Wireless Technology Research Articles

Diagnostic value of 4D pelvic floor ultrasound for postpartum mild to moderate pelvic organ prolapse in primiparas based on medical thermal imaging monitoring

Traditional diagnostic methods often rely on the doctor’s experience, which can lead to missed diagnosis or misdiagnosis. With the development of wireless network medical technology, it provides a new possibility for the diagnosis of pelvic floor ultrasound. The purpose of this study was to evaluate the diagnostic value of 4D pelvic floor ultrasound based on wireless network medical technology in puerperal mild to moderate pelvic organ prolapse, and to explore its feasibility in clinical application. In this study, puerperal women were selected for 4D pelvic floor ultrasound examination after delivery, and image data was transmitted in real time to remote experts for analysis combined with wireless network technology. The sensitivity, specificity and application effect of the technique were evaluated by comparing the ultrasound results with the clinical diagnosis results. The results show that compared with traditional methods, wireless network medical technology can significantly improve the efficiency of image transmission and diagnosis accuracy. Therefore 4D pelvic floor ultrasound based on wireless network medical technology can effectively diagnose the postpartum mild and moderate pelvic organ prolapse of first-time partrients, which has high clinical application value, not only improves the diagnostic efficiency, but also provides a new development direction for telemedicine, and is worthy of promotion and application in clinical practice.

Power Transmission Technology Using Wireless Network

In this paper, we have presented the concept of wireless transmission i.e. power transmission without using any type of the electrical conductor and/or wires. We have presented an idea that is discussed here about how electrical energy can be transmitted as microwaves so that to reduce the transmission, allocation and other types of losses. Such technique is known as Microwave Power Transmission (MPT). We have also presented and correlated several aspects with the currently available Power transmission systems to the related history of wireless power transmission systems and also the related developmental changes. The basic design, merits and demerits, applications of Wireless Power Transmission are also discussed . The paper describes the various types of WPT technologies; Inductive Coupling, Magnetic Resonance and Radio Frequency (RF) technology. It also discusses the advantages and shortfalls of each type. An extensive survey of past works was discussed. Results from the research findings showed that distance and conversion efficiency were limiting factors in implementing wireless transfer technology

Improving efficiency of wireless charging system in electric vehicle using a hybrid ultracapacitor-battery energy storage approach

This research aims to enhance the efficiency of wireless charging systems in electric vehicles by integrating a hybrid ultracapacitor-battery energy storage solution. Traditional standalone battery-based energy storage systems in wireless charging often face sub-optimal charging efficiency, resulting in extended charging times and reduced energy transfer efficiency. To address this limitation, we propose a hybrid approach that combines the rapid charging capability of ultracapacitor (supercapacitor) with the long-term storage capacity of batteries. The optimal charging range is 0 cm to 2 cm, and the combined output voltage and current are 5 V to 12 V and 0.63 A, respectively. This hybrid energy storage system will significantly boost electric vehicles (EVs) charging efficiency. Our research involves experimental evaluation and data analysis to assess crucial parameters, including charging efficiency, energy transfer efficiency, and charging time. The experimental results are validated and compared against existing battery-only systems, shedding light on the advantages and limitations of the hybrid approach. This study contributes to the optimization of wireless charging systems, enhancing energy transfer efficiency, and promoting the broader adoption of wireless charging technology in electric vehicles.

