This paper presents a data-driven optimization framework for wearable microstrip patch antennas operating near the 2.4 GHz ISM band using an Adaptive Network-Based Fuzzy Inference System (ANFIS). The proposed approach predicts key antenna geometry parameters-patch width, patch length, and feed point coordinates-from target electromagnetic performance metrics, including resonant frequency, reflection coefficient, bandwidth, and substrate thickness. A dataset of 500 samples was extracted from parametric HFSS simulations, and the ANFIS model was trained using a 70/30 training-testing split. Four membership function types "triangular, trapezoidal, Gaussian, and generalized bell" were systematically evaluated to analyze their influence on prediction accuracy and convergence behavior. Results demonstrate strong agreement between ANFIS predictions and HFSS simulations, with sub-millimeter mean absolute errors for patch dimensions and high regression coefficients across parameters. Among the tested membership functions, the generalized bell function showed the most stable convergence and the lowest overall prediction error. The proposed approach reduces reliance on repeated full-wave simulations by providing rapid estimation of antenna geometry from performance specifications, enabling faster prototyping of wearable antennas. The results highlight the importance of membership function selection in neuro-fuzzy modeling for antenna design and demonstrate the feasibility of ANFIS-based surrogate modeling for wearable communication devices.

Abnormal crowd detection and estimation are critical in video surveillance for ensuring public safety and preventing stampedes. Owing to occlusions and blind spots, traditional video surveillance methods cannot detect, estimate, or locate people in dense moving crowds with acceptable accuracy, posing a major challenge. Therefore, this study aims to provide an in-depth analysis of the most recent advancements in recognizing abnormal behaviors in large crowds. We present a comprehensive literature review on crowd anomaly detection using disruptive technologies such as radio frequency identification, wireless sensor networks, Wi-Fi, and Bluetooth low energy, employing device-free noninvasive algorithms based on received signal strength indicator variations to detect the speed and direction of a moving crowd to predict the onset of a stampede. Furthermore, this study presents the most recent findings on mobile crowdsensing based on edge computing, urban dynamics, optical flow, and machine learning techniques. Finally, we critically analyze the major challenges, shedding light on opportunities and directions for future work.

A virtual power plant (VPP) is analogous to a microgrid. However, a VPP is designed to participate in the electricity markets, such as the day-ahead (DA) and the real-time (RT) markets, while a microgrid does not. In order to participate in the electricity markets, historical data evaluation is necessary to predict market behavior. There are three main parameters to predict: the day-ahead market price, the real-time market price, and the renewable energy sources data such as the wind speed. One of the popular techniques used for forecasting is the autoregressive integrated moving average (ARIMA) model. In this paper, an improved ARIMA model is introduced. Using the proposed sequential ARIMA model, the VPP operator can forecast the uncertain parameters with higher accuracy, improving the optimization decisions taken by the VPP. This will reduce the risk of failure to participate in the electricity markets and give a better opportunity to achieve better results in terms of the optimization objectives such as cost minimization and profit maximization.

There are many advantages to deploying small-scale distributed generation resources. They reduce the power generation cost, enhance the system's overall voltage profile, and reduce system losses. However, misplacing them could have an adverse effect on the power system. In this paper, the optimal size and site of a distributed generation unit are determined to enhance the voltage stability of a power network. A voltage stability index is employed to determine the weakest link in the system. Then, the optimal size of the distributed generation unit is calculated. Newton-Raphson optimal power flow is employed to solve this problem. The voltage stability index enhancement and loss reduction are examined during normal, stressed loading, and contingency conditions. The simulation is carried out on IEEE 14 bus mesh system. The results show that the method used in this paper successfully improves the system's voltage stability and decreases power losses.

Demand-generation mismatch introduces extensive technical as well as economic challenges to the power system network. Furthermore, with the increasing global interest in integrating variable renewable generation systems, it becomes more challenging to eliminate demand-generation mismatch. Therefore, the elimination of demand-generation mismatch will define the efficacy and quantify the economics of future renewable integrated smart grid systems. Incorporating batteries to provide energy buffering is among the most feasible, but most expensive, solutions to deal with system discrepancies. The battery energy storage system (BESS) has a limited life cycle and inherently lacks economic significance due to frequent charging and discharge. Therefore, in this paper, a monotonic operation of BESS is coordinated and kept between maximum and minimum State-of-Charge (SoC). The classical controller has been designed and validated with sets of generation and load profiles with two batteries. Accordingly, a neural network system based on pattern recognition is trained to operate the BESS under monotonic operation.

