Wireless Research Articles

A circular-shaped two-slot foam-based flexible UWB antenna for medical applications

The biomedical industries have recently shown a great deal of interest in the study of flexible wireless devices. Wearable antennas are vital in medical applications as they enable continuous, real-time monitoring of patient health. In this context, a circular-shaped two-slot flexible ultra-wideband microstrip antenna is presented for use in the medical field. An inexpensive, lightweight flexible foam substrate material of 2 mm thickness with dielectric constant 1.07 and copper foil of 50 microns for patch is proposed in the fabrication of antenna. This paper presents a circularly shaped antenna of size 48×36mm2 with patch radius of 12 mm and detailed analysis of bending, on-body and SAR with actual measurement. A good matching is observed between measured and simulated results with the bandwidth of 10 GHz over the ultra-wideband operating frequencies of 3.1–10.7 GHz. The slot and stub added into geometry has resulted into the total gain of 4.7 dB, with good impedance matching. An extensive SAR analysis for 1 and 10 g tissue has been carried out with average SAR of 0.0215 W/kg and 0.0138 W/kg respectively and found below the safety limit as prescribed by IEEE.

Frequency Tunable Film Bulk Acoustic Resonator Integrating PMN‐PT/FSMA Multiferroic Heterostructure for Flexible MEMS

AbstractFrequency tunable flexible piezo resonators exhibit significant potential for technological advances in wearable magnetic field sensing, futuristic wireless telecommunication devices, and flexible micro‐electromechanical systems. This study presents a multifunctional and flexible 0.67Pb(Mg1/3Nb2/3)O3−0.33PbTiO3(PMN‐PT)/Ni50Mn35In15 (Ni‐Mn‐In) multiferroic heterostructure‐based bulk acoustic wave (BAW) resonator fabricated over Kapton substrate. The fundamental resonance frequency (fR = 5.31 GHz) of the resonator is tunable with magnetic and electric fields. A significant change in resonance frequency (ΔfR) of 405 MHz has been achieved with 3.37 Hz nT−1 sensitivity using a direct current (DC) magnetic field of 1200 Oe, attributed to the delta‐E effect. The resonator displays a significant magnetic field tunability of 8.83%. Additionally, a substantial ΔfR of 360 MHz, 36 Hz µV−1 sensitivity and 6.78% tunability is attained with 10 V of DC bias voltage. The impact of magnetic field and DC bias voltage on the acoustic characteristics have been studied by fitting the resonance frequency curves with an equivalent modified Butterworth‐Van Dyke model. The fabricated BAW resonator exhibits outstanding flexibility with no discernible change in fR up to 2000 bending cycles. Such PMN‐PT/Ni‐Mn‐In‐based multiferroic BAW resonators displaying magnetic and electric field tunability are propitious for next‐generation flexible electronics and magnetic field sensors.

HOME AUTOMATION SYSTEM USING COMPUTER VISION TECHNIQUE

Home automation using computer vision technology is an emerging field that aims to provide seamless and intelligent control of various home appliances and systems. This technology leverages the power of computer vision algorithms to identify and track objects, gestures, and movements, and then use this information to automate various tasks in the home environment. By integrating computer vision technology with home automation systems, homeowners can enjoy the benefits of a more intuitive and personalized home environment. Some of the potential applications of this technology include smart lighting, climate control, security, and entertainment systems. In this abstract, we will explore the key components of home automation using computer vision technology, the benefits and challenges associated with this technology, and some of the promising applications that are currently being developed. In this project we are going to work on home automation using computer vision technique. Normally home automation is controlled by using wireless devices, mobile phone and voice commands which indicated that a user is involved whil0.e accessing devices. In our project we are using facial detection system to check for the presence of human in a particular are and making the devices to operate without and command form the user. Key Words: Computer Vision, Haar Cascade Classifier, Face detection

Wireless Modular Implantable Neural Device with One-touch Magnetic Assembly for Versatile Neuromodulation.

Multimodal neural interfaces open new opportunities in brain research by enabling more sophisticated and systematic neural circuit dissection. Integrating complementary features across distinct functional domains, these multifunctional neural probes have greatly advanced the interrogation of complex neural circuitry. However, introducing multiple functionalities into a compact form factor for freely behaving animals presents substantial design hurdles that complicate the device or require more than one device. Moreover, fixed functionality poses challenges in meeting the dynamic needs of chronic neuroscience inquiry, such as replacing consumable parts like batteries or drugs. To address these limitations, the modular implantable neural device (MIND) is introduced with a one-touch magnetic assembly mechanism. Leveraging the seamless exchange of neural interface modules such as optical stimulation, drug delivery, and electrical stimulation, MIND ensures functional adaptability, reusability, and scalability. The versatile design of MIND will facilitate brain research by enabling simplified access to multiple functional modalities as needed.

A Scalable Framework for Secure and Reliable Wireless-based Fog Cloud Communication

—Wireless telecommunication systems are essential in transferring data through fog cloud servers. However, the fog cloud servers suffer from unreliable and non-secure routing and limited power resources when mobile users are mobile. This paper introduces a scalable framework (SFRRDC) for reliable wireless routing and secure data transfer. We aim to address security and reliability issues by combining pheromone termite (PT) characteristics and ant colony optimization (ACO) algorithms for high-performance, more secure, highly reliable data transfer among the fog cloud servers. For that, the proposed SFRRDC supports a user authentication mining (UAM) algorithm to secure the confidentiality of the users. Based on testing results, it is confirmed that the proposed SFRRDC provides a better solution for confidentiality and fast routing for a wireless telecommunication system. The results show that the proposed SFRRDC framework’s energy consumption outperforms competing frameworks’ energy consumption with a better-achieved latency. For example, the suggested SFRRDC method uses 748.5 Joules during 72 hours of operation, competing frameworks use more energy, and DDFQFR uses 976.22 Joules. It also shows that the proposed SFRRDC is immune to malicious attacks. The results show that with 3,600 Fog cloud users, the proposed HEE protocol reduces the number of attacks to only 48 compared to 58, 72, and 77415 expected malicious attacks when using the ICDRP-F-SDVN, ACO, and DDFQFR frameworks, respectively.

Structural, optical, and dielectric Properties of Sr2+ substituted Ba1-xSrx(Co1/2W1/2)O3 ceramics for wireless application

The solid solution of Ba1-xSrx(Co1/2W1/2)O3, (BSCWO), (0.0 ≤ x ≤ 0.60) ceramics has been prepared via conventional solid-state reaction route. In this work, the impact spawned by doping Sr2+ cation on the phase, dielectric, optical and morphological properties of (BSCWO), ceramics has been investigated with respect to the frequency range of 1-3GHz. The X-ray diffraction patterns revealed that the base sample has a tetragonal structure, while Sr+2 doped samples exhibit orthorhombic structure. The appearances of the surface and grain size distribution of samples are analyzed using scanning electron microscope (SEM). The FTIR study confirms the presence of metal-oxygen bond and functional groups. The dielectric properties of the prepared samples were strongly dependent on the frequencies and as well as on concentration. The UV-visible absorption spectra results, the band gap energy (Eg) drops from 2.56 to 2.37 eV with an increasing the Sr2+ contents. The EDX (energy dispersive x-rays) spectroscopy corroborate the presence of Ba, Sr, Co, and W elements. We observed the lowest dielectric loss (tan = 0.092) and the highest dielectric constant (εr = 51) at contents (x = 0.60), making it a promising option for wireless device applications.

Collective Diagnostic Prototypical in Internet of Medical Things for Depression Identification using Deep Learning Algorithm

Background:: The majority of wearable technology is employed in the Internet of Medical Things (IoMT) health monitoring systems to recognize various bodily indicators. All monitored values are sent to a central server, where they are all treated by experts at the appropriate moment. Therefore, by expanding the use of wireless devices, it has been discovered that such communication technologies can recognize specific depression traits and mood swings. Objectives:: The major objective of the proposed method is to analyze the disputes that arise in the characteristics of an individual by observing the leveling periods that are identified from the processed image. In addition, the rate of data transfer in case of any dispute is maximized therefore recognition problem is solved at a minimized distance. Further, the steady state probability values are achieved at low delay thus minimizing the dropout packets in the monitored system using IoMT and LSTM. Methods:: A balanced record with four distinct parameters—such as livelihood, self-reliance, correlation, and precision—is employed with the projected model on IoMT for depression identification. As a result, high data transfer rates and low distance separation are used to process the identification framework. Additionally, by combining an original matrix representation with the input feature set using LSTM, a novel framework with great efficiency is created. Results:: In order to assess the results of IoMT using LSTM, four situations are split apart and their probability ratios are calculated. The results of each situation are then contrasted with the current methodology, and it is found that when there is a low dropout ratio, depression in a person is quickly diagnosed. Conclusion:: The comparison analysis demonstrates that the proposed method, when compared to the current method, offers the best-compromised outcomes at roughly 64%.

