Wireless Data Transmission Technology Research Articles

Advanced IoT-Based Wireless Sensors for Remote Geotechnical Monitoring and Structural Diagnostics

This paper presents an innovative design and implementation of a wireless sensor module using low-power Internet of Things (IoT) technologies for applications in geotechnical engineering and structural diagnostics, with a main focus on monitoring rock formations below the water surface in areas without access to electrical power. Designed for continuous monitoring of linear displacements and other critical parameters in structural engineering, geotechnical engineering and engineering diagnostics, this sensor module is particularly useful in remote locations. Utilizing wireless data transmission and advanced IoT technologies such as LoRa, IQRF and NB-IoT, this system allows for flexible coverage options and efficient remote management. The system allows users to remotely change measurement parameters, the period of messaging and set thresholds for alarm activation. The study highlights the importance of innovative IoT solutions to improve accuracy and efficiency in monitoring geotechnical and civil engineering structures, especially in challenging sub-surface environments, opening new opportunities for predictive maintenance and risk management in these specific applications.

СПОСОБ ПЕРЕДАЧИ ДИАГНОСТИЧЕСКИХ ДАННЫХ О ТЕХНИЧЕСКОМ СОСТОЯНИИ ДВИГАТЕЛЕЙ СЕЛЬСКОХОЗЯЙСТВЕННОЙ ТЕХНИКИ

The article analyzes modern wireless data transmission technologies. Their advantages and disadvantages are revealed. A method for remote transmission of diagnostic data from agricultural machinery engines using Lora technology is proposed. A simplified diagram for transmitting diagnostic data is presented. Laboratory studies of the diagnostic method were performed.

ОРГАНИЗАЦИЯ СИСТЕМЫ УПРАВЛЕНИЯ ОФИСНЫМ ОСВЕЩЕНИЕМ С ВОЗМОЖНОСТЬЮ ТОЧЕЧНОЙ НАСТРОЙКИ

This article describes a specific approach to organizing the artificial light environment of an office space with a common space. The main criteria of modern lighting systems are given, which must be taken into account when designing. It is proposed to create an energy-efficient system with great functionality to integrate a lighting control module into the existing system, which includes LED lamps with built-in microcontrollers. To control the level of illumination and the color spectrum emitted by the LED lighting device in real time, it is proposed to use a portable small-sized sensor. The system for monitoring and controlling lighting parameters is built using Wi-Fi wireless data transmission technology. The control system will make it possible to carry out point individual adjustment, taking into account the specified operating parameters and user requirements.

ENHANCED DIAGNOSTIC TECHNIQUES FOR MARINE DIESEL ENGINES: ACHIEVING IMO DECARBONIZATION COMPLIANCE

This paper discusses hardware-based methods for monitoring the operational parameters of marine diesel engines and online mathematical modeling techniques (digital twins) for calculating the emissions of CO2, NOx, soot, and other harmful pollutants. It is demonstrated that measuring and analyzing the engine's vibrational diagrams in parallel with gas pressure diagrams in the cylinders allows the evaluation of the actual fuel injection and gas distribution timings. The obtained data is used to refine the mathematical model of the engine's working process, which determines the engine's indicator parameters and power, as well as the emission of harmful substances that need to be monitored in compliance with current IMO requirements. The authors have accumulated experience in using the discussed hardware-based methods for diagnosing marine engines during operation. The hardware and software methods discussed have been implemented into a real-time system for in-service diagnostics of marine engines. The system is designed based on a modern dual-core controller with high performance and low power consumption, incorporating a high-speed ADC with sufficient capability to monitor the working process with a 0.1-degree crankshaft rotation resolution for all types of marine main and auxiliary engines. The system also utilizes wireless data transmission technology. A contemporary Android/iOS smartphone or tablet serves as the computational and graphical component of the system. This real-time system enables the utilization of all the advantages of parallel pressure and vibroacoustic analysis, including real-time determination of key operating parameters, identification of top dead center position, and evaluation of fuel delivery and gas distribution phases. Additionally, it harnesses the benefits of employing a digital twin—an online mathematical model of the engine cylinder's working process. These solutions will enhance diagnostic quality and, ultimately, improve the operational efficiency of marine engines by reducing operational costs and extending the period of reliable, trouble-free operation.