Recently, massive events are gathering bigger crowds than ever before. During such events, minor incidents can escalate to big tragedies. Consequently, crowd monitoring and management have become an important research topic in pursuing innovative technologies that can help mitigate such risks. In this paper, a novel crowd monitoring system is fully developed and verified. The system is wearable and has a simple manufacturing process. It includes processing and communication modules and vital-sign sensors (temperature, skin hydration, and heart rate). Wearability is achieved using an innovative Kirigami-based, stretchable Printed Circuit Board (PCB) with a remarkable stretchability, up to 65%. Moreover, the system has a two-way wireless communication module enabling a smartphone interface. The system receives the vital signs from the sensors, analyzes the sensor's data, sets off an alarm to the user in case of emergency, and submits the collected information to a management center. Thus, data collected from many individuals in the crowd may be analyzed to detect big scale crises and potentially help prevent tragedies. The developed wearable system was successfully tested in Makkah city, and its sensitivity to crowd density was demonstrated.

This article presents an integrated current mode configurable analog block (CAB) system for field-programmable analog array (FPAA). The proposed architecture is based on the complementary metal-oxide semiconductor (CMOS) transistor level design where MOSFET transistors operating in the saturation region are adopted. The proposed CAB architecture is designed to implement six of the widely used current mode operations in analog processing systems: addition, subtraction, integration, multiplication, division, and pass operation. The functionality of the proposed CAB is demonstrated through these six operations, where each operation is chosen based on the user's selection in the CAB interface system. The architecture of the CAB system proposes an optimized way of designing and integrating only three functional cells with the interface circuitry to achieve the six operations. Furthermore, optimized programming and digital tuning circuitry are implemented in the architecture to control and interface with the functional cells. Moreover, these designed programming and tuning circuitries play an essential role in optimizing the performance of the proposed design. Simulation of the proposed CMOS Transistor Based CAB system is carried out using Tanner EDA Tools in 0.35 mu m standard CMOS technology. The design uses a +/- 1.5 V power supply and results in maximum 3 dB bandwidth of 34.9 MHz and an approximate size of 0.0537 mm2. This demonstrates the advantages of the design over the current state-of-the-art designs presented for comparison in this article. Consequently, the proposed design has a clear aspect of simplicity, low power consumption, and high bandwidth operation, which makes it a suitable candidate for mobile telecommunications applications.

This study demonstrates that a drone flying above photovoltaic (PV) panels can clean the dust and enhance the panels' efficiency. If operated regularly, the drone's downward thrust generated during its cruise at a certain height above the panels can remove most of the accumulated dust. Sandstorms are frequent in Saudi Arabia, creating dust deposition on PV panels, which acts as a shield against solar radiation. As a result, the energy absorption from solar radiation is reduced and subsequently, the panels' energy output is reduced. This experimental investigation was conducted at KFUPM University's beach, Dhahran, Saudi Arabia, to prove the effectiveness of drone-based cleaning of PV panels. Volumes of 20, 50, and 100 CC of dust were spread on the panel during different experiments. These experimental results showed that the back thrust of the drone could remove most of the dust and improve the solar panels' energy output performance. For example, for 50 CC dust spread on the panel, the current increased from 1.34 A to 2.16 A (61.2% increase), relative to the pre- and post-drone flight for horizontal movement of the drone. Similarly, for vertical and diagonal movements, the current increased by 69.83% and 68.03%, respectively, for a dust spread of 20 CC. Furthermore, dust reductions of 74.64%, 57.0%, and 78.4% were realized during the horizontal, vertical, and diagonal paths, respectively, of the drone flight for 50 CC dust spread.

The security and safety of public places have been a concern to more entities in recent decades. Video surveillance is widely used to guarantee the security and safety of public places. Yet, abnormal crowd movement detection and estimation are essential in video surveillance to avoid incidents like a stampede. The most challenging problem is detecting and locating people in moving dense crowds with obstacles like occlusion and blind spots where traditional video surveillance techniques fail. This paper presents an extensive review of state-of-the-art advances in detecting abnormal behavior in dense crowds approaches. The techniques are based on range-free localization for detecting the direction and speed of the crowd movement. Radio Frequency Identification (RFID) and Wireless Sensor Networks (WSN) are surveyed. RFID is used by analyzing the Received Signal Strength Indicator (RSSI) for detecting orientation and speed of crowd movement and provides information like the crowd density, movement velocity, flow rate, and the number of persons passing to detect the onset of a stampede.

