Notice boards play a vital role in day-to-day life and are constructively used in various places. Using manual paper-based noticeboards at universities, and public spaces like hospitals, bus stations, and transport hubs has become a tedious task to perform daily, especially when frequent notice updates are required. There is also a risk of false notices being posted on these manual noticeboards if not secured properly. With the advancement in technologies over the last decade, electronic noticeboards have gained widespread attention due to their simplicity, flexibility, low cost, and rapid response, and are becoming an essential element for relaying messages or notices in such places. This article proposes a solar-powered wireless electronic noticeboard using an ESP8266 microcontroller. A webpage has been developed to instantly update the message or notice on the electronic noticeboard via Wi-Fi communication. To prevent unauthorized messages or notices being posted, the proposed system is password-protected and requires authentication from the users to access the webpage. The proposed system has several features that give users greater flexibility such as retrieving the current message or notice being displayed on the noticeboard, providing an option to specify a time frame for which a message or notice should be displayed, and providing an option to mark the message as an emergency message or notice, so that the alert is highlighted on the notice board for quick attention. The system also integrates a sleep mode feature which reduces its power consumption. The proposed system is low-cost and offers better efficiency and security over manual noticeboards.

Managing firmware updates in large-scale IoT deployments presents significant challenges regarding security, reliability, and operational cost. This paper presents the design and implementation of “IOTAfy”, a new, open-source, comprehensive, Over-The-Air (OTA) firmware management platform tailored for ESP32-based IoT devices. “IOTAfy” distinguishes itself through its efficient database design and asynchronous update mechanism, enabling scalable deployments. The proposed system comprises a device-side solution for ESP32 microcontrollers, incorporating a custom bootloader, an application firmware boilerplate code, and an OTA library, alongside a web-based management interface developed using PHP, SQLite3, and Bootstrap. This integrated approach facilitates secure and reliable OTA application firmware updates. The platform enables centralized monitoring of device status, scheduled firmware updates, and robust version control for multiple IoT devices. OTA updates are implemented directly on the ESP32, eliminating the need for physical access or intervention. The web interface provides administrators with features for group upgrades, rollback capabilities, real-time update status monitoring and alerts. The system was tested in a controlled environment with 50 ESP32 devices, achieving a 98% success rate for OTA updates. Results demonstrate the potential for significant cost savings and reduced maintenance time compared to manual update processes. The architecture of the “IOTAfy” platform, leveraging an efficient database design and asynchronous update mechanism, facilitates scalability to hundreds or thousands of devices. This work offers a practical and scalable solution for managing firmware in large-scale IoT deployments, contributing to enhanced device security, improved reliability, and reduced operational expenditures.

The accelerating adoption of electric vehicles (EVs) has positioned them among the fastest-growing sectors in the electricity market. Since reliability, energy efficiency, and robustness are the fundamental criteria in motor drive selection, the permanent magnet synchronous motor (PMSM) has emerged as a preferred choice for EV applications. Nevertheless, achieving high-performance control of PMSM systems remains challenging due to nonlinear dynamics, parameter uncertainties, and external disturbances. To address these issues, this paper proposes a predefined-time output-feedback tracking control strategy for PMSMs subject to full-state error constraints, unknown nonlinear dynamics, external disturbances, and unmeasured states. Multi-dimensional Taylor networks (MTNs) are employed to approximate unknown nonlinearities, while MTN-based observers are designed to estimate unmeasured states. The proposed controller integrates predefined-time stability theory, a general potential Lyapunov function, dynamic surface control (DSC), and backstepping to guarantee constraint satisfaction and rapid convergence. A hyperbolic tangent function is incorporated to eliminate singularities, and a predefined-time filter is introduced to mitigate the computational complexity of recursive backstepping. Theoretical analysis based on Lyapunov methods proves that all closed-loop signals remain bounded and that the tracking error converges to zero within a prespecified time. Simulation results confirm the effectiveness, robustness, and practical feasibility of the proposed approach for PMSM-driven EV applications.