Gulf of Mexico Case Study Highlights Smart-Completion Application

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 218794, “Multifaceted Smart Completion Application: A Gulf of Mexico Case Study,” by Jeffrey P. Manning, Ben J. Carter, SPE, and Leila Bannister, Occidental Petroleum, et al. The paper has not been peer reviewed. _ Reservoir heterogeneity, stacked pay systems, reservoir compartmentalization, and high temperature and pressure are common challenges seen in Gulf of Mexico (GOM) fields. The use of conventional completion design in vertical wells with commingled production from multiple zones has led to multiple operational challenges. In the complete paper, the authors explore the use of intelligent completions in deepwater GOM as a solution. Benefits of Intelligent Completions Intelligent completions allow collection, transmission, and validation of real-time, high-frequency data. This enables analysis of completion, production, and reservoir data while selected reservoir zones are controlled and monitored remotely in real time. Intelligent completions such as multiphase flowmeters, bottomhole pressure gauges, and cased-hole logging tools enable real-time data gathering and monitoring. Additionally, downhole flow-control systems, pinpoint stimulation, intelligent injection, and multizonal isolation technology are examples of intelligent completions that enable production optimization. This study concentrates on the application of downhole intelligent choke systems in wells that use radio frequency identification technology. Combining this technology with smart sensors or Global Positioning System technology enables sensor data to be transmitted wirelessly. Operations such as opening and closing of valves, indexing and release mechanisms, and a variety of other functions can be implemented using this technology. Multiple tools can be run at the same time without compromising the tool’s internal diameter. Each tool has a unique address; therefore, tags can be coded with data that identifies an individual tool to be actuated. Intelligent completions can be broadly categorized into the following: - Downhole flow-control systems: These are passive or active control systems to control flow from each zone. They are remotely controlled by hydraulic lines from the surface facility. - Permanent downhole sensors: These are discrete or distributed systems that monitor downhole parameters. - Permanent downhole chemical injection: These systems allow for treatment at different points in the wellbore and flowlines to prevent issues caused by corrosion, hydrates, asphaltenes, paraffin, and scaling. Case Study: Practical Use of Intelligent Completions in the GOM The operated field in the northern GOM has successfully used intelligent completions in multiple vertical producing wells to help significantly reduce operating costs associated with topsides water processing, mitigate the risk of sand production, and allow for better subsurface understanding using individual zone-flow tests (this synopsis concentrates on the first two of these three aspects). Intelligent completions enabled these operations without the use of an intervention vessel.

Space-based solar power: Unlocking continuous, renewable energy through wireless transmission from space

Space-Based Solar Power (SBSP) is an emerging technology that aims to harness the abundant and uninterrupted solar energy available in space and beam it wirelessly to Earth. This innovative approach addresses the limitations of terrestrial solar energy, such as weather variability and the day-night cycle, by positioning solar power stations in space where sunlight is constant. The stations, composed of large arrays of solar panels, capture the solar energy and convert it into microwaves or laser beams, which are then transmitted to receiving stations on Earth for conversion into usable electricity. Research in SBSP focuses on optimal orbital positions, with geostationary and low Earth orbits being considered for maximum energy capture and efficient transmission. Advancements in materials, wireless power transmission technologies, and space-based assembly techniques are critical to the design and deployment of these stations. Additionally, economic and technical feasibility studies explore the challenges of launching, maintaining, and scaling SBSP systems. These include high initial costs, energy transmission efficiency, safety concerns, and the logistics of long-term maintenance. The potential benefits of SBSP are significant. It offers a clean, renewable energy source that could meet the growing global demand for electricity while reducing reliance on fossil fuels. By providing continuous energy, SBSP could enhance energy security and contribute to global efforts to combat climate change. However, several challenges remain, including addressing space debris risks and ensuring the safety of high-power energy transmission to Earth. As research and technological advancements continue, SBSP holds promise as a transformative solution for future energy needs.

Experimental investigation to analyze the electromagnetic radiation exposure from wireless communication devices

Recent advancements in wireless communication technologies have led to the existence of a higher amount of electromagnetic radiation (EMR) in the atmosphere. The intensity of these exposed radiation depends upon the frequency of operation from these communication devices. The paper presents a scientific study on assessing the intensity of electromagnetic waves emitted by different wireless communication devices with human beings based on analyzing the electric field, magnetic field and power density generated from various electronic gadgets and wireless communication devices like smartwatch, laptop, mobile phone, nano-station, headset and mobile towers using an electro-smog meter (Electromagnetic Field (EMF) Meter - PCE-EM 29). The interaction is being studied by placing different wireless communication equipment near to human body. Based on the study, it is identified that a portion of the EMR is absorbed by nearby human beings and is identified by differentiating the field characteristics with and without its presence and is tested in near or far away from the devices. From the test results, it is identified that a portion of the EMR is absorbed by the body parts of the human beings near to the wireless device. This result could act as scientific evidence providing the effects of EMR interactions like electromagnetic hypersensitivity symptoms on humans. Similarly, most of the field exposures from the radiating devices are highly influenced by all the biotic community including human beings based on its interaction. All these field exposures to radiation from various wireless communication devices are direct indications of the Specific Absorption Rate (SAR).