Efficient Compressed Sensing Reconstruction Algorithm for Nonnegative Vectors in Wireless Data Transmission

With the rapid development of 5G communication and wireless Internet of Things technology, the application of intelligent wearable devices based on wireless data transmission technology is becoming more and more popular. However, due to the bandwidth of wireless data transmission nodes and the power consumption of the device system, the use time and data storage of wearable devices are severely restricted. The compressed sensing (CS) technology has become an effective method to tackle this problem. CS technology includes data compressive sensing at the transmission end and data reconstruction at the receiving end. In this paper, we consider the reconstruction of nonnegative sparse vectors, an important problem in the area of CS for wireless data transmission. It is known that the interval-passing (IP) algorithm is a low-complexity message-passing type method for the problem. However, the reconstruction performance of the IP algorithm is inferior to that of the other state-of-the-art CS reconstruction algorithms such as the orthogonal matching pursuit (OMP) algorithm. In order to address the problem, we propose a two-stage reconstruction algorithm in this paper. The proposed algorithm applies the IP algorithm for the first stage of reconstruction. If the reconstruction fails, the OMP algorithm is then used on the basis of the results in the first stage. The proposed algorithm is evaluated and compared with other state-of-the-art algorithms by the probability of perfect reconstruction under the given sparsity order value. Simulation results suggest that the proposed two-stage algorithm can greatly improve the reconstruction performance of the IP algorithm and can even outperform the OMP algorithm. In addition, the low-complexity advantages of the IP algorithm are maintained in the proposed algorithm.

Retracted: Visual Communication Design and Wireless Data Transmission Technology for Blockchain Big Data Information Presentation

Retracted: Visual Communication Design and Wireless Data Transmission Technology for Blockchain Big Data Information Presentation

AUTOMATED RESOURCE MANAGEMENT SYSTEM FOR THE UTILITY SECTOR BASED ON WIRELESS SENSOR NETWORKS

The subject of this study is methods, tools and automated resource management systems for the housing and communal sector. The object of research is the process of controlling resource consumption at housing and communal facilities. The aim of the study is to develop an automated resource management system for the utility sector based on wireless sensor networks. To achieve this goal, the following tasks were solved: a review and analysis of existing methods, tools and automated resource management systems; selection of system components based on technical requirements and taking into account the selected LoRaWAN wireless connection technology; development of a structural diagram and algorithm for the operation of an automated resource management system based on wireless sensor networks; modelling of the process of managing the resources of the utility sector using a wireless sensor network based on t The following methods are used in the work: critical analysis of LoRa technology and other wireless IoT technologies, FOREL and -means clustering methods. The following results were obtained: a general description of the automated resource management system was carried out, its composition and main tasks were determined, and technical requirements for it were established, wireless data transmission technology was selected, on the basis of which the automated resource management system was built, an in-depth comparative analysis of the most effective modern wireless technologies – LoRaWAN and NB-IoT – was carried out, system components were selected, a structural diagram and algorithm for the automated resource management system were developed, and the process of the automated resource management system was modelled. Conclusions: the application of the proposed automated resource management system provides high-quality control of energy consumption at the facilities of the housing and communal sector, makes it possible to control their volume, monitor and analyse energy consumption data, and manage the entire energy supply network as a single system, which is especially necessary in martial law. This approachallows rationalising the consumption of resources by household consumers, which means that the financial costs of energy supply will decrease and the level of energy savings in the country will increase.

Study of data and power transmission based on frequency-shift modulation in wireless charging

To ensure the reliability of the Wireless Power Transfer (WPT), the simultaneous wireless power and data transmission technology has gained more attention to realize real-time information exchange between the transmitter and receiver sides. In this paper, the shared channel technology and 2FSK modulation method are proposed to accomplish data and power transmission simultaneously. The theoretical analysis of the series-series compensation network is established, and the data modulation method through frequency-shifted modulation is analyzed. In order to reduce the bit error rate of transmitted data, a communication data format containing start and stop bits is proposed in this proposed system. Finally, an experimental prototype is constructed to validate the correctness and effectiveness of the proposed design and approach.