Impact of micro-cracking and self-healing on electromagnetic interference shielding of ultra-lightweight engineered cementitious composites

The explosion of wireless devices and electronic equipment has escalated electromagnetic pollution, sparking health concerns and demand for building shielding materials. Ultra-lightweight engineered cementitious composites (ULW-ECCs) incorporating carbon fibres (CF) and calcined petroleum coke (CPC) were proposed for electromagnetic interference (EMI) shielding. The effects of microcracking and self-healing, common in real-world applications, on EMI shielding effectiveness (SE) were examined. Two levels of microcracking (low and high) were induced, each followed by a self-healing process in a natural environment. Various lengths and contents of CFs, along with different CPC contents, were tested. Damage evolution throughout the cracking–self-healing cycle was monitored by measuring resonant frequency, while microstructural variations were observed via optical microscopy and SEM-EDS. Results show hybrid CF with polyethylene fibre enhanced cracking resistance but reduced strain-hardening capacity. CF was proved more effective than CPC in enhancing both EMI SE and cracking resistance. EMI SE was influenced by the length and content of conductive filler. Microcracking reduced EMI SE by up to 24.8% at 1.0GHz, depending on severity and conductive fillers. Higher conductivity based on contact conductive pathways enhanced EMI SE but led to greater SE loss after cracking. Self-healing restored EMI SE to its original levels after low-degree cracking and recovered SE to low-cracking levels even after severe damage. The multiple microcracking of ULW-ECCs promotes the nucleation of healing products and crack closure. These findings provide insights into EMI shielding of ULW-ECCs under microcracking and self-healing, highlighting practical applications.

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).

Engineering Laboratory IAQ Monitoring: A Real-Time Solution using Raspberry PI and Grafana Dashboard

The World Health Organization (WHO) has reported that people who spent approximately 80 % - 90 % of their time being indoors daily, resulted in over 3 million premature deaths each year due to a disease caused by indoor air pollution. High concentration of indoor air pollutant such as particulate matter, carbon dioxide and imbalances between temperature and relative humidity have the potential to create unpleasant odour and dusty air, resulting in an incommodious environment and respiratory issues. The purpose of this project was to investigate the air quality at two engineering laboratories in a higher learning institution. A survey revealed that 41 % of students reported a bad odour in the workshop laboratory, while 38 % experienced the same issue in the Material & Automation Laboratory of the particular institution. Therefore, an IAQ (Indoor Air Quality) alert system was developed. The system consisted of sensors that measured the air quality, whereby data were continuously read and fed into a Raspberry PI controller by using a wireless communication device namely ESP-32. The controller has a smart card memory for logging purposes. The data were continuously read by a computer dashboard by using Grafana software. A beacon light was integrated with the controller to provide an alert indicator. Parameters measured were Particulate matter concentration, Carbon Dioxide level, Temperature and Humidity level. Measurement was done for three days while students were undergoing their activities in both laboratories. Data was benchmark with IAQ DOSH (Department of Safety & Health) and WHO (World Health Organisation). It was found that Particulate Matter in both laboratory and Workshop exceeded the IAQ limits, while the Carbon Dioxide reading was a concern. Temperature and Humidity were at acceptable levels but required constant monitoring.

