is paramount and it is imperative that certain measures such as encryption, multi-factor authentication, and intrusion detection systems are implemented. These measures help to ensure the safety and security of critical information and protect against potential risks. Physical security is also essential to protect scientific equipment and data. This paper provides a comprehensive overview of the critical factors involved in designing a secure, intelligent laboratory. It discusses the benefits of the integration of IoT devices and applications, and the security challenges that must be addressed. The paper also provides recommendations for designing and implementing a secure smart lab
Implementing and developing multi-stage cryptography technique for low-cost long-range communication system
Get PDFThe requirement for a secure emergency communication system has become imperative in tandem with the industrial revolution. Additionally, the development of technology has led to increasingly robust penetration techniques that pose a threat to communication system security, leaving data vulnerable to unwanted third parties. This paper introduces a novel, powerful security approach that ensures a secure emergency communication system. Moreover, this research focuses on several cryptographic techniques among various symmetric and asymmetric ciphers, including advanced encryption standards, substitution, and transposition. The article presents an affordable and secure communication system that can transmit data over long distances with low power consumption using long-range technology. This system features a unique function that transmits updated locations, directing rescuers to the designated location
Multispectral imaging and deep learning for oil palm fruit bunch ripeness detection
Get PDFOil palm fresh fruit bunches (FFBs) are the raw material of crude palm oil (CPO) on which ripeness levels of FFBs are essential to obtain good quality CPO. Most palm oil mills use experienced graders to evaluate FFB ripeness levels. Researchers have developed rapid and non-destructive methods for ripeness detection using computer vision (CV) and deep learning. However, most of the experiments used color cameras, such as a webcam or a smartphone, limited to visible wavelengths, and used still FFBs on–trees or on the ground. This study developed a light-emitting diode (LED)-based multispectral imaging system with deep learning for rapid and real-time ripeness detection of oil palm FFBs on a moving conveyor. The ripeness levels used were unripe and ripe. We also evaluated the spectrum of reflectance intensities for the ripeness levels. The ripeness detection system employed a two-class you only look once version 4 (YOLOv4) detection model using a dataset of 2000 annotated unripe and ripe FFB multispectral images and a video of 30 moving FFBs for real-time testing. The results show a promising method to detect oil palm FFB ripeness with an average accuracy of 99.66% and a speed range of 3.32-3.62 frame per second (FPS)
Cross-project software defect prediction through multiple learning
Get PDFCross-project defect prediction is a method that predicts defects in one software project by using the historical record of another software project. Due to distribution differences and the weak classifier used to build the prediction model, this method has poor prediction performance. Cross-project defect prediction may perform better if distribution differences are reduced, and an appropriate individual classifier is chosen. However, the prediction performance of individual classifiers may be affected in some way by their weaknesses. As a result, in order to boost the accuracy of cross-project defect prediction predictions, this study proposed a strategy that makes use of multiple classifiers and selects attributes that are similar to one another. The proposed method's efficacy was tested using the Relink and AEEEM datasets in an experiment. The findings of the experiments demonstrated that the proposed method produces superior outcomes. To further validate the method, we employed the Wilcoxon sum rank test at 95% significance level. The approach was found to perform significantly better than the baseline methods
Portable internet of things-based soil nutrients monitoring for precision and efficient smart farming
Get PDFThis paper describes the design and implementation of a portable internet of things (IoT)-based system for online monitoring of soil nutrients, specifically nitrogen (N), phosphorus (P), and potassium (K), to improve precision and efficiency in smart farming. The main goal is to use IoT technology to analyze soil conditions on-site and provide advice about fertilization and soil management. The system measures soil nutrient levels using field-based sensors, such as an NPK probe, and transmits data over a wireless sensor network. The research comprises a quantitative evaluation of the performance of the IoT system using various sensors. An analysis of variance (ANOVA) was used to compare the accuracy of the IoT device with industrial soil nutrient measurement equipment, demonstrating differences in P and K values but not in N values. This disparity points to certain areas where the accuracy of the P and K measurements in the IoT system should be improved. This IoT-based soil nutrient monitoring system highlights the potential of smart farming technology to boost agricultural output, optimize resource consumption, and support sustainable farming practices. The system's portability and online data availability provide farmers with exact soil condition information, allowing them to make more efficient and intelligent farming decisions