PELP: Accounting for Missing Data in Neural Time Series by Periodic Estimation of Lost Packets.

Recent advances in wireless data transmission technology have the potential to revolutionize clinical neuroscience. Today sensing-capable electrical stimulators, known as “bidirectional devices”, are used to acquire chronic brain activity from humans in natural environments. However, with wireless transmission come potential failures in data transmission, and not all available devices correctly account for missing data or provide precise timing for when data losses occur. Our inability to precisely reconstruct time-domain neural signals makes it difficult to apply subsequent neural signal processing techniques and analyses. Here, our goal was to accurately reconstruct time-domain neural signals impacted by data loss during wireless transmission. Towards this end, we developed a method termed Periodic Estimation of Lost Packets (PELP). PELP leverages the highly periodic nature of stimulation artifacts to precisely determine when data losses occur. Using simulated stimulation waveforms added to human EEG data, we show that PELP is robust to a range of stimulation waveforms and noise characteristics. Then, we applied PELP to local field potential (LFP) recordings collected using an implantable, bidirectional DBS platform operating at various telemetry bandwidths. By effectively accounting for the timing of missing data, PELP enables the analysis of neural time series data collected via wireless transmission—a prerequisite for better understanding the brain-behavior relationships underlying neurological and psychiatric disorders.

Compression Reconstruction and Fault Diagnosis of Diesel Engine Vibration Signal Based on Optimizing Block Sparse Bayesian Learning.

It is critical to deploy wireless data transmission technologies remotely, in real-time, to monitor the health state of diesel engines dynamically. The usual approach to data compression is to collect data first, then compress it; however, we cannot ensure the correctness and efficiency of the data. Based on sparse Bayesian optimization block learning, this research provides a method for compression reconstruction and fault diagnostics of diesel engine vibration data. This method’s essential contribution is combining compressive sensing technology with fault diagnosis. To achieve a better diagnosis effect, we can effectively improve the wireless transmission efficiency of the vibration signal. First, the dictionary is dynamically updated by learning the dictionary using singular value decomposition to produce the ideal sparse form. Second, a block sparse Bayesian learning boundary optimization approach is utilized to recover structured non-sparse signals rapidly. A detailed assessment index of the data compression effect is created. Finally, the experimental findings reveal that the approach provided in this study outperforms standard compression methods in terms of compression efficiency and accuracy and its ability to produce the desired fault diagnostic effect, proving the usefulness of the proposed method.

Bank Green Credit Risk Assessment and Management by Mobile Computing and Machine Learning Neural Network under the Efficient Wireless Communication

The study is aimed at assessing and managing the green credit risk of banks, reduces the systemic risk in the financial industry, and improves the efficiency of the use of bank funds. With the development and evolution of efficient wireless data communication and transmission technology, the study combines theoretical and empirical green credit analysis to analyze listed companies in different industries quantitatively. The index system of credit risk assessment is established through wireless data transmission technology combined with mobile computing and machine learning neural networks. A back-propagation neural network (BPNN) model is confirmed by principal component analysis and factor analysis, and the performance of the model is verified with example data. The results show that the BPNN-based credit risk assessment model can provide 95% accuracy. In addition, 99% of the sample companies have low risk and no green credit risk. However, most companies in the coal industry are at greater risk. Overall, medium and high-risk companies accounted for 11.5%. Compared with other state-of-the-art models, the machine learning neural network adopted here has better data fitting and prediction accuracy, higher learning efficiency, and higher accuracy. The model established inefficient wireless communication is suitable for bank credit risk assessment and has good reference value and practical significance for bank credit risk assessment and management in different industries.

