Wireless Research Articles

Assessing DIEP flap perfusion using handheld wireless laser speckle contrast imaging: A proof of principle study.

In reconstructive surgery, adequate perfusion of flaps is essential for successful outcomes. Assessing normal flap perfusion and differentiating it from problematic perfusion is important and time-consuming. Laser speckle contrast imaging (LSCI), an optical technique for quantitative microcirculation assessment, can be used to non-invasively monitor flap perfusion. We designed a wireless handheld LSCI device and investigated its clinical feasibility in Deep Inferior Epigastric Perforator (DIEP) flap reconstruction surgery. In a case series study with 15 patients and 20 DIEP flaps, perfusion was measured perioperatively across the 4 Hartrampf zones at 4 specific time points and on the first post-operative day. In unilateral reconstructions, the perfusion in dissected flaps showed a perfusion gradient across the zones, with the highest perfusion in zone I and lowest perfusion in zone IV. The decrease in perfusion between unilateral flap elevation and temporary occlusion measurements was detected in unilateral flaps, but not in bilateral flaps. The device could detect flap failure in 2 cases by measuring anomalous perfusion values. The results indicate that our device is potentially valuable for flap monitoring. It detected differences in perfusion throughout the flap zones, a decrease in perfusion when clamping the pedicle and anomalous perfusion in flaps that failed. Motion artefact correction is needed to measure reliably during motion caused by patient breathing, pulse and operator motion. Further studies are needed to determine whether the wireless perfusion imager enables the early detection of complications, which could aid in prevention or prompt reintervention to salvage a flap.

Validation of Wireless Harness for Measuring Respiratory Rate, Heart Rate, and Body Temperature in Hospitalized Dogs

Continuous monitoring of vital signs could improve patient care in veterinary hospitals by identifying changes earlier and reducing patient stress from repeated handling. This study aimed to assess the agreement between a wireless harness device and manual measurement of heart rate, respiratory rate, and body temperature in hospitalized dogs. Nineteen client-owned dogs wore the harness throughout hospitalization and paired manual and harness measurements were collected every 4–8 h. Linear regression and Bland–Altman analysis were used to assess agreement. The device demonstrated strong correlation with manual measurements for heart rate and respiratory rate; however, the limits of agreement (LoA) exceeded predefined clinical thresholds, indicating high variability in individual readings. Temperature measurements showed a mean difference of 1.34 °F (manual minus harness), indicating underestimation by the harness. The LoA for temperature also exceeded predefined clinical thresholds, particularly in dogs with long fur. Fur length significantly influenced respiratory rate and temperature measurements, but not heart rate. Chest conformation also impacted respiratory rate and temperature accuracy. Heart rate was the most consistent parameter across all body types. Overall, the device tracked trends in heart rate and respiratory rate, supporting its potential as a supplemental monitoring tool. However, measurements should be confirmed manually prior to clinical decision-making.

A Self-Supervised Specific Emitter Identification Method Based on Contrastive Asymmetric Masked Learning

Specific emitter identification (SEI) is a core technology for wireless device security that plays a crucial role in protecting wireless communication systems from various security threats. However, current deep learning-based SEI methods heavily rely on large amounts of labeled data for supervised training, facing challenges in non-cooperative communication scenarios. To address these issues, this paper proposes a novel contrastive asymmetric masked learning-based SEI (CAML-SEI) method, effectively solving the problem of SEI under scarce labeled samples. The proposed method constructs an asymmetric auto-encoder architecture, comprising an encoder network based on channel squeeze-and-excitation residual blocks to capture radio frequency fingerprint (RFF) features embedded in signals, while employing a lightweight single-layer convolutional decoder for masked signal reconstruction. This design promotes the learning of fine-grained local feature representations. To further enhance feature discriminability, a learnable non-linear mapping is introduced to compress high-dimensional encoded features into a compact low-dimensional space, accompanied by a contrastive loss function that simultaneously achieves feature aggregation of positive samples and feature separation of negative samples. Finally, the network is jointly optimized by combining signal reconstruction and feature contrast tasks. Experiments conducted on real-world ADS-B and Wi-Fi datasets demonstrate that the proposed method effectively learns generalized RFF features, and the results show superior performance compared with other SEI methods.

