Wireless Communication Module Research Articles

Design and Development of Fire Extinguisher Action Robot

The project titled "Design and Development of Fire Fighting Robot" presents the creation of a robotic system aimed at assisting in firefighting operations. This robot is equipped with various sensors and modules to effectively detect and combat fires remotely. The key components utilized in this project include a camera module, an ESP module for wireless communication, and ultrasonic sensors for environment sensing

A multi-directional magnetic-driven multifunctional soft crawling robot

Multifunctional and multi-freedom integrated magnetic-driven soft robots have received widespread attention in the past decade. However, the current magnetic-driven soft crawling robots with multiple functional modules focus on the development of new materials or innovation of driving component. Herein, we propose a soft crawling robot that materializes multi-directional motion driven only through a unidirectional magnetic field (MF) while possessing the ability to communication, loading, and positioning. The locomotion of robot relies on ingenious leg design to generate differences in friction between each leg and the ground by controlling the MF intensity. The integrated wireless communication modules on the robot's legs serve as a medium for interacting with the external world, enabling the robot to effectively perceive the environment via electromagnetic coupling. In addition, the magnetic-driven soft crawling robot carries loads (3.37 g) larger than twice its own weight for motion. Overall, this work showcases a new paradigm for robot applications, providing a practicable idea for developing miniaturization, multi-directional soft crawling robots.

IoT CONTROLLED LED NOTICE BOARD

The IoT Controlled LED sign board design represents a slice- edge bid aimed at revolutionizing display results for a multitude of purposes including advertising, information dispersion, and aesthetic improvement. At its core, the sign board features an intricate array of LEDs strictly arranged in a grid pattern, each strictly orchestrated by a central microcontroller unit( MCU) harmoniously integrated with a Bluetooth module for flawless wireless communication. This community enables druggies to apply their smartphones or any Bluetooth- enabled bias as important remote controls, decreeing the content showcased on the LED board with unknown ease and perfection. Through a devoted mobile operation, druggies gain a gateway to a realm of creative expression, empowered to transmit a myriad of content types ranging from brief textbook dispatches to witching, robustness and images for immediate display. specially, the system's hallmark lies in its capability to grease real- time content operation, preventing the need for physical intervention and fostering dynamic rigidity to evolving demands and scripts. likewise, the mobile operation's robust point set extends beyond bare content transmission, offering sophisticated tools for communication scheduling and contemporaneous operation of multiple sign boards, thereby accelerating scalability and usability across different surroundings similar as bustling retail spaces, bulging transportation capitals, and bustling public spaces likewise. With its intimately designed interface and multifaceted functionality, the IoT Controlled LED sign board design emerges as a lamp of invention, promising to review the veritably geography of information dispersion and visual communication in the digital age. KEYWORDS: IoT Controlled LED subscribe Board, Microcontroller Unit( MCU), Wireless Communication, Mobile Application, Management, Remote Control.

Wearable Piezoelectric Sensors Based on BaTiO3 Films for Sarcopenia Recognition

AbstractSarcopenia recognition is very crucial in the early diagnosis of sarcopenia. However, the commonly used screening methods are limited by real‐time property, portability, and convenient usability at home. Herein, an electrospun BaTiO3 film is proposed and a piezoelectric sensor with silver electrodes and polyimide substrates is fabricated. The sensor exhibits high piezoelectricity (74.2 pC N−1), sensitivity, linearity, low detection limit (0.2 mN), and significant bending ability (bending angle can exceed 90°), maintaining stable output after more than 20 000 cycles during a week. Due to its excellent performance, the piezoelectric sensor to the recognition of sarcopenia is applied and a wearable system to collect piezoelectric signals from the lower limb movements of the elderly is developed. By selecting features from these signals, eight kinds of machine learning models are employed and their performances in recognizing sarcopenia are compared in both male and female groups. The results indicate that the artificial neural network (ANN) model has the highest performance, with accuracies of 92.9% in males and 98.1% in females. This piezoelectric sensor, combined with a wireless communication module, is expected to provide crucial evidence for sarcopenia detection, offering a new, convenient, and household screening solution for early diagnosis and prevention of sarcopenia.

Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications.

Smart biosensors attract significant interest due to real-time monitoring of user health status, where bioanalytical electronic devices designed to detect various activities and biomarkers in the human body have potential applications in physical sign monitoring and health care. Bioelectronics can be well integrated by output signals with wireless communication modules for transferring data to portable devices used as smart biosensors in performing real-time diagnosis and analysis. In this review, the scientific keys of biosensing devices and the current trends in the field of smart biosensors, (functional materials, technological approaches, sensing mechanisms, main roles, potential applications and challenges in health monitoring)will be summarized. Recent advances in the design and manufacturing of bioanalytical sensors with smarter capabilities and enhanced reliability indicate a forthcoming expansion of these smart devices from laboratory to clinical analysis. Therefore, a general description of functional materials and technological approaches used in bioelectronics will be presented after the sections of scientific keys to bioanalytical sensors. A careful introduction to the established systems of smart monitoring and prediction analysis using bioelectronics, regarding the integration of machine-learning-based basic algorithms, will be discussed. Afterward, applications and challenges in development using these smart bioelectronics in biological, clinical, and medical diagnostics will also be analyzed. Finally, the review will conclude with outlooks of smart biosensing devices assisted by machine learning algorithms, wireless communications, or smartphone-based systems on current trends and challenges for future works in wearable health monitoring.

UNJUK KERJA KOMUNIKASI NIRKABEL HALF-DUPLEX ANTARKENDARAAN MEMANFAATKAN NRF24L01

This study investigates the efficacy of the affordable NRF24L01 wireless communication module in half-duplex mode for vehicle-to-vehicle (V2V) communication. The prototype integrated the NRF24L01 module with an ESP32 microcontroller and an OLED display. The study assesses the delay and packet success rate to uncover the module's attributes under half-duplex situations. This not only surpasses the mere collecting of data, but also emphasizes the practical limitations and strengths of the module. The project aims to achieve two main objectives: firstly, to gather empirical data that may be used to make well-informed decisions in the design of NRF24L01 applications, and secondly, to contribute to the broader examination of wireless communications protocols. It improves comprehension of the impact of half-duplex operation on the performance of the NRF24L01 module. By revealing the mechanics of half-duplex communication, it enhances the efficiency of NRF24L01 usage and facilitates the development of a better protocol.

Design and Implementation of Smart Blind Stick for Obstacle Detection and Navigation System

The design, advancement, and evaluation of an IoT -enabled smart stick that can detect and alert users to obstacles is presented in this study to help visually impaired persons traverse the outside world. A water sensor deployed to identify puddles and other wet surfaces in the user's route, and ultrasonic sensors for detecting obstacles are all used in the suggested design. Additionally, after correctly detecting and recognising items, the user receives voice feedback through earphones regarding various obstacles and objects. The suggested smart stick has two modes: the first detects and recognises obstacles and provides speech feedback; the second mode employs ultrasonic sensors for detecting and response through vibration motors to inform about the direction of the obstacle. The suggested method enables users to alternate between the two modes based on their preferences and the surroundings. Additionally, the user's latitude and longitude values are recorded and uploaded to the IoT platform for efficient tracking through global system for wireless communication modules, allowing the user or device to be tracked in real time on the dashboard. An IoT-enabled environment generates an alert signal in the form of an SMS with Google Maps link generated using latitude and longitude coordinates, and this serves as a panic button for emergency assistance. The smart stick's design includes features such a long battery life, size adjustment, waterproofing, and light weight. Robust features, portability, stability, ease of access, and energy efficiency are all guaranteed by the entire design.

AC-FPSK modulation for low-energy and low data rate optical wireless communications

This article proposes an amalgam of phase-shift keying and asymmetrically clipped frequency-shift keying (i.e., AC-FPSK) for low-energy/low-data rate optical wireless communications. We design a near-optimal, low-complexity harmonic receiver by analyzing the AC-FPSK time-domain (TD) and frequency-domain (FD) waveforms. The Euclidean distance analysis between AC-FPSK waveform pairs yields lower and upper bounds for theoretical bit error probability. Using numerical simulations, we present an exhaustive evaluation of the optimal cardinality of PSK, which illustrates the superiority of AC-FPSK. We show that AC-FPSK provides better energy efficiency versus spectral efficiency trade-off than state-of-the-art AC-FSK, direct current-FPSK, pulse amplitude modulation, and asymmetrically clipped optical orthogonal frequency division multiplexing. We also demonstrate that by making a suitable choice for the cardinality of PSK, the proposed 2-tap harmonic receiver for AC-FPSK can reach a similar complexity as the AC-FSK harmonic receiver.

Sub-1 GHz RF-Based Energy-Efficient Sensor Node for Secure Communication in Low-Power IoT and Embedded Applications

Background: The Internet of Things (IoT) devices consist of a microcontroller unit for data processing, a low-power wireless radio module for data transmission, and various sensors for data collection. The sensor nodes and processing devices used in the Internet of Things are resource-constrained, with power consumption and security being the two most critical parameters. Objective: This paper addresses the challenges of power consumption and security in IoT scenarios. It presents a low-power and secure heterogeneous multicore sensing architecture designed for lowpower IoT and wireless sensor networks. The architecture comprises a sensing and control subsystem, an information processing unit, and a wireless communication module. Methods: The architecture uses a microcontroller unit based on ARM Cortex M4, a low-power sub-1 GHz RF-compliant communication radio, and a few sensors. The proposed architecture has been implemented and tested using the Contiki Operating System. Results: The implemented sensor node architecture demonstrated performance efficiency, lower energy consumption, and higher security. Conclusion: By leveraging efficient power management, data transmission strategies, and cryptographic security, the architecture contributes to developing energy-efficient and secure IoT devices.

SMART/DIGITAL TIME TABLE SYSTEM

The Smart/Digital College Timetable System is an innovative project designed to enhance the efficiency and accessibility of college schedules. The system integrates advanced technologies such as the Real-Time Clock (RTC), GSM module, Node MCU ESP8266, and an OLED display to provide a comprehensive solution for managing and displaying college timetables ➢ Key Features: ➢ Real-Time Clock (RTC) Integration: • The system incorporates an RTC module to maintain accurate and synchronized time information. • The RTC ensures that the timetable reflects real- time changes and provides precise scheduling for classes, events, and activities. ➢ GSM Module for Remote Updates: • A GSM module is integrated into the system to facilitate remote updates of the college timetable. • Authorized personnel can send schedule updates or modifications via SMS, and the system will automatically adjust the displayed timetable accordingly. ➢ Node MCU ESP8266 for Wireless Connectivity: • The Node MCU ESP8266 serves as the wireless communication module, connecting the system to the internet and enabling seamless data transfer. • The ESP8266 allows for real-time synchronization with online databases, ensuring that the timetable is always up-to-date ➢ OLED Display for Clear and Dynamic Presentation: • An OLED display is employed to present the timetable information in a clear, readable format. • The display provides a dynamic interface, allowing users to easily navigate through the schedule and view relevant details such as class names, venues, and timings. ➢ User-Friendly Interface: • The system is designed with a user-friendly interface to cater to both administrators and end- users. • Administrators can update the timetable remotely, while students and faculty members can access the schedule effortlessly using the interactive OLED display. ➢ Automated Notifications: • The system can be configured to send automated notifications, such as class reminders, to the relevant parties through the GSM module. • This feature helps in ensuring that individuals are informed of any changes or upcoming events. ➢ Energy-Efficient Operation: • The system is optimized for energy efficiency, utilizing low-power modes when idle to conserve power and extend the lifespan of the device. • The Smart/Digital College Timetable System represents a significant advancement in college schedule management, promoting accuracy, real-time updates, and enhanced accessibility. This project serves as a model for integrating emerging technologies to streamline and modernize educational institutions. Key Words: Smart, Synchronization, Harness, LED.

Full‐Range On‐Body Strain Sensor of Laser‐Induced Graphene Embedded in Thermoplastic Elastomer via Hot Pressing Transