Wireless Module Research Articles

Research on marine oil spill identification based on laser-induced fluorescence LiDAR

The rise in oil extraction and transportation in marine environments has led to frequent oil spill incidents, posing a severe threat to marine ecosystems and becoming an urgent environmental issue. This paper presents a laser-induced fluorescence light detection and ranging (LiDAR) system specifically designed for monitoring marine oil spills. The system comprises a laser emission module, a receiving module, a data processing module, and a wireless transmission module. Through outdoor experiments, the system has demonstrated its effectiveness and reliability in detecting and identifying various oil types, including crude oil, diesel, heavy oil, gasoline, and lubricating oil. Additionally, a BP neural network model was employed to process the fluorescence spectral data collected by the LiDAR system. This model successfully predicted oil types with an accuracy of 96.58%. This research presents a new technological solution for marine oil spill monitoring, offering significant potential for practical applications and further research.

AUTOMATIC SPRINKLER SYSTEM USING ARDUINO

This report investigates the implementation and benefits of an Automatic Sprinkler System driven by the Arduino Uno microcontroller in agricultural irrigation. The primary aim is to elucidate the functionality and practicality of this automated system in enhancing water efficiency and crop productivity. Through accessible language and technical explanations, the report explores the system's design, operation, and integration with sensors for optimal performance. Emphasis is placed on the system's ability to provide precise watering, customizable scheduling, and water conservation, thereby addressing critical challenges in modern agriculture. By examining the technical aspects and real-world implications, this report underscores the transformative potential of automated irrigation systems in promoting sustainable farming practices.. Keyword: Arduino Uno, IoT, microcontroller, moisture sensor, sensors, wireless module

Three-Dimensional Electrodes of Liquid Metals for Long-Term, Wireless Cardiac Analysis and Modulation.

Cardiovascular disease is a major public health issue, and smart diagnostic approaches play an important role in the analysis of electrocardiograms. Here, we present three-dimensional, soft electrodes of liquid metals that can be conformably attached to the surfaces of the heart and skin for long-term cardiac analysis. The fine micropillar structures of biocompatible liquid metals enable precise targeting to small tissue areas, allowing for spatiotemporal mapping and modulation of cardiac electrical activity with high resolution. The low mechanical modulus of these liquid-metal electrodes not only helps avoid inflammatory responses triggered by modulus mismatch between the tissue and electrodes, but also minimizes pain when embedded in biological tissues such as the skin and heart. Furthermore, in vivo experiments with animal models and human trials demonstrate long-term and accurate monitoring of electrocardiograms over a period of 30 days.

The Application of GPS-Based Friend/Foe Localization and Identification to Enhance Security in Restricted Areas.

This paper is devoted to the application of object localization and identification with information combined from a radar system and a dedicated portable/mobile electronic device equipped with a global positioning system (GPS) receiver. This device is able to provide object's (staff member, and staff vehicle) rough location and identification. Such systems are required in very restrictive security areas like airports (e.g., open-air area and apron). Currently, the outdoor area of the airport is typically protected by a surveillance system operated by security guards. Surveillance systems are composed of different sensors, video and infrared cameras, and microwave radars. The sheer number of events generated via the system can lead to fatigue among staff, potentially resulting in the omission of critical events. To address this issue, we propose an electronic system equipped with a wireless module and a GPS module. This approach enables automatic identification of objects through the fusion of data from two independent systems (GPS and radar). The radar system is capable of precisely localizing and tracking objects, while the described system is able to identify registered objects. This paper contains a description of the subsystems of a portable/mobile electronic device. The fusion of information from the proposed system (rough location and identification) with the precise location obtained from short-range radar is intended to reduce the number of false alerts in the surveillance system.

A pragmatic data processing system for large resistive sensor arrays.

Large resistive sensor arrays (RSAs) show great potential in tactile perception. However, the large number of sensors can result in great hardware overhead and bring difficulties for acquiring and processing mass data timely in transient measurement applications. This paper implements a field programmable gate array (FPGA)-based data processing system for a large RSA of 96 × 96, which shows good power consumption and high-speed wireless data update. For crosstalk-free measure, the zero potential method is improved with bus switches, leading to fewer operational amplifiers required and less negative power consumption. A real-time embedded data processing system is realized by FPGA for excellent parallel processing ability. A high-speed wireless transfer scheme with automatic regulated transfer size is proposed and realized by a wireless fidelity module, which allows timely data analysis at the remote end. Moreover, fault identification of RSAs fabricated by micro-electromechanical system technology is achieved. Tests carried out on a 32 × 32 RSA show that the total power consumption is 2209 mW, including 1261 mW of processors and 948 mW of readout circuits, corresponding to 2.15 mW/pixel. The total negative power consumption of 549 mW has been reduced by 50% compared with the zero potential method. The scanning speed is 400fps, and the wireless transfer speed is up to 120fps when the transceiver and receiver are 5m apart.

Implantable Zinc Ion Battery and Osteogenesis-Immunoregulation Bifunction of Its Catabolite.

Biocompatible batteries can power implantable electronic devices and have broad applications in medicine. However, the controlled degradation of implantable batteries, the impact of battery catabolites on surrounding tissues, and wireless charging designs are often overlooked. Here, we designed an implantable zinc ion battery (ZIB) using a gelatin/polycaprolactone-based composite gel electrolyte. The prepared ZIBs deliver a high specific capacity of 244.0 mA h g-1 (0.5C) and long cycling stability of 300 cycles (4C). ZIBs were completely degraded within 8 weeks in rats and 30 days in a phosphate-buffered saline lipase solution, demonstrating good biocompatibility and degradability. ZIBs catabolites induced macrophage M2 polarization and exhibited anti-inflammatory properties, with mRNA levels of the M2 markers Arg-1 and CD206 up-regulated 15.8-fold and 13.4-fold, respectively, compared to the blank control group. Meanwhile, the expressions of two typical osteogenic markers, osteopontin and osteocalcin, were up-regulated by 3.6-fold and 5.6-fold, respectively, demonstrating that designed ZIBs promoted osteogenic differentiation of bone marrow mesenchymal stem cells. Additionally, a wireless energy transmission module was designed using 3D printing technology to realize real-time charging of the ZIB in rats. The designed ZIB is a promising power source for implantable medical electronic devices and also serves as a functional material to accelerate bone repair.

Use of wireless technologies in IoT projects

When it comes to creating projects based on the use of the Internet of Things (IoT), wireless sensor networks are often used. Edge computing in IoT technology reduces system response delays to sensor output signals and increases the network throughput. At the same time, a short-range sensor network can work locally without access to the Internet, while long-range networks, as a rule, require access to the Internet and use both edge and cloud computing. The paper shows the features of the application of both peripheral and cloud computing in the practical implementation of IoT projects with various methods of wireless data transmission. Specific examples show the possibility of data transmission over a short distance using ESP-NOW technology, nRF24L01 radio modules and creating a local Wi-Fi access point. The range of sensor data transmission between microcontrollers is practically determined for each proposed option. The calculation of the range of the LoRa radio line is carried out for the actual sensitivity values of the receiver. The Okamura-Hata radio wave propagation model is proposed to estimate the LoRa radio line’s total loss. The operational range of LoRa modules with different types of signal modulation is practically determined. The essence of edge computing combined with digital and analogue sensors is shown. Peculiarities of peripheral computing during the implementation of IoT projects for remote control of blood saturation of patients using wireless technologies are considered. An example of data transmission of the air quality control system through a gateway based on an ESP8266 microcontroller with a graphical display of measurements in the IoT cloud service ThingSpeak and Blynk was provided.

Innovative wireless ocular modulation patch for controlled axial length shortening

Innovative wireless ocular modulation patch for controlled axial length shortening

Radio Signal Modulation Recognition Method Based on Hybrid Feature and Ensemble Learning: For Radar and Jamming Signals.

The detection performance of radar is significantly impaired by active jamming and mutual interference from other radars. This paper proposes a radio signal modulation recognition method to accurately recognize these signals, which helps in the jamming cancellation decisions. Based on the ensemble learning stacking algorithm improved by meta-feature enhancement, the proposed method adopts random forests, K-nearest neighbors, and Gaussian naive Bayes as the base-learners, with logistic regression serving as the meta-learner. It takes the multi-domain features of signals as input, which include time-domain features including fuzzy entropy, slope entropy, and Hjorth parameters; frequency-domain features, including spectral entropy; and fractal-domain features, including fractal dimension. The simulation experiment, including seven common signal types of radar and active jamming, was performed for the effectiveness validation and performance evaluation. Results proved the proposed method's performance superiority to other classification methods, as well as its ability to meet the requirements of low signal-to-noise ratio and few-shot learning.

Three-Coil Wireless Charging System Based on S-PS Topology

To protect the battery, radio energy transmission charging typically uses constant current (CC) charging before switching to constant voltage (CV) charging to enhance battery durability. This paper proposes adding an auxiliary clamp coil to the original circuit topology. The IPT battery charger designed with the auxiliary clamp coil can achieve both constant current (CC) and constant voltage (CV) outputs. The mutual inductance between the auxiliary clamp coil and the primary side coil greatly influences the output performance of the entire IPT system, so the auxiliary clamp coil should not be too large. To solve this problem, an S-S-PS circuit with secondary compensation topology in the secondary coil is proposed. This circuit topology reduces the size of the auxiliary clamp coil, allowing it to be placed in an optimal position. When the constant voltage output critical position is reached, the IPT system can still automatically, continuously, and smoothly switch between CC and CV modes. Consequently, this approach avoids increased cost consumption associated with detecting CC-CV switching thresholds, adding wireless transmission communication modules, real-time control of the power transmitter, and active protection of the circuit during constant current charging. Finally, a 48 V/2.5 A prototype was built to verify that the IPT system has CC-CV conversion functionality.

A Visible-Light-Driven Self-Powered Nodularin-R Biosensing Platform Controlled by an Integrated Portable Photoelectrochemical Detection Device.

The presence of nodularin-R (NOD-R) in water has gained considerable attention because of its widespread distribution and high toxicity. In this study, an accurate and rapid visible-light-driven self-powered photoelectrochemical (PEC) biosensor was developed by integrating a portable paper-based electrode with a custom-built miniaturized PEC detection device. The newly designed system successfully achieved on-site detection of NOD-R in real water samples based on PEC technology. First, target recognition triggers the initiation of the hybridization chain reaction to generate double-stranded DNA. The thus-formed double-stranded DNA entrapped methylene blue (MB), and the dye molecules were irradiated with visible light for conversion to leuco-MB in the presence of ascorbic acid. The resulting leuco-MB species significantly amplified the PEC signal output of TiO2-MXene, enabling NOD-R detection. Under optimal conditions, the proposed PEC assay strategy demonstrated NOD-R detection within a concentration range from 20 fg mL-1 to 10 ng mL-1 with a detection limit of 19.6 fg mL-1. In addition, a custom-built miniaturized PEC detection device conveniently integrates the detection component with the light source, enabling the real-time collection of results via a wireless module. This innovative self-powered PEC platform provides significant advancements in smooth and intelligent detection compared to traditional PEC detection devices.

Embedded System Based on Task Interval Data Interaction Model

In the Internet of Things era, more intelligent systems can communicate with each other. Embedded system combined with network communication applications has become the basis for Internet of Things research. The programmable logic unit designed by ARM architecture has great advantages in running speed, power control and so on. In the paper, to solve the problems of common embedded MCU control resources occupying a large amount of memory and the slow speed of building engineering simulation model, it is necessary to use the queuing connection algorithm model to directly input the timing physical characteristics of the code stream in the embedded system to calculate and match the timing physical characteristics of the output code stream. The optimization algorithm of DTF-MARTE to detect the probability of timing deviation is used in the paper. It is to detect the problem of inaccurate timing information in the demand. We compare the expected physical characteristics of the timing sequence and obtain the timing deviation probability of the output data stream. The model developed in this paper has the characteristic of dynamic reconfiguration of the task interval. The design of monotonically decreasing data tasks can be realized, and the reconfigured task modules are used for interacting the data buffer area and dynamically reconstructing the instruction overhead and transmission. We analyze the performance comparison between the proposed model and the traditional communication connection model. It proves that the proposed model can further improve the priority queue and guide the data flow. According to that method, the problem of asynchronous spatial data interaction by controlling and combining different communication modes in a large scene can be solved. Data interaction can be triggered at a fixed time, and mutual interference of randomly triggered wireless communication and data acquisition modules can be avoided. It can solve the problem of insufficient computing power when future embedded devices need massive data encryption in the Internet of Things era, and provide a new way of thinking for fast, safe and efficient implementation.

One Meter Triboelectric Nanogenerator for Efficient Harvesting of Meter‐Scale Wave Energy

AbstractTriboelectric nanogenerators (TENGs) are effective in harvesting high‐entropy low‐frequency wave energy, yet traditional TENGs struggle to align with the meter‐scale wavelengths prevalent in marine environments, significantly impairing their wave energy conversion efficiency. Addressing this, the One Meter TENG (OM‐TENG) is introduced, a pioneering advancement in TENG design that extends the shell size to 1 m. This innovation features a novel lantern‐shaped stacked silicon‐manganese steel sheet configuration, optimizing internal space usage, and achieving a single‐cycle transfer charge of 60.82 µC and a friction layer area density of 1.76 cm−1. Furthermore, by integrating a segmented limiter device for rational control of different sliders, effective contact separation among numerous TENG units is realized. Comprehensive evaluations through theoretical analysis, multiphysics field numerical simulations, sensor data analytics, and comparative experimental measurements have unequivocally demonstrated OM‐TENG's superior capability in capturing meter‐scale wave energy under actual environmental conditions, alongside its remarkable anti‐capsize performance. Achieving peak outputs of 584 V and 444 µA, OM‐TENG can power 96 2 W LEDs and drive wireless communication modules, marking a significant step forward in the efficient utilization of wave energy and the design of large‐scale TENGs.

A Straightforward Solvent-Pair-Enabled Multicomponent Coassembly Approach toward Noble-Metal-Nanoparticle-Decorated Mesoporous Tungsten Oxide for Trace Ammonia Sensing.

The straightforward synthesis of noble-metal-nanoparticle-decorated ordered mesoporous transition metal oxides remains a great challenge due to the difficulty of balancing the interactions between precursors and templates. Herein, a solvent-pair-enabled multicomponent coassembly (SPEMC) strategy is developed for straightforward synthesis of noble-metal-nanoparticle-decorated nitrogen-doped ordered mesoporous tungsten oxide (abbreviated as NM/N-mWO3, NM=Pt, Rh, Pd). The amphiphilic poly(ethylene oxide)-block-polystyrene (PEO-b-PS) copolymers coassemble with ammonium metatungstate (AMT) clusters and different kinds of hydrophilic noble metal precursors without phase separation. SPEMC synthesis requires no direct interaction between PEO-b-PS and AMT, thus the assembly equilibriums between noble metal precursors and PEO-b-PS can be readily controlled. The obtained NM/N-mWO3 nanocomposites possess ordered mesopores, abundant oxygen vacancies, and metal-metal oxide interfaces. As a result, the Pt/N-mWO3 sensors exhibit superior ammonia sensing performances with high sensitivity, an ultralow limit of detection (51.2 ppb), good selectivity, and long-term stability. Spectroscopic analysis reveals that ammonia is oxidized stepwise to NO, NO2 -, and NO3 - during the sensing process. Moreover, a portable wireless module based on Pt/N-mWO3 sensor can recognize ppm-level concentration of ammonia, which lays a solid foundation for its application in various fields.

Autonomous UAV Safety Oriented Situation Monitoring and Evaluation System

In this paper, a LabVIEW-based online monitoring and safety evaluation system for UAVs is designed to address the deficiencies in UAV flight state parameter monitoring and safety evaluation. The system consists of a lower unit for UAV recording and an upper unit on the ground. The lower unit collects and detects flight data and connects to the upper unit through a wireless digital transmission module via a serial port. The upper unit receives the data and carries out the monitoring and safety situation evaluation of the UAV. The lower unit of the system adopts multi-sensors to collect UAV navigation information in real time to achieve flight detection, while the upper unit adopts LabVIEW to design the UAV online monitoring and safety situation prediction system, enabling monitoring and safety situation prediction during UAV navigation. The test results show that the system can detect and comprehensively display the navigation information of the UAV in real time, and realize the safety evaluation and warning function of the UAV.

In vivo magnetogenetics for cell-type-specific targeting and modulation of brain circuits.

Neuromodulation technologies are crucial for investigating neuronal connectivity and brain function. Magnetic neuromodulation offers wireless and remote deep brain stimulations that are lacking in optogenetic- and wired-electrode-based tools. However, due to the limited understanding of working principles and poorly designed magnetic operating systems, earlier magnetic approaches have yet to be utilized. Furthermore, despite its importance in neuroscience research, cell-type-specific magnetic neuromodulation has remained elusive. Here we present a nanomaterials-based magnetogenetic toolbox, in conjunction with Cre-loxP technology, to selectively activate genetically encoded Piezo1 ion channels in targeted neuronal populations via torque generated by the nanomagnetic actuators in vitro and in vivo. We demonstrate this cell-type-targeting magnetic approach for remote and spatiotemporal precise control of deep brain neural activity in multiple behavioural models, such as bidirectional feeding control, long-term neuromodulation for weight control in obese mice and wireless modulation of social behaviours in multiple mice in the same physical space. Our study demonstrates the potential of cell-type-specific magnetogenetics as an effective and reliable research tool for life sciences, especially in wireless, long-term and freely behaving animals.