Laser diodes are crucial for the success of long-distance optical communication systems operating in the 1.2- to 1.6-μm range. The performance of these remarkable devices is significantly affected by optical feedback from external reflectors, which is determined by factors such as feedback strength, external cavity length, and injection current. Additionally, the rate of non-radiative recombination plays a crucial role in the performance of laser diodes, influencing key parameters such as carrier lifetime, threshold current, and turn-on time delay. In this study, we emphasize the important roles of non-radiative recombination rate and optical feedback in enhancing the dynamics and frequency noise of laser diodes. We categorize the dynamics of lasers based on bifurcation diagrams of photon numbers. Our findings indicate that a lower non-radiative recombination rate stabilizes the laser output and promotes periodic oscillation or continuous wave modes. In regions with strong optical feedback, decreasing the non-radiative recombination rate shifts the operation from chaotic to stable modes, aligning the frequency noise with the characteristics of solitary lasers. In chaotic regions, the frequency noise increases by over twelve orders of magnitude compared to the noise level of solitary lasers. Conversely, under weak optical feedback, an increase in the non-radiative recombination rate leads to a significant rise in low-frequency noise. By carefully engineering the non-radiative recombination rate and adjusting the strengths of optical feedback, we can effectively stabilize the performance of laser diodes and advance laser technology.

This article introduces a novel meta-surface configuration designed to enhance the gain of antennas for advanced communication systems. The proposed design features a rectangular meta-surface with circular cutouts placed beneath the rectangular ring, which contributes to improved electromagnetic performance. The core of the system is a rectangular monopole antenna, carefully designed to operate at two frequency bands: 3 GHz and 8 GHz. These dual-band capabilities ensure the antenna's adaptability to various wireless communication needs. To further boost performance, the monopole antenna is supported by two Artificial Magnetic Conductor (AMC) structures, which resonate at 3.9 GHz and 8.8 GHz, respectively. These AMC layers improve signal stability and improve the overall efficiency of the antenna. The antenna achieves a bandwidth of 3.2 at the 0.9 GHz resonance and 0.829 at the 3.9 GHz resonance, demonstrating its ability to maintain wide and stable operational ranges. Furthermore, when the design incorporates a 4×4 AMC array, the antenna's gain reaches 8.23 dB, ensuring stronger signal strength and improved coverage. This combination of meta-surface, monopole, and AMC structures provides a compact, efficient, and high-performance antenna suitable for real-world applications. With its improved gain, wide bandwidth, and reliable performance, this antenna design is a highly promising solution for enabling seamless 5G communication networks. It offers a powerful and efficient option for next-generation wireless systems that require enhanced signal integrity and broader coverage.

Electrical microgrids are essential components for the energy transition, facilitating the integration of renewable sources and demanding robust, formally validated control strategies. The IEC 61850 architecture establishes itself as the fundamental standard for ensuring interoperability in these complex systems. To address this challenge, this paper proposes a methodology that uses Interpreted Petri Nets (IPNs) to model, validate, and implement the control logic for a microgrid compatible with this architecture. The developed formal model represents all operational modes, including autonomous, grid-connected, and fault, as well as the transitions between them, which are conditioned by the availability of energy resources (Utility, BESS, and DG) and the occurrence of grid disturbances. Formal validation, conducted through reachability analysis, state space exploration, and incidence matrix verification, demonstrated that the model possesses the desired properties: it is complete, safe, bounded, live, and free of deadlocks. The control logic extracted from the IPN model was then converted into Ladder language (IEC 61131-3) and tested in a CODESYS simulation environment, which emulates the operation of a Programmable Logic Controller (PLC). The experimental results confirmed a perfect match between the simulated behavior and practical operation, validating the proposed approach. This study consolidates IPNs as a reliable formal tool for the digitalization of microgrid control systems, ensuring a safe and verified transition from design to implementation.

Tunnel Field-Effect Transistors (TFETs) are being widely explored for ultra-low-power VLSI because their band-to-band tunnelling (BTBT) transport permits subthreshold swings (SSs) below the 60 mV/dec thermionic limit at room temperature, along with significantly lower leakage than MOSFETs. This paper presents a systematic TCAD study of Double-Gate (DG) TFETs, which maps how four primary knobs—gate dielectric material, silicon channel thickness, gate length, and source and drain doping—shape the following key figures of merit: ON-current (ION), OFF-current (IOFF), threshold voltage (VTH), SS, and the ION/IOFF switching ratio. High-κ gate enhances gate-to-channel coupling and boosts tunnelling efficiency; rigorous body scaling enhances electrostatic control; and targeted source-proximal doping profiles elevate ION while minimising leakage. We also measure the trade-offs between ION, SS, and IOFF that occur when scaling is completed at the same time. This shows that careful coordination is needed instead of simply tuning one parameter. This is a simulated work; the physical models are calibrated to experimental TFET data, and all parameters were checked against previously reported results. The device reaches SS = 31.4 mV/dec, VTH = 0.46 V, ION = 5.91 × 10⁻⁵ A, and an ION/IOFF of about 4.5 × 10¹¹. This shows that it can switch quickly with little leakage. The design insights that come from this work can provide useful advice on how to choose gate dielectric materials, structures, and doping strategies so that DG-TFETs can be included in the next generation of low-power semiconductor technologies.

This work presents a facial emotion-based concentration monitoring system, designed with a didactic focus for students beginning their studies in Artificial Intelligence. The application uses the OpenCV library for real-time video capture and face detection, combined with a simple neural network model trained on facial expression images to classify seven basic emotions: anger, disgust, fear, happiness, neutral, sadness, and surprise. The key innovation of this project lies in its simple and accessible structure, allowing students to grasp core concepts of computer vision and machine learning through practical experimentation. The model was intentionally trained using a reduced and simplified dataset, emphasizing how basic neural architectures can still produce functional results in real-world scenarios. Based on the detected emotion, the system applies straightforward rule-based logic to estimate the user’s concentration level (high, medium, or low), offering an intuitive application of AI in educational or interactive environments. In addition to promoting technical learning, the codebase is modular, well-documented, and easily encourages students to explore extensions such as model refinement, data preprocessing, or alternative AI approaches. This work bridges theoretical learning and hands-on AI application, highlighting how even minimal resources and simple neural models can serve as powerful tools for understanding intelligent systems and human–computer interaction.

The stability of an electrical grid is compromised by unbalance between production and load; therefore, across the engineering literature, stability is an important concern in interconnected power systems. The present work seeks to remedy the phenomenon of instability of a power system linked to a Static Synchronous Compensator (Statcom) by introducing power system stabilizers (PSSs). The typical two-area, four-machine, and eleven-bus system is submitted to a three-phase fault without any control. A Statcom intruduces separately at the center of the line and at the access of the two areas of the studied system, and power system stabilizers are connected to the exciter with different inputs (conventional PSS with electrical power input ; conventional PSS with generator speed input ; multi-band PSS (MB_PSS)), offering the possibility of returning to the permanent regime for a short period. Matlab/Simulink simulation permits us to plot the inter-area transfer rotor speed and survey the permanent divergence of the oscillatory regime. Results are compared in order to detect the best solution to achieve transient stability.

Comparing the results of our simulation, we concluded that installing a delta w PSS with Statcom at the center of the line in the two-area power system provides the best solution to avoid the problem of instability in electrical grids.

The growing EV charging infrastructure introduces significant power quality issues due to harmonics from nonlinear loads like diode rectifiers and switching converters. These harmonics increase current/voltage THD, degrade power factor, voltage regulation, and system efficiency, often violating the IEEE 519 standard. This paper presents a comprehensive design and critical analysis of four passive harmonic filter topologies, namely, single-tuned filter (STF), double-tuned filter (DTF), high-pass filter (HPF), and C-type high-pass filter (CHPF), to mitigate harmonics and improve power quality in grid-tied EV charging stations. A generalized model is developed and simulated in MATLAB/Simulink R2021a for an EV charging load, with all filters evaluated under identical conditions based on current THD (I-THD), voltage THD (V-THD), input power factor (PF), voltage regulation (VR), and efficiency. The results indicate that the STF achieves an I-THD of 8.3%, V-THD of 4.6%, PF of 0.92, VR of 6.2%, and an efficiency of 91.3%. The DTF performs slightly better, with an I-THD of 6.1%, V-THD of 3.9%, PF of 0.95, VR of 5.4%, and efficiency of 93.5%. The HPF further improves these metrics, showing an I-THD of 5.6%, V-THD of 3.5%, PF of 0.96, VR of 5.0%, and efficiency of 94.2%. In comparison, the proposed CHPF outperforms all traditional filters, achieving the lowest I-THD and V-THD values of 3.7% and 2.1%, respectively, the highest PF of 0.987, improved VR of 3.8%, and superior efficiency of 96.2%. The results confirm that CHPF offers superior harmonic mitigation, voltage stability, power factor, and efficiency, thereby ensuring better vehicle-grid compatibility.