Design of Circularly Polarized Koch Snowflake Fractal Antenna With Schottky Band Diode Rectifiers for RF Energy Harvesting Applications

ABSTRACTRadio frequency (RF) energy harvesting has recently become an effective way of powering wireless devices, reducing the requirement of batteries along with their related storage as well as lifespan restrictions. One of the main obstacles to RF energy harvesting is the limited quantity of energy that can be obtained from wireless sources due to weak signal strength, low efficiency, and poor gain. To address these shortcomings, the proposed method is designed based on the circularly polarized Koch snowflake fractal antenna with the Jerusalem cross (JC)–based frequency‐selective surface (FSS) and Schottky diode–based rectifiers for RF energy harvesting applications at the resonance frequency of 5.8 GHz. The electromagnetic energy from the environment can effectively captured using a proposed wide band and high gain antenna designed using a Koch snowflake array based on FSSs. Flame Retardant‐4 (FR‐4) material has good dielectric qualities for electronics, and it is employed as the dielectric substrate in this model; copper serves as the ground plane. The squid game optimizer (SGO) determines the ideal outer snowflake dimensions by maximizing the resonance frequency in order to achieve high gain. The optimally selected outer snowflake length and width are 40 and 23.09 mm. The designed antenna model uses a rectifier based on Schottky diodes for RF energy harvesting applications, which involves converting electromagnetic waves into direct current. The fractal antenna model and RF energy harvesting are designed and simulated using the ANSYS HFSS and Matlab RF toolbox. The model is used to evaluate the antenna's performance by concentrating on gain radiation patterns, S11, and voltage standing wave ratio (VSWR). The Koch snowflake fractal antenna, which uses a JC–based FSS, has been measured for performance at 5.8‐GHz frequency; the values obtained for impedance bandwidth, gain, S11, and VSWR are 7.61%, 9.962 dB, −33 dB, and 1.01, respectively. The analysis of the experimental data demonstrates that the Koch snowflake fractal antenna, which is being proposed for energy harvesting applications, outperforms several other existing designs in terms of effectiveness.

Rumus Umum Pelabelan L(2, 1) pada Graf Koprima Grup Bilangan Bulat Modulo m

Groups are nonempty sets equipped with binary operations and fulfill certain conditions. One example of a group is the group of integers modulo . A coprime graph of a group is a graph whose vertices are elements in and any two vertices in are directly connected if and only if the greatest common factor of the orders x and y are relatively prime. labeling has important applications in wireless telecommunication networks, where there are limited radio frequencies available and adjacent transmitters cannot use the same frequency. To overcome this problem, frequency assignment is done using the concept of labeling, where transmitters are symbolized as vertices connected by edges. labeling is a graph labeling technique that assigns non-negative integer labels to graph vertices with the rule that two directly connected vertices must have a minimum label difference of two, and two vertices that are two apart must have a minimum label difference of one. The purpose of this research is to find out the general formula for the labeling on the coprime graph of the group of integers modulo and the general formula for the minimum value of the largest label of the labeling. The steps taken in this research are to determine the coprime graph form of the group of integers modulo . Then label each vertex with a non-negative label. Then label each vertex with labeling rule. From the result of this research, it can be concluded that the coprime graph of integer group modulo has a labeling with .

An Overview of Key Technologies for Wireless Charging Systems for Unmanned Aerial Vehicles

With the demand for an intelligent and modernized society, the application of UAVs has become increasingly widespread. However, their performance is limited by battery capacity constraints, making UAV wireless charging an effective solution for prolonging operational time. This thesis focuses on the research of shutdown technology in UAV wireless charging systems. Firstly, it introduces the current research status in this field. It then comprehensively covers the principles of wireless energy transmission, with a particular focus on magnetic coupling resonance. Next, it addresses key issues such as compensation topology mechanisms and coupling coil circuit analysis. Following that, a technical analysis is conducted based on hover charging and landing charging, respectively. Finally, the thesis summarizes the current progress of UAV wireless charging and provides an outlook on areas for improvement in related research.

Wireless Devices for Optical Brain Stimulation: A Review of Current Developments for Optogenetic Applications in Freely Moving Mice

Wireless Devices for Optical Brain Stimulation: A Review of Current Developments for Optogenetic Applications in Freely Moving Mice

Secured and energy efficient cluster based routing in WSN via hybrid optimization model, TICOA