A Network Communication Frequency Routing Protocol of Coal Mine Safety Monitoring System Based on Wireless Narrowband Data Communication Network

In recent years, the coal industry has been expanding the scale and output of coal mining in China, yet the safety in production is faced with great challenge. Communication system in coal mines plays a significant role in production safety, and wireless narrowband data communication network technology is a new-type advantageous measure to construct wireless network security monitoring system for coal mining. Here, a coal mine monitoring signal transmission method based on bus technology and wireless data transmission technology suitable for coal mines is proposed. The corresponding monitoring system is designed, and the system is able to collect the gas concentration and mechanical operation status of the mines. Wireless sensor network nodes are used for the RF communication module. The communication performance of this system in coal and rock medium and the roadway along the goaf is simulated, and the quantitative relationship between the attenuation coefficient of different communication frequencies and the effective communication distance is obtained. Hence, the results show that the protocol has good performance in terms of route establishment, maintenance, and data transmission hop count for the positioning of coal mine employees.

Development and Implementation of Smart Water Metering System based on Lora Technology

The article presents an overview of traditional water meters in Vietnam, digitizing metrology technologies and wireless data transmission technology for data collection and user applications in smart water metering systems. After that, it is proposed to design a smart wireless water meter module. This paper focuses on designing and implementing a smart water meter to re-use traditional mechanical water meters by designing a smart water metering module attached to the existing meter. This way, it eliminates the costs of investing in flow water meter and influences the old water meter infrastructure system. The contribution of this paper is threefold: (i) Firstly, it proposes wireless data transmission and digitizing metrology technologies suitable for water metering systems in Viet Nam. (ii) Secondly, the proposed smart water meter module designs include hardware, firmwave, and plastic cover. There are two experimental prototypes of the module is introduced in this paper (iii) Lastly, The paper provides a water metering management software model for smart cities. And the overall systems of the proposed platform were built to verify the presented design. To reduce the amount of water leaking or users hacking from outside the meter in the measurement results, the article proposes to design features to alert about: abnormal flow, strong magnetic field influence, and equipment cover being removed. The experimental verification was designed with the Actaris water meter using Hall technology to digitize data and the Itron water meter with digitizing technology using the LC sensor. Besides, the Lora wireless network system is proposed and deployed to verify the water metering management with the advantages of low energy consumption, high security, and strict authentication process. Actual results for the laboratory environment and residential areas show that signal loss (RSSI) and signal noise (SNR) is within the allowable range. In addition, the packet loss rate <1% and average power consumption meter <50uA. Water metering management software is presented to verify the smart city service system.

Control of parameters of electrochemical protection of gas distribution systems against corrosion using wireless data transmission technology of short range

Control of parameters of electrochemical protection of gas distribution systems against corrosion using wireless data transmission technology of short range

Recent Advances in Bioinspired Hydrogels: Materials, Devices, and Biosignal Computing.

The remarkable ability of biological systems to sense and adapt to complex environmental conditions has inspired new materials and novel designs for next-generation wearable devices. Hydrogels are being intensively investigated for their versatile functions in wearable devices due to their superior softness, biocompatibility, and rapid stimulus response. This review focuses on recent strategies for developing bioinspired hydrogel wearable devices that can accommodate mechanical strain and integrate seamlessly with biological systems. We will provide an overview of different types of bioinspired hydrogels tailored for wearable devices. Next, we will discuss the recent progress of bioinspired hydrogel wearable devices such as electronic skin and smart contact lenses. Also, we will comprehensively summarize biosignal readout methods for hydrogel wearable devices as well as advances in powering and wireless data transmission technologies. Finally, current challenges facing these wearable devices are discussed, and future directions are proposed.

Research on hand key point recognition and localization method based on SSD network

With the development of the times and the progress of society, multimedia presentation has become a necessary skill for people. In the field of education, the application of multimedia presentations for teaching activities has become a necessary and common way. In this paper, we propose to use camera capture for image analysis and wireless data transmission technology for information interaction with computers. Among them, SwiftShow performs image analysis by capturing the gestures of the presenter using the camera. The device provides personalization, and users can choose the mode that suits them through the interaction interface, and even customize the gestures. The device can be controlled by the simple hand gesture recognition overhead, which not only can realize the basic functions such as ppt play, pause, page turn, and focus, but also includes many practical and unique presentation functions, the research aims to completely free the presenter from the computer.