Utilization of a communication network to transmit remote-control signals might introduce time delay into the control loop, which degrades the controller efficacy. This paper proposes a new design of wide-area damping controller based on scattering transformation to enhance power system stability. The proposed control approach is comprised of a classical structure in addition to two scattering transformation ports. These ports are inserted between the power system and the wide-area damping controller (WADC) to regulate the signal exchanging between them. Since the WADC is a centralized controller, the time-delay imperfections are considered in the design stage. The proposed controller improves the system damping performance thanks to the achieved time-delay compensation. The effectiveness of the proposed controller is demonstrated by implementing the controller in several case studies under different disturbance scenarios. The proposed controller performance is benchmarked with the classical WADC based on lead-lag structure. The efficacy of the proposed controller is confirmed to reduce the time delay resulting in a better power system stability.

This article presents a novel hybrid control scheme for speed control of Brushless DC (BLDC) motor by simultaneously controlling BLDC motor reference current and inverter DC bus voltage. A fractional-order PID (FOPID) controller is employed to control BLDC motor reference current while a fuzzy logic controller manipulates the inverter DC bus voltage. A modified harmony search (HS) metaheuristic technique is developed for FOPID controller parameters tuning. Three different operating conditions are applied to test the motor, including no-load operation, varying load operation, and varying speed operation to verify the proposed controller’s effectiveness. Furthermore, the proposed hybrid control strategy has been compared to Fuzzy-based and FOPID-based speed control schemes. The obtained results confirm that the proposed control scheme provides better and accurate speed control over a wide range of speeds. Also, the proposed controller decreases the torque ripples under different operating conditions.

Over the past decade, chaotic systems have found their immense application in different fields, which has led to various generalized, novel, and modified chaotic systems. In this paper, the general jerk equation is combined with a scaled sine map, which has been approximated in terms of a polynomial using Taylor series expansion for exhibiting chaotic behavior. The paper is based on numerical simulation and experimental verification of the system with four control parameters. The proposed system’s chaotic behavior is verified by calculating different chaotic invariants using MATLAB, such as bifurcation diagram, 2-D attractor, Fourier spectra, correlation dimension, and Maximum Lyapunov Exponent. Experimental verification of the system was carried out using Op-Amps with analog multipliers.

This paper presents a new design of a scattering transformation-based wide-area damping controller for static synchronous series compensator (SSSC) to enhance power system stability in the presence of communication latency. The proposed control approach is comprised of a classical structure in addition to two scattering transformation ports. These ports are inserted between the power system and the wide-area damping controller (WADC) to regulate the signal exchange. Since the WADC is a centralized controller, the time delay imperfections are considered in the design stage. The proposed controller design is formulated as an optimization problem where the controller parameters are optimized using the particle swarm optimization (PSO) algorithm. The proposed controller improves the system damping performance due to the achieved time delay compensation. The proposed controller's effectiveness is demonstrated by implementing the controller in several case studies under different disturbance scenarios. The proposed controller performance is benchmarked with the classical WADC based on the lead-lag structure. The results confirm the robustness of the proposed WADC against time delay uncertainty. The proposed controller's efficacy is confirmed to reduce the time delay, resulting in better power system stability.

In massive events, minor incidents can cause big tragedies. Therefore, the development of crowd monitoring technologies for risk mitigation has become of great relevance. Thus, we have developed and verified a novel wearable crowd monitoring system that includes processing, communication, and vital signs sensing capabilities (temperature, skin hydration, and heart rate). A novel stretchable Printed Circuit Board (PCB) was developed to achieve high stretchability and wearability. Moreover, the collected data from individuals in a crowd may be further analyzed to detect potential crises and prevent tragedies. Finally, the performance of the developed system was verified in real-life experiments in Makkah city.

This paper proposes a non-superconducting bridge-type fault current limiter (BFCL) as a potential solution to the fault problems of doubly fed induction generator (DFIG) integrated voltage source converter high-voltage DC (VSC-HVDC) transmission systems. As the VSC-HVDC and DFIG systems are vulnerable to AC/DC faults, a BFCL controller is developed to insert sizeable impedance during the inception of system disturbances. In the proposed control scheme, constant capacitor voltage is maintained by the stator VSC (SVSC) controller, while current extraction or injection is achieved by rotor VSC (RVSC) controller. Current control mode-based active and reactive power controllers for an HVDC system are developed. Balanced and different unbalanced faults are applied in the system to show the effectiveness of the proposed BFCL solution. A DFIG wind-based VSC-HVDC system, BFCL, and their controllers are implemented in a real time digital simulator (RTDS). The performance of the proposed BFCL control strategy in DFIG-based VSC-HVDC system is compared with a series dynamic braking resistor (SDBR). Comparative RTDS implementation results show that the proposed BFCL control strategy is very efficient in improving system fault ride through (FRT) capability and outperforms SDBR in all cases considered.

This paper proposes a non-linear control-based variable resistive bridge type fault current limiter (VR-BFCL) as a prospective solution to ease the effect of disturbances on voltage source converter-based high voltage DC (VSC-HVDC) systems. A non-linear controller for VR-BFCL has been developed to insert a variable optimum resistance during the inception of system disturbances in order to limit the fault current. The non-linear controller takes the amount of DC link voltage deviation as its input and provides variable duty to generate a variable effective resistance during faults. The VSC-HVDC system’s real and reactive power controllers have been developed based on a current control loop where direct axis and quadrature axis currents are used to control the active and reactive power, respectively. The efficacy of the proposed non-linear control-based VR-BFCL solution has been proved with balanced as well as unbalanced faults. The results confirm that the oscillations in active power and DC link voltage have been significantly reduced by limiting the fault current through the insertion of an optimum effective resistance with the proposed control technique. The real time digital simulator (RTDS) has been used to implement the proposed approach. The performance of the proposed non-linear control based VR-BFCL is compared with that of traditional fixed duty control.

This paper presents the control of active front-end rectifier (AFE) using finite set model predictive control (MPC). Finite set MPC uses discrete nature of power converter to generate the optimal switching states. The power flow, as well as the power factor of the rectifier, is controlled by controlling the input currents using current controller. In this work, MPC is used as a current controller for its robust dynamic response which also avoids the difficult task of tuning classical controller. The set points for inner MPC are generated from an outer voltage regulator. The performance of the proposed MPC based controller has been compared with classical VOC based PWM controller for AFE. The results obtained from the simulation study demonstrate the efficacy of the proposed MPC based control scheme. The system modeling and control strategy has been developed in RSCAD software and simulated in the real-time environment using real-time digital simulator (RTDS).

In this paper, a new capacitor-less DC-DC converter is proposed to be used as a light emitting diode (LED) driver. The design is based on the utilization of the internal capacitance of the LED to replace the smoothing capacitor. LED lighting systems usually have many LEDs for better illumination that can reach multiple tens of LEDs. Such configuration can be utilized to enlarge the total internal capacitance and hence minimize the output ripple. Also, the switching frequency is selected such that a minimum ripple appears at the output. The functionality of the proposed design is confirmed experimentally and the efficiency of the driver is 85% at full load.

Electric spring (ES) is a novel smart grid technology, which is based on power electronic components. It has multitude of benefits associated with its widespread use at distribution level, which includes voltage profile enhancement, power imbalance mitigation, and power quality improvement. With the ever increasing need of incorporating intermittent renewable energy sources (RES), electric spring offers a viable solution to the problems linked with such energy sources. A new generation of electrical loads is also recently proposed, known as smart loads, which is the outcome of integrating electric spring in series with a non-critical load. This work proposes a novel control scheme for electric spring based on fuzzy logic to regulate mains voltage. Simulations are carried out for ES based on conventional PI controller, fuzzy logic controller, and adaptive fuzzy PI and their results are analytically compared.

Voltage source converter high voltage DC (VSC-HVDC) system has number of advantages over traditional line commutated converter HVDC (LCC-HVDC). However, VSC-HVDC system is exposed to high current due to faults having great negative effect on converters. In order to limit fault current to relatively low level, bridge type fault current limiter (BFCL) for VSC-HVDC system has been proposed in this study. Fault current limiters are placed with the AC gird sides of VSC-HVDC system. Real and reactive power controller for the VSC-HVDC has been developed based on current control mode. Symmetrical as well as unsymmetrical faults are applied to evaluate the effectiveness of proposed BFCL controller in order to limit the fault current and improve system stability. Simulations are carried out with real time digital simulator (RTDS) to validate the efficacy of the proposed BFCL solution. The results show the potential of the proposed scheme to limit the fault current and improve greatly the system performance.