There are two main design issues in Wireless Sensor Network (WSN) routing including energy optimization and security provision. Due to the energy limitations of wireless sensor devices, the problem of high usage of energy must be properly addressed to enhance the network efficiency. Several research works have been addressed to solve the routing issue in WSN with security concerns and network life time enhancement. However, the network overhead and routing traffic are some of the obstacles still not tackled by the existing models. Hence, to enhance the routing performance, a new cluster-based routing model is introduced in this work that includes two phases like Cluster Head (CH) selection and Routing. In the first phase, the hybrid optimization model, Tasmanian Integrated Coot Optimization Algorithm (TICOA) is proposed for selecting the optimal CH under the consideration of constraints like security, Energy, Trust, Delay and Distance. Subsequently, the routing process takes place under the constraints of Trust and Link Quality that ensures the enhancement of the network lifetime of WSN. Finally, simulation results show the performance of the proposed work on cluster-based routing in terms of different performance measures. The conventional systems received lower trust ratings, specifically BOA=0.489, BSA=0.475, GA=0.493, TDO=0.418, COOT=0.439, TSGWO=0.427, and P-WWO=0.408, whereas the trust value of the TICOA technique is 0.683.

Assessing Cell Viability and Genotoxicity in Trigonella foenum-graecum L. Exposed to 2100 MHz and 2300 MHz Electromagnetic Field Radiations

The escalating utilization of wireless electronic devices, notably cellular phones, has led to a substantial augmentation in the levels of electromagnetic field radiation (EMF-r) within the environment. Consequently, an imperative arises to investigate the impact of these radiations on biological systems, specifically on plants. In this study, we examined the genotoxic and cytotoxic effects of 2100 MHz and 2300 MHz EMF-r on the Trigonella foenum-graecum L. test system, evaluating parameters such as percentage germination, growth characteristics, biochemical activities, cell viability and chromosomal aberrations. The roots and shoots of T. foenum-graecum L. were exposed to 2100 MHz and 2300 MHz EMF-r for varied exposure durations (0.5 h, 1 h, 2 h, 4 h and 8 h/day) (at a power density of 10.0 dBm). Substantial reductions in root and shoot lengths were observed after a exposure period of 4 h and 8 h at a frequency of 2100 MHz and 2300 MHz. Genotoxic studies revealed both physiological and clastogenic effects of EMF-r, as evidenced by an increase in chromosomal aberrations (CAs). Biochemical analyses demonstrated elevated malondialdehyde levels and activities of various antioxidative enzymes following 2 h and 4 h per day exposure to 2100 MHz and 2300 MHz EMF-r. Chromosomal aberrations increased by 2.88% to 14.86% and 2.84% to 18.49% (0.5 h to 8 h per day) exposure to 2100 MHz and 2300 MHz, respectively when compared to that of the control group. Exposure to electromagnetic fields (EMF-r) at both 2100 MHz and 2300 MHz resulted in reduced cell viability. This study examines the impact of electromagnetic fields (EMF-r) at 2100 MHz and 2300 MHz on plant root meristems. The results reveal more pronounced genotoxic effects at 2100 MHz, highlighting the frequency-dependent nature of EMF-r impacts. By providing insights into these frequency-specific effects, this research addresses a critical gap in understanding how EMF-r influences plant cellular health and offers guidance for mitigating potential environmental risks from mobile communication technologies.

Intelligent Wireless Charging Path Optimization for Critical Nodes in Internet of Things-Integrated Renewable Sensor Networks.

Wireless sensor networks (WSNs) play a crucial role in the Internet of Things (IoT) for ubiquitous data acquisition and tracking. However, the limited battery life of sensor nodes poses significant challenges to the long-term scalability and sustainability of these networks. Wireless power transfer technology offers a promising solution by enabling the recharging of energy-depleted nodes through a wireless portable charging device (WPCD). While this approach can extend node lifespan, it also introduces the challenge of bottleneck nodes-nodes whose remaining energy falls below a critical value of the threshold. The paper addresses this issue by formulating an optimization problem that aims to identify the optimal traveling path for the WPCD based on ant colony optimization (WPCD-ACO), with a focus on minimizing energy consumption and enhancing network stability. To achieve it, we propose an objective function by incorporating a time-varying z phase that is managed through linear programming to efficiently address the bottleneck nodes. Additionally, a gateway node continually updates the remaining energy levels of all nodes and relays this information to the IoT cloud. Our findings indicate that the outage-optimal distance achieved by WPCD-ACO is 6092 m, compared to 7225 m for the shortest path and 6142 m for Dijkstra's algorithm. Furthermore, the WPCD-ACO minimizes energy consumption to 1.543 KJ, significantly outperforming other methods: single-hop at 4.8643 KJ, GR-Protocol at 3.165 KJ, grid clustering at 2.4839 KJ, and C-SARSA at 2.5869 KJ, respectively. Monte Carlo simulations validate that WPCD-ACO is outshining the existing methods in terms of the network lifetime, stability, survival rate of sensor nodes, and energy consumption.

The utility of wearable electroencephalography combined with behavioral measures to establish a practical multi-domain model for facilitating the diagnosis of young children with attention-deficit/hyperactivity disorder

BackgroundA multi-method, multi-informant approach is crucial for evaluating attention-deficit/hyperactivity disorders (ADHD) in preschool children due to the diagnostic complexities and challenges at this developmental stage. However, most artificial intelligence (AI) studies on the automated detection of ADHD have relied on using a single datatype. This study aims to develop a reliable multimodal AI-detection system to facilitate the diagnosis of ADHD in young children.Methods78 young children were recruited, including 43 diagnosed with ADHD (mean age: 68.07 ± 6.19 months) and 35 with typical development (mean age: 67.40 ± 5.44 months). Machine learning and deep learning methods were adopted to develop three individual predictive models using electroencephalography (EEG) data recorded with a wearable wireless device, scores from the computerized attention assessment via Conners’ Kiddie Continuous Performance Test Second Edition (K-CPT-2), and ratings from ADHD-related symptom scales. Finally, these models were combined to form a single ensemble model.ResultsThe ensemble model achieved an accuracy of 0.974. While individual modality provided the optimal classification with an accuracy rate of 0.909, 0.922, and 0.950 using the ADHD-related symptom rating scale, the K-CPT-2 score, and the EEG measure, respectively. Moreover, the findings suggest that teacher ratings, K-CPT-2 reaction time, and occipital high-frequency EEG band power values are significant features in identifying young children with ADHD.ConclusionsThis study addresses three common issues in ADHD-related AI research: the utility of wearable technologies, integrating databases from diverse ADHD diagnostic instruments, and appropriately interpreting the models. This established multimodal system is potentially reliable and practical for distinguishing ADHD from TD, thus further facilitating the clinical diagnosis of ADHD in preschool young children.

Design and Optimization of Higher Education Online English Teaching Utilizing Wireless Network Technology in the Context of 5G

The global demand for wireless communication networks is a result of the widespread use of wireless devices and the related surge of wireless service providers. Data transmission speed, coverage areas, cost-effectiveness, resource utilization, security, scalability, and adaptability are all elements expected to be improved in future 5G wireless networks. Since this rapid development of network communication technology affects the delivery of English education in tertiary contexts, English teachers in colleges and universities should make use of network resources—especially the communication tools embedded in the 5G network. File transfer protocol can utilize the advanced artificial bee colony optimization algorithm (AABCOA) to realize classification, and the system proposed in this article is simulated and tested in Matrix Laboratory (MATLAB). The research results indicate that students are unsatisfied with traditional methods of English pedagogy in higher education and are keen to explore the new learning possibilities provided by 5G integrated wireless network technology.

Design and implementation of wireless power transfer device

Abstract. Magnetic coupled resonant radio energy transmission (WPT) technology utilizes the coupling of the magnetic fields of the transmitting and receiving coils and wirelessly transmits energy through electromagnetic induction, greatly expanding the applications of power equipment in special environments. The technology uses the magnetic field coupling between the transmitting coil and the receiving coil to realize the wireless transmission of energy through electromagnetic induction. This method breaks the limitation of traditional wire transmission and greatly expands the application potential of power equipment in various special environments. In this paper, an efficient, stable and long-distance wireless charging device is designed and realized. In order to improve transmission efficiency, two-coil configuration with series-series structure is adopted, and its equivalent circuit model is established by circuit theory and Kirchhoff's law. Therefore, a new radio energy transmission device based on single chip microcomputer is designed, including PWM signal generator, level matching circuit, high frequency inverter circuit and other key parts. Expressions for transmission efficiency and output power are derived from equation analysis and power-on experiments performed on a physical device. In addition, the effects of transmission frequency, load impedance and transmission distance on the performance are investigated.