Monitoring System for Railway Automation Devices Based on the Industrial Internet of Things

The features of monitoring systems for railway infrastructure and rolling stock are considered. The main approaches to organisation of monitoring of railway infrastructure and rolling stock objects are described, their advantages and disadvantages are noted. The main objective of this work is to present to the reader a conceptual vision of a system for monitoring devices and systems for ensuring train traffic safety, using technologies for transmitting diagnostic information over a radio channel. The methods of the theory of technical diagnostics and monitoring were used. Attention is focused on the use of wireless data transmission technologies and the use of autonomous industrial automation sensors for monitoring systems for railway automation devices.The architecture of the monitoring system is presented. The description of the system itself and the monitoring technology is given, the main advantages of the presented approach are noted, which, first, are linked to reduction of the volume of design work and of energy consumption of the system as a whole. The disadvantages are associated with the need to replace autonomous power supply sources, ensure security of the data transmission network, to proceed with periodic verification and calibration of measuring instruments. The basic diagrams of connecting sensors for measuring physical quantities to the circuit units of railway automation are presented. A list of parameters necessary for high-quality and effective monitoring of railway automation devices is given. The need is noted for both the control of mechanical and geometric parameters of devices and the accounting of data from interconnected objects of railway infrastructure and rolling stock. The proposed approach can find its application in the field of railway automation and, first of all, at those facilities that are located in premises with limited area (e.g. at subway facilities).

Artificial intelligence-powered remote monitoring of patients with chronic obstructive pulmonary disease.

Artificial intelligence-powered remote monitoring of patients with chronic obstructive pulmonary disease.

DLM technique for QoS improvement in MANETS

Wireless networks are used extensively in communication technologies. From Tesla to date researchers, many are working on wireless data transmission techniques and technologies. Despite the immense progressions over the past decade, there are precise hurdles that the industry endures to face. Bandwidth restrictions, latency problems, and device compatibility issues prevent the viewer from meeting seamless data transmissions. Many devices used for communication are used with the wireless interface and are proficient in transmitting data efficiently to the communication range. The growth in data communication requirements increases the network traffic and results in a network bottleneck. There are more challenges for Mobile Ad hoc Networks (MANETs) due to the additional overhead of resource constraints. Congestion leads to depletion of the node's energy, deterioration of network performance, and increased network latency and packet loss. As a result, energy-efficient and reliable state-of-the-art congestion control protocols must be designed to detect, notify and control congestion effectively. To minimize the packet loss in MANETs using Transmission Control Protocol (TCP), we proposed a data loss minimization technique (DLMT). Results show that enhanced DLMT outperforms by 18% compared to state-of-the-art proven congestion control mechanisms. DLMT improves the Quality of Service (QoS) constraints and improves performance by reducing the delay in better throughput, which can be seen by analyzing experimental results. The proposed coordination process's scalability and robustness are shown in good agreement with simulation results and analytic results for the stochastic model.

Performance enhancement of ultra-dense WDM over FSO hybrid optical link by incorporating MIMO technique

Abstract Free-space optical (FSO) communication is a wireless optical data transmission technology with a high data transmission rate. It has received much attention in recent years as it is cost-effective and has license free operation. It is line of sight free-space communication technique where optical signal severely degraded from atmospheric losses especially due to weather conditions; hence it restricts the link range and data carrying capacity. Therefore, a 16-channel ultra-dense wavelength division multiplexing–free space optics (UWDM–FSO) system each having each 10 Gb/s data rate is proposed to enhance the capacity and performance of FSO system. To authenticate the performance of the proposed system, investigation for different modulation formats such as nonreturn to zero (NRZ), return to zero (RZ), carrier suppressed return to zero (CSRZ) and duo binary (DB) are reported. Further, to reduce the atmospheric interference, multiple input multiple output (MIMO) technique is integrated into the proposed system. The outcomes of MIMO–UWDM–FSO link revealed a significant improvement in the bit error rate (BER), eye diagram and Q-factor, under different weather conditions. It is also observed that NRZ modulation formats perform better than RZ, CSRZ and DB formats.