Assessing the impact of radiofrequency radiation from cellular towers on human health: A comprehensive review

The proliferation of cellular communication towers, driven by the rapid advancement of wireless technologies like 4G and 5G, has raised significant public health concerns regarding the potential effects of long-term exposure to radiofrequency (RF) electromagnetic radiation (EMR). This review explores the implications of RF radiation emitted by these towers, which is classified as non-ionizing and typically associated with thermal effects, albeit at levels considered safe by major health organizations such as the World Health Organization (WHO) and the International Commission on Non-Ionizing Radiation Protection (ICNIRP). Key topics addressed include the mechanisms of RF radiation interaction with biological systems, public concerns about health effects including cancer risks, neurological impacts, reproductive health, and the controversial condition known as electromagnetic hypersensitivity (EHS). While numerous studies suggest that RF exposure does not lead to significant adverse health outcomes at permissible levels, evidence regarding potential non-thermal effects, such as oxidative stress and changes in cell signaling, remains inconclusive. The review emphasizes the need for further research into the long-term effects of RF radiation, particularly with the expansion of 5G technology, and considers the regulatory frameworks established to ensure public safety. The conclusion highlights a cautious approach, advocating for ongoing scientific inquiry and the application of the precautionary principle, especially concerning vulnerable populations like children and pregnant women.

High-fidelity digital-analog hybrid RoF fronthaul link enabled by nonlinear radio signal shaping.

We propose a simple and effective method to enhance the fidelity of radio signals in a digital-analog radio-over-fiber (DA-RoF) system by introducing nonlinearity into the transmitted signal. This nonlinearity is introduced via an arctangent function for radio signal shaping (RSS), while the corresponding tangent function is used for signal recovery. Nonlinear shaping spreads near-zero amplitude signals and compresses far-from-zero ones. After nonlinear recovery, noise in near-zero signals is suppressed, while noise in far-from-zero signals is amplified. Since the radio signal follows a Gaussian distribution, with most amplitudes near zero, the overall SNR is improved. In our experiments, we demonstrate the proposed radio signal shaping technology using a DA-RoF system based on intensity modulation with a direct detection communication system, achieving a 1.8-dB SNR gain. We achieve an SNR of 34.17 dB for QAM-1024 signals at a DA-RoF symbol rate of 104 Gbaud over 1 km of fiber. This corresponds to a CPRI-equivalent rate of 1560 Gbps and an equivalent fronthaul channel capacity of 294.85 Gbps. Our proposed scheme offers a promising solution for high-fidelity, high-capacity RoF links in Beyond 5G (B5G) and 6G networks.

Analysis of Data Communication Networks for VTS Surabaya in Class I Type A Navigation District Tanjung Perak

A reliable data communication network is essential in supporting Vessel Traffic Service (VTS) operations, especially in managing vessel traffic in the Class I Navigation District of Tanjung Perak, Surabaya. However, challenges such as network reliability, bandwidth capacity, and potential interference are still obstacles in ensuring efficient operations. This research aims to analyze the condition of the data communication network at the Tanjung Perak Class I Navigation District VTS, focusing on the technology used, its performance, and the obstacles faced. This research uses a qualitative descriptive approach, with data collected through direct observation, interviews with VTS operators, and analysis of related documents. The results show that the communication network at VTS uses Very High Frequency (VHF) frequency-based radio communication technology to support operations, such as digital maps of ship traffic and Automatic Identification System (AIS) systems. In conclusion, the data communication network at the Tanjung Perak Class I Navigation District VTS has met basic operational needs, but still requires further development in terms of technology and infrastructure to improve its efficiency and reliability. This research provides recommendations for the integration of advanced technology, infrastructure improvement, and human resource training to optimize the performance of the communication network.

Unified Multi-Abstraction-Level Functional Testing and Performance Measurements for Industrial IoT in Spatially Distributed Narrow Band-Wireless Wide Area Networks

Narrow Band-Wireless Wide Area Networking (NB-WWAN) technologies are becoming more popular across a wide range of application domains due to their ability to provide spatially distributed and reliable wireless connectivity in addition to offering low data rates, low bandwidth, long-range, and long battery life. For functional testing and performance assessments, the wide range of wireless technology alternatives within this category poses several difficulties. At the device level, it is necessary to address issues such as resource limitations, complex protocols, interoperability, and reliability, while at the network level, challenges include complex topologies and wireless channel/signal propagation problems. Testing the functionality and measuring the performance of spatially distributed NB-WWAN systems require a systematic approach to overcome these challenges. Furthermore, to provide a seamless test flow, it is also critical to test and compare the performance of wireless systems systematically and consistently across the different system development phases. To evaluate NB-WWAN technologies comprehensively across multiple abstraction levels—network simulators, emulated lab testbeds, and field test environments—we propose a unified multi-abstraction-level testing methodology. A detailed technical description of the prototype implementation and its evaluation is presented in this paper.

Reliable and cost-efficient session provisioning in CRNs using spectrum sensing as a service

With the advancement of wireless communication technologies, and the growing number of wireless and IoT applications that demand various types and volumes of data, Sensing as a Service (SaaS) has emerged as a necessary enabling business model for many of those applications. Spectrum Sensing as a Service (SSaaS) has also emerged as a form of SaaS that is concerned with the monitoring of wireless spectrum to facilitate its safe reuse by cognitive radio-enabled wireless users. SSaaS was primarily motivated by the need for a low-cost, accurate, and reliable spectrum sensing service to support a plethora of heterogeneous wireless devices and applications. Under the SSaaS model, clients need to pay the service provider for the sensing service they receive. In this paper, we address the problem of allocating spectrum channels to links of a given communication session in a cognitive radio network (CRN) that utilizes SSaaS. The objective is to allocate channels such that the worst link availability among the session is maximized and the spectrum access cost is minimized. A number of multi-objective evolutionary optimization algorithms (MOEAs) were used to solve this multi-objective optimization problem. Extensive experimentation was conducted to compare between these algorithms and identify the best ones to use. We also propose a post-processing greedy algorithm to further enhance the solution obtained by a MOEA algorithm. Results show that an improvement of up to 20% can be achieved using the proposed greedy algorithm under some network settings.

Research and Analysis on the Application of Radio Frequency Identification Technology in the Internet of Things and Future Development

Research and Analysis on the Application of Radio Frequency Identification Technology in the Internet of Things and Future Development

Self-Powered Wearable Displacement Sensor for Continuous Respiratory Monitoring and Human-Machine Synchronous Control.

Flexible wearable electronic devices play a vital role in daily monitoring, medical diagnosis, and human-computer interaction, and such devices have a great demand for portability, integration, comfort, and self-power. In this study, a triboelectric nanogenerator integrated into a flexible chest belt is proposed as a displacement sensor to monitor the displacement and frequency of thoracic expansion. Based on three parallel interpolation electrode structures with phase differences, the Triboelectric Nanogenerators's(TENG) output signal pulse number can characterize the sliding displacement, with a resolution of more than 1mm and a durability of more than 700,000 cycles. Based on the flexible printed circuit processing technology, the volume of the sensor is less than 8.5cm3, and the weight is less than 3.2g, which improves the portability of the device. Based on wireless radio frequency technology, the collected signals are transmitted to the upper computer, and then the monitoring of respiratory physiological signals and the human-machine synchronous control of the ventilator are achieved within the overshoot of 1.5% and the control error of 5% through a simulation machine. This work provides a sensing method for daily and medical respiratory monitoring and demonstrates the enormous potential of frictional electric sensors in intelligent medical applications.

Safety Dynamic Monitoring and Rapid Warning Methods for Mechanical Shaft

In the context of urban space constraints, subway and underground projects have become crucial strategies to alleviate urban congestion and enhance residents’ quality of life. However, pit engineering, a frequent accident area in geotechnical engineering, urgently requires innovative safety monitoring technologies. Traditional monitoring methods face challenges such as high labor costs, lengthy monitoring cycles, high-risk working environments, and over-reliance on human judgment. To address these issues, this paper introduces an innovative monitoring system integrating Fiber Bragg Grating (FBG) sensing technology based on a subway pit project in Guangzhou. This system not only achieves fully automated data acquisition but also includes an intelligent monitoring cloud platform, providing unprecedented automated and intelligent monitoring solutions for support structures and the surrounding environment during mechanical shaft construction. The key findings of this paper include the following: (1) The breakthrough application of distributed optical fiber monitoring technology, including successfully deploying this advanced technology in complex pit engineering environments, enabling the precise and continuous monitoring of support structures and surrounding changes, and demonstrating its high effectiveness and intelligence in practical engineering. (2) The innovative design of an intelligent safety monitoring system. By integrating sensors and wireless communication technology, an efficient data networking architecture is constructed, supporting remote configuration and flexible adjustment of monitoring equipment, significantly enhancing data collection‘s real-time performance and continuity while greatly reducing safety risks for field staff, achieving an intelligent upgrade of monitoring work. (3) Comprehensive and accurate empirical analysis. During shaft excavation, the monitoring data collected by the system were stable and reliable, with all indicators maintained within reasonable ranges and closely matching expected changes caused by construction activities, validating the system’s practical application effectiveness in complex construction environments and providing a scientific basis for pit engineering safety management.

Wi-Fi Sensing Techniques for Human Activity Recognition: Brief Survey, Potential Challenges, and Research Directions

Recent advancements in wireless communication technologies have made Wi-Fi signals indispensable in both personal and professional settings. The utilization of these signals for Human Activity Recognition (HAR) has emerged as a cutting-edge technology. By leveraging the fluctuations in Wi-Fi signals for HAR, this approach offers enhanced privacy compared to traditional visual surveillance methods. The essence of this technique lies in detecting subtle changes when Wi-Fi signals interact with the human body, which are then captured and interpreted by advanced algorithms. This paper initially provides an overview of the key methodologies in HAR and the evolution of non-contact sensing, introducing sensor-based recognition, computer vision, and Wi-Fi signal-based approaches, respectively. It then explores tools for Wi-Fi-based HAR signal collection and lists several high-quality datasets. Subsequently, the paper reviews various sensing tasks enabled by Wi-Fi signal recognition, highlighting the application of deep learning networks in Wi-Fi signal detection. The fourth section presents experimental results that assess the capabilities of different networks. The findings indicate significant variability in the generalization capacities of neural networks and notable differences in test accuracy for various motion analyses.

Enhanced 6G MIMO Signal Detection With Dynamic Sparse Region‐Based Convolutional Neural Network With White Shark Optimization

ABSTRACTMultiple‐input multiple‐output (MIMO) technology is emerging as a promising choice for upcoming sixth‐generation (6G) and beyond‐fifth‐generation (B5G) networks due to the advancements in AI. However, the complexity of MIMO systems, which involve numerous antennas, results in a challenging detection process with high computational demands. To address the interference challenges inherent in large‐scale MIMO technology, this research proposes a 6G massive MIMO signal identification algorithm that integrates a Dynamic Sparse Region‐based Convolutional Neural Network (DSR‐CNN) with White Shark Optimization (WSO) into conventional MIMO receivers. The DSR‐CNN dynamically refines proposal boxes and features, enhancing detection accuracy by effectively handling complex signal patterns. The WSO optimizes the weight parameters within the R‐CNN, improving the algorithm's convergence toward optimal solutions. This hybrid methodology significantly reduces bit error rates (BER) and enhances detection performance, making it ideally suited to the advanced requirements of 6G networks. The proposed approach, DSR‐CNN‐WSO, not only improves accuracy and efficiency but also seamlessly integrates with existing MIMO systems, offering a robust solution for future wireless communication technologies. The proposed method achieves significantly lower BER (0.01) and Mean Square Error (MSE) (0.1), indicating more reliable bit detection and more accurate signal detection.

Real-Time Self-Positioning with the Zero Moment Point Model and Enhanced Position Accuracy Using Fiducial Markers

Many companies are turning their attention to digitizing the work efficiency of employees in large factories and warehouses, and the demand for measuring individual self-location indoors is increasing. While methods combining wireless network technology and Pedestrian Dead Reckoning (PDR) have been developed, they face challenges such as high infrastructure costs and low accuracy. In this study, we propose a novel approach that combines high-accuracy fiducial markers with the Center of Gravity Zero Moment Point (COG ZMP) model. Combining fiducial markers enables precise estimation of self-position on a map. Furthermore, the use of high-accuracy fiducial markers corrects modeling errors in the COG ZMP model, enhancing accuracy. This method was evaluated using an optical motion capture system, confirming high accuracy with a relative error of less than 3%. Thus, this approach allows for high-accuracy self-position estimation with minimal computational load and standalone operation. Moreover, it offers a cost-effective solution, contributing to society by enabling low-cost, high-performance self-positioning. This research enables high-accuracy standalone self-positioning and contributes to the advancement of indoor positioning technology.

Wireless Remote-Monitoring Technology for Wind-Induced Galloping and Vibration of Transmission Lines

In order to achieve wireless remote monitoring of wind-induced vibrations in power-transmission lines based on MEMS sensors, it is necessary to devise a method for reconstructing the wind swing curve, enabling the device’s real-time performance to promptly acquire, restore, and analyze data. Based on existing single-axis vibration-sensitive components, a measurement array using self-powered MEMS sensors and spacers has been designed. The Orthogonal Matching Pursuit (OMP) algorithm is selected to obtain displacement data collected by sensors installed on the transmission-line spacers. Leveraging the inherent sparsity of the data, a Gaussian white noise regularization matrix is chosen to establish the observation matrix. Through the algorithm, wind data curve reconstruction is achieved, enabling the reconstruction of large-span wind-induced vibration information without distortion. The experimental results demonstrate that when applying the orthogonal tracking algorithm in transmission-line curve reconstruction, sparsity is selected based on the sampling length, that is, the number of sensors installed on the spacers is determined by the span length; a portion of the observation values are selected to generate the observation matrix; and the wind galloping data curve of the transmission line is well restored.

The Application of National Security Algorithm in Wireless Networks for Industrial Automation Process Automation (WIA-PA) Network Data Security Transmission

Industrial wireless communication technology is the key to promoting the development of factory intelligence and automation. However, wireless network data security has hindered the development of industrial intelligence. Therefore, to solve the security issues of industrial wireless networks, a network data secure transmission technology based on the national security algorithm is proposed based on industrial wireless network standard protocols. Firstly, to address the vulnerability of network node identity authentication to attacks, the national security algorithm is used to construct a node authentication model. Secondly, a data security transmission model is constructed based on the improved national security algorithm, which can securely transmit industrial wireless networks by encrypting network application layer data. In network node identity authentication, when the step size was 50, the identity authentication average accuracy of the research mode reached over 98.95%, which was better than other models. When the step size was 50, the average accuracy of identity authentication in the research model was over 98.95%, showing the best performance among similar models. In the attack test of illegal client C, when the interaction history data was within 500, the node identity authentication was higher than 99.56%. However, when the interaction history data exceeded 500, the overall performance of the research model was still the best. In the comparison of node code storage and content usage overhead, when the code quantity was 15000, the storage overhead of the research model was 87356 bytes, with more node code storage and lower memory usage. The overall performance of the research model is better. From this, the research method performs the best in both identity recognition accuracy and security in network data security. The research content will provide technical support for the security management and data transmission of industrial wireless technology.

Conventional Banking Strategy in Facing Digital Financial Institutions in the Era of Banking Competition

Industry 4.0 is an era of rapid development or change that covers all aspects of industrial activity and human life using digital technology and the internet. Industry 4.0 is also known as a systematic production activity through the use of wireless technology and big data, which makes data use more precise with server systems, and integrates all operations automatically into the system. The data collected and analyzed in this study were collected and analyzed to produce authoritative studies and achieve research objectives. This study uses a data collection method through library research. The data collected comes from English and Arabic literature, Islamic banking, journals, and other sources found in libraries and other information centers. Digital banks are expected to facilitate the backup and analysis of bank consumer data. To make it easier for banks to maintain customer relationships, handle customer complaints better, and improve products and services that are faster, cheaper, clearer, more accurate, and better for customers. The banking industry faces new challenges and expectations during this digital economy era. Companies are turning to digital banking to retain their old clients and attract new clients from the millennial generation. Digital banking is a term that refers to the use of technology in banks. It refers to banking services that use digital technology to meet client needs and develop the desired digital economy.