Fuzzy Logic Controller-based Intelligent Irrigation System Using Solar Radiation Data

Solar radiation is a critical factor influencing agricultural productivity and water resource management. Irrigation systems play a pivotal role in maintaining crop health and yield, and optimizing their operation requires accurate solar radiation data. This abstract explores the significance of solar radiation data in enhancing the efficiency of irrigation systems. Irrigating agricultural fields using an intelligent information system plays a crucial role. This study introduces an irrigation control system employing closed-loop control to use the available water resources efficiently. Continuous data collection from field sensors was done and transmitted to a central station in wireless mode. The data was then retrieved and processed in a computer-based or microcontroller-based solution model, enhancing system autonomy, reliability, and cost-effectiveness. Weather conditions are translated into fuzzy set values. The pump, water outlet valves, and sprinklers are set into motion according to control commands. This research simplifies the need for manual labor and reduces water wastage.

Studies of the influence of the degradation of the capacitances of an inductively coupled oscillator circuit on the characteristics of the wireless power supply module of an implantable spinal cord stimulator

Studies of the influence of the degradation of the capacitances of an inductively coupled oscillator circuit on the characteristics of the wireless power supply module of an implantable spinal cord stimulator

Sticker-Type Remote Monitoring System for Early Risk Detection of Catheter Associated Urinary Tract Infections.

A substantial number of critically ill patients in intensive care units (ICUs) rely on indwelling urinary catheters (IDCs), demanding regular monitoring of urine bags. This process increases the workload for healthcare providers and elevates the risk of exposure to contagious diseases. Moreover, IDCs are a primary cause of catheter-associated urinary tract infections (UTIs) in ICU patients whose delayed detection can have life-threatening complications. To address this, we have developed a Sticker Type Antenna for Remote Sensing (STARS) system capable of measuring urine flow rate and conductivity as early-risk markers for UTIs, alongside tracking patients' urine bag status to facilitate medical automation for healthcare providers. STARS comprises a simple, low-cost, disposable antenna module for contactless measurements of urine volume and conductivity, and a reusable wireless module for real-time data transmission. Systematic studies on STARS revealed its stable performance within physiologically relevant ranges of urine volume (0 to 2000 ml) and conductivity (5 to 40 mS/cm) in urine bags. As a proof-of-concept, STARS was tested in artificially created healthy and infected urine specimens to validate its non-contact sensing performance in detecting the onset of UTIs in catheterized patients within a hospital-like environment. STARS represents the first application of a real-time, contactless, wireless monitoring platform for simultaneous urine bag management and early risk detection of UTIs.

Smart Helmet for Motorcycle Safety Internet of Things Based

IoT (Internet of Things) is a concept that aims to utilize continuously connected internet connectivity, there are several IoT capabilities including data sharing, remote control and so on. One use that can be used is for security purposes, such as for safety riding , namely a Smart Helmet. The emergence of cases of motorbike theft and robbery requires vehicle owners to be more careful and increase their vigilance. Much has been done to prevent motorbike theft and robbery, for example using multiple locks and installing alarms on vehicles, but unfortunately some of these methods cannot completely overcome the rampant theft and robbery that is currently occurring. Apart from that, awareness among motorcyclists regarding the use of helmets is currently very minimal, which will have a fatal impact if the rider is involved in a high-profile accident without wearing a helmet. This thesis proposes a solution by developing a smart helmet, namely by providing facilities and equipment to anticipate crime while driving. Apart from that, this smart helmet will send a message if a robbery occurs and immediately send the driver's position. This helmet is integrated with the motorbike engine so the motorbike engine will stop if it is far from the helmet and the motorbike will not start if the helmet is not used. This Smart Helmet is designed based on IoT by using a Wireless module to connect to the motorbike engine, a GSM module for the alarm and notification system, and a GPS module to determine the location which is integrated with Google Maps.