Wireless device to checking pollution severity of high voltage transmission line insulators

ABSTRACT In electrical systems insulation plays major role. The level of insulation safety provided depends upon the amount of leakage current flowing on its surface. This paper proposes detection of leakage current, temperature in transmission line. The proposed system upgrade electrical safety by quick interruption of the power supply such fault events like leakage current, short circuit and has been designed with the goal to be integrated in smart grid or smart sub-station for protecting the electrical equipment. The system also enables real-time monitoring and notification events through a 16*2 LCD display interface using a Microcontroller board. This paper provides an extended description of the proposed system’s design and implementation, as well as the experimental validation results. This paper proposes an efficient system for identifying the issues in transmission line based on Internet-of-Things technologies and the parameters like Current flow using CT, Potential transformer for Voltage measurement level and temperature are read using PIC Microcontroller. It has been designed with the goal to be integrated in smart grid or smart sub-station for protecting the electrical equipment. This paper proposes a relay protection device for transmission line based on Internet-of-Things technologies.The system also enables real-time monitoring and notification events through an advanced communication interface using a microcontroller architecture. Keywords-Internet of things,current transformer,potential transformer,digital relay

Energy Consumption Optimization Method of Edge Computing System Based on Wireless Energy Transmission of UAV

Mobile edge computing (MEC) and wireless power transmission (WPT) can provide energy supply and task computing for wireless devices, effectively improving the energy efficiency of devices. On the basis of wireless energy transfer for drones, we provide an approach to optimizing energy usage for edge computing systems. By simultaneously optimizing the energy harvesting (EH) duration, user transmission power, as well as offloading choice, the presented method reduces the overall energy usage of the system. We decompose the optimization problem into two sub-problems with the block coordinate descent method (BCD). Simulation results suggest that our presented system energy consumption optimization method outperforms other baseline schemes and the energy required by the system can be significantly reduced.

Novel triangular-diamond fractal MIMO antenna with super-wideband capability for portable 5 G/IoT-driven wireless devices

Abstract This research introduces the modeling, simulation, and performance testing of a dual-element, fractal-inspired super-wideband multiple-input multiple-output (MIMO) antenna tailored for applicability in emerging fifth-generation (5 G)/Internet of Things (IoT) networks. The array utilizes a 1.57 mm flame retardant (FR)-4 substrate sheet, covering a 28 × 35.6mm2 footprint. The array design incorporates two microstrip-fed hexagonal radiators, each embedded with a novel triangular-diamond fractal (2nd iterative) shape on its upper face, yielding an efficient impedance matching across a broad operating spectrum of 2.4–18 GHz with 152.94% fractional bandwidth. Adopting this novel fractal pattern contributes to a 48.25% area reduction relative to the standard hexagonal patch configuration. The partial ground structure, assembled on the rear FR-4 surface, integrates defected ground structure (DGS) and funnel-type decoupling strategies to effectively limit inter-element coupling and signal mismatches. Several diversity performance indicators are assessed and observed to adhere to their prescribed thresholds, confirming the consistency between the simulation and practical measurements. The proposed array is engineered to meet the escalating need for space-efficient, well-isolated antennas in portable electronics, facilitating real-time communication in dynamic 5 G/IoT environments.

Sustainable Management of Energy Storage in Electric Vehicles Involved in a Smart Urban Environment

Electric vehicles are increasingly being used for green transportation in smart urban mobility, thus protecting environmental biodiversity and the ecosystem. Energy storage by electric vehicle batteries is a critical point of this ecologically responsible transportation. This storage is strongly linked to the different external managements related to its capacity state. The latter concerns the interconnection of storage to energy resources, charging strategies, and their complexity. In an ideal urban context, charging strategies would use wireless devices. However, these may involve complex frames and unwanted electromagnetic field interferences. The sustainable management of wireless devices and battery state conditions allows for optimized operation and minimized adverse effects. Such management includes the sustainable design of devices and monitoring of complex connected procedures. The present study aims to analyze this management and to highlight the mathematical routines enabling the design and control tasks involved. The investigations involved are closely related to responsible attitude, “One Health”, and twin supervision approaches. The different sections of the article examine the following: electric vehicle in smart mobility, sustainable design and control, electromagnetic exposures, governance of physical and mathematical representation, charging routines, protection against adverse effects, and supervision of complex connected vehicles. The research presented in this article is supported by examples from the literature.

Evaluation of Websites of Wireless Telecommunications Companies in Algeria Using Z-number TOPSIS

Evaluation of Websites of Wireless Telecommunications Companies in Algeria Using Z-number TOPSIS

Enhancing Multiband Fractal Antenna Design through Green Anaconda Optimization (GAO)

Fractals can be applied to antenna elements to create smaller, resonant, multiband/broadband antennas that can potentially be gain-optimized. They are easy and affordable to construct, and they don't require extra loading components. They can be affixed to restrictive form factors, such as the case of hand-held transceivers. For many real-world uses, fractal antennas prove to be valuable, high-performing, resonant antennas. They enable greater adaptability in their use with wireless devices and are typically built as or on tiny circuit boards. A new outline Multiband Printed Circular Fractal antenna is proposed in this paper. This roundabout fix receiving device is capable of operating at 10.3GHz, 16.7GHz, and 21.7GHz frequencies. It is employed because the fractal design system fills space and is self-comparable. The purpose of the roundabout fix antenna is to minimize the projected radio cable's area. The dielectric of the measurement substrate, the Rogers RT Duroid5880, is 2.2. The HFSS.15 programming software is used to calculate the proposed radio wire's radiation pattern, gain, return loss, and VSWR. The ultimate goal of Green Anaconda Optimization (GAO), which mimics the behavior of green anacondas, is to develop this suggested Multiband Fractal Antenna by increasing its efficiency, dependability, and range.

The Parametrization of Electromagnetic Emissions and Hazards from a Wearable Device for Wireless Information Transfer with a 2.45 GHz ISM Band Antenna

The parameters of electromagnetic emissions from the antenna of a wearable radio communication module (parameterizing device functionality) were investigated at different positions near the body where an antenna is located. The specific absorption rate (SAR) coefficient was also investigated as a way of parameterizing the absorption of electromagnetic radiation in the user’s body adjacent to the antenna in various locations. The modeled exposure scenarios concerned a body-worn device with a 2.45 GHz ISM band antenna (used, e.g., for Wi-Fi 2G/Bluetooth applications). The antennas were modeled as follows: (1) located directly on the body (considered to be a model of a disposable, adhesive device) or (2) next to the body (considered to be a model of a classic, reusable, wearable electronic device located inside a plastic housing). Several body sections adjacent to the antenna were considered: head, arm, forearm, and chest (simplified and anatomical body models were used). The numerical models of the exposure scenarios were verified by relevant laboratory tests using physical models. It was found that the use of simplified models of the human body (numerical or physical) may be sufficient when analyzing antenna performance and SAR in a user’s body, such as in studies regarding microwave imaging and sensing, wireless implantable devices, wireless body-area networks or SAR estimation.

Return Loss Optimization in Rectangular Microstrip Patch Antennas Using Response Surface Methodology (RSM) for 5G Applications

In recent decades, wireless communication has advanced significantly. People increasingly rely on the Internet of Things, cloud computing, and big data analytics. These services require higher data rates, faster transmission and reception times, greater coverage, and increased throughput. 5G technology supports all of these features. Antennas, essential components of modern wireless devices, must be designed to meet the growing demand for fast and intelligent products. This study aims to optimize the dimensions and characteristics of a rectangular patch antenna. To examine the impact of independent variables (such as patch length, patch width, inset slot length, and inset slot width) on the response variables (return loss and resonant frequency), Response Surface Methodology (RSM) combined with Central Composite Design (CCD) was applied. The findings of the RSM analysis indicated that the experimental data were best represented by a quadratic polynomial model, with regression coefficients exceeding 0.970 for all responses. The optimized parameters identified are as follows: a patch length of 4.7 mm, a patch width of 4.7 mm, an inset slot length of 0.8 mm, and an inset slot width of 1.0 mm. The antenna designed using these optimized parameters achieved a target return loss of -45.865 dB at a frequency of 28.122 GHz. Finally, the results were validated using CST Studio Suite, which demonstrated good agreement with the experimental data.

Aging With Artificial Intelligence: How Technology Enhances Older Adults' Health and Independence.

As the global population ages healthcare challenges are escalating. Frailty, a clinical syndrome characterized by decreased reserve and resilience to stressors, is critically linked to adverse health outcomes in older adults. However, artificial intelligence (AI)-driven technologies offer promising solutions for revolutionizing older individuals care and enhancing senior health and independence. This paper explores how AI-driven technologies, including wearables, nonwearable devices, and wireless systems, are transforming senior care. These innovations enable continuous health monitoring, fall detection, medication adherence, and cognitive assistance. Recent advancements in sensor technology, machine learning/AI algorithms, and user interface design have made these technologies more effective and accessible to older adults. Key benefits include early health issue detection, improved medication adherence, reduced hospitalizations, extended independent living, and improved quality of life. Privacy concerns, ease of use, and technology adoption are challenges that must be addressed. Thoughtfully designed AI wearables and supportive policies and infrastructure can significantly enhance seniors' quality of life while reducing caregiver burden and healthcare costs. As technology advances, AI-driven solutions across wearable, nonwearable, and wireless devices are set to become indispensable in global strategies for healthy aging.

The influence of Wi-Fi on the mesonephros in the 9-day-old chicken embryo

The use of wireless devices has increased rapidly in recent times, especially in developed countries. As a result, all living systems are to some extent permanently exposed to this artificial electromagnetic non-ionizing radiation (NIR). These modern devices provide countless benefits to the users, but the disadvantage of their excessive use is the production of electrosmog. This physical pollutant of the environment can be particularly dangerous especially during the developmental period of the individual. The aim of the current study was to elucidate the effect of Wi-Fi radiation on the mesonephros development in the chicken embryo on day 9 of incubation. Continual 9-day application of radiation with a frequency of 2.4 GHz and a power density of 200—500 µW/m2 had no adverse effect on the general development of the mesonephros, however moderate diffuse degenerative changes were found in the developing mesonephric corpuscles and tubules. Also congested blood vessels were present in the surrounding interstitium, but no signs of inflammatory infiltrate were detected. In the Wi-Fi group, we also noted a significantly increased number of apoptotic and proliferating cells as well as a significant up-regulation of caspase-1 gene expression. The results indicated that non-ionizing radiation at the frequency and power density used in the study can interfere with the key regulatory mechanisms involved in the normal development of tissues and organs.

P300 ERP System Utilizing Wireless Visual Stimulus Presentation Devices

The P300 event-related potential, evoked by attending to specific sensory stimuli, is utilized in non-invasive brain–computer interface (BCI) systems and is considered the only interface through which individuals with complete paralysis can operate devices based on their intention. Conventionally, visual stimuli used to elicit P300 have been presented using displays; however, placing a display directly in front of the user obstructs the field of view and prevents the user from perceiving their surrounding environment. Moreover, every time the user changes posture, the display must be repositioned accordingly, increasing the burden on caregivers. To address these issues, we propose a novel system that employs wirelessly controllable LED visual stimulus presentation devices distributed throughout the surrounding environment, rather than relying on traditional displays. The primary challenge in the proposed system is the communication delay associated with wireless control, which introduces errors in the timing of stimulus presentation—an essential factor for accurate P300 analysis. Therefore, it is necessary to evaluate how such delays affect P300 detection accuracy. The second challenge lies in the variability of visual stimulus strength due to differences in viewing distance caused by the spatial distribution of stimulus devices. This also requires the validation of its impact on P300 detection. In Experiment 1, we evaluated system performance in terms of wireless communication delay and confirmed an average delay of 352.1 ± 30.9 ms. In Experiment 2, we conducted P300 elicitation experiments using the wireless visual stimulus presentation device under conditions that allowed the precise measurement of stimulus presentation timing. We compared P300 waveforms across three conditions: (1) using the exact measured stimulus timing, (2) using the stimulus timing with a fixed compensation of 350 ms for the wireless delay, and (3) using the stimulus timing with both the 350 ms fixed delay compensation and an additional pseudo-random error value generated based on a normal distribution. The results demonstrated the effectiveness of the proposed delay compensation method in preserving P300 waveform integrity. In Experiment 3, a system performance verification test was conducted on 21 participants using a wireless visual presentation device. As a result, statistically significant differences (p < 0.01) in amplitude between target and non-target stimuli, along with medium or greater effect sizes (Cohen’s d: 0.49–0.61), were observed under all conditions with an averaging count of 10 or more. Notably, the P300 detection accuracy reached 85% with 40 averaging trials and 100% with 100 trials. These findings demonstrate that the system can function as a P300 speller and be utilized as an interface equivalent to conventional display-based methods.

Optimal Realization of Parallel MAC-Based Adaptive FIR Filter Using a Gaussian Mutation on Quantum-Behaved Particle Swarm Optimization Algorithm

With the increasing prevalence of Digital Signal Processing (DSP) circuits in audio devices, the demand for low-power and high-performance processors has grown due to hardware limitations. Low-power design is particularly important for wireless audio devices with limited battery capacity. Nevertheless, as Field Programmable Gate Array (FPGA) technology advances, many challenging algorithms have recently been implemented to achieve high computing performance for both embedded and real-time applications. Conventional Least Mean Square (LMS) algorithms face challenges in real-time noise cancelation due to short secondary path delays. To address this, an optimized Finite Impulse Response (FIR) filter system using Particle Swarm Optimization (PSO) and Gaussian mutation on Quantum-Behaved PSO (GQPSO) is proposed. This design, implemented in a low-end FPGA, employs pipelined parallel multipliers and partial product-based shift-and-add multipliers for resource efficiency. GQPSO-based adaptive FIR filters are developed in Verilog and synthesized for 8-tap and 16-tap configurations, showing significant performance gains. Post-route FPGA results demonstrate an 89.3% reduction in area utilization and a 97.3% speed improvement over existing architectures, highlighting their effectiveness for real-time noise cancelation.

Design of Microstrip Patch Antenna for 5G Applications

The development of microstrip patch antennas for 5G applications is driven by the need to support high-frequency millimeter-wave bands (24–40 GHz and beyond). These antennas are small, lightweight, and easily integrated into modern wireless devices. Essential design features include selecting low-loss substrates, achieving impedance matching to minimize signal reflections, and optimizing parameters such as bandwidth, gain, and radiation efficiency. To further improve performance, techniques such as antenna array configurations and advanced feed algorithms are used, which enable capabilities such as beam steering. The integration of multiple-input multiple-output (MIMO) technology improves system performance and communication reliability. Simulation tools are instrumental in optimizing antenna designs to overcome the challenges associated with high-frequency operations. Microstrip patch antennas are critical for deploying 5G networks, enabling high-speed, low-latency communication essential for IoT, smart devices, and other advanced connectivity platforms. This paper presents the design and performance analysis of a microstrip patch antenna tailored for 5G frequency bands, specifically targeting the 28 GHz and 38 GHz ranges within the millimeter-wave spectrum. The antenna utilizes a low-loss dielectric substrate to achieve a small footprint while providing improved gain, wide bandwidth, and efficient radiation characteristics. Simulation results confirm the antenna’s ability to meet stringent 5G performance standards, showing low return loss and high radiation efficiency. The proposed design addresses key challenges related to miniaturization and high-frequency operation, making it well-suited for integration into mobile devices, IoT systems, and 5G base station infrastructure.

Multiband printed rectenna for radio frequency energy harvesting (RF-EH)

The growing demand for renewable energy has spurred significant interest in radio frequency (RF) energy harvesting as a sustainable method to power wireless devices. This paper presents a novel multiband monopole rectenna design for efficient RF energy harvesting across key wireless communication bands, including 900 MHz to 2.1 GHz (GSM/GPRS), 4.5 GHz (WiMAX), and 7 GHz (lower 5G). The antenna and rectifier are simulated in CST Studio and fabricated on a low-cost FR4 substrate. The monopole antenna exhibits strong resonances at 900 MHz, 4.5 GHz, and 7 GHz, with − 10 dB impedance bandwidths of 90, 7, and 21%, respectively, demonstrating robust impedance matching. Both simulated and measured reflection coefficients align with performance standards for WLAN, GSM/GPRS, and WiMAX applications. A key innovation of this work is the integration of a unified matching circuit that optimizes DC power conversion efficiency across multiple bands, simplifying the system architecture. The rectifier employs a Schottky diode with a low junction potential (0.34 mV) and a breakdown voltage of 2 V, striking an optimal balance between high power conversion efficiency and wideband operation. This design advances RF energy harvesting technology, offering a scalable and energy-efficient solution for next-generation wireless systems.

Micromagnetic simulation and optimization of spin-wave transducers

The increasing demand for higher data volume and faster transmission in modern wireless telecommunication systems has elevated requirements for 5G high-band RF hardware. Spin-Wave technology offers a promising solution, but its adoption is hindered by significant insertion loss stemming from the low efficiency of magnonic transducers. This work introduces a micromagnetic simulation method for directly computing the spin-wave resistance, the real part of spin-wave impedance, which is crucial for optimizing magnonic transducers. By integrating into finite-difference micromagnetic simulations, this approach extends analytical models to arbitrary transducer geometries. We demonstrate its effectiveness through parameter studies on transducer design and waveguide properties, identifying key strategies to enhance the overall transducer efficiency. Our studies show that by varying single parameters of the transducer geometry or the YIG thickness, the spin-wave efficiency, the parameter describing the efficiency of the transfer of electromagnetic energy to the spin wave, can reach values up to 0.75. The developed numerical model allows further fine-tuning of the transducers to achieve even higher efficiencies.

NetFlow Analyzer

The rapid growth in wireless device usage has created an urgent need for intelligent, secure, and efficient network management systems. This paper introduces NetFlow Analyzer, an advanced Wi-Fi management solution that offers a real-time, end-to-end view of network activity with a focus on bandwidth tracking, indoor location detection, device management, and security enforcement. The system enables per-device bandwidth monitoring, allowing administrators to visualize data usage and detect unusual activity with precision. A standout feature of NetFlow Analyzer is its indoor positioning system, which uses RSSI-based Wi-Fi triangulation combined with SciPy optimization techniques to accurately track the physical location of connected devices within a defined space. Built on a Flask backend with MongoDB and a feature-rich React.js frontend, the platform provides a seamless user experience. Administrators can manage connected devices through an approval-based control system, ensuring only authorized users access the network. To safeguard against misuse, the system triggers automated alerts for data threshold breaches and unauthorized connection attempts. Incorporating Scapy for deep packet inspection and real-time network traffic analysis, NetFlow Analyzer empowers administrators with detailed visibility and control. The solution is ideal for high-traffic environments like campuses, enterprises, and public Wi-Fi zones, delivering an integrated approach to performance monitoring, location awareness, and network security.

Flexible Rectenna on an Eco-Friendly Substrate for Application in Next-Generation IoT Devices

Globally, there are now more than 19 billion connected Internet of Things (IoT) devices, which are fostering innovation across various sectors, including industry, healthcare, education, energy, and agriculture. With the rapid expansion of IoT devices, there is an increasing demand for sustainable, self-powered, eco-friendly solutions for next-generation IoT devices. Harvesting and converting radio frequency (RF) energy through rectennas is being explored as a potential solution for next-generation self-powered wireless devices. This paper presents a methodology for designing, optimizing, and fabricating a flexible rectenna for RF energy harvesting in the 5G lower mid-band and ISM 2.45 GHz band. The antenna element has a tree form based on a fractal structure, which provides a small size for the rectenna. Furthermore, to reduce the rectenna’s environmental impact, we fabricated the rectenna on a substrate from biodegradable materials—natural rubber filled with rice husk ash. The rectifier circuit was also designed and fabricated on the flexible substrate, facilitating the seamless integration of the rectenna in next-generation low-power IoT devices. The numerical analysis of the parameters and characteristics of rectenna elements, based on the finite-difference time-domain method, demonstrates a high degree of agreement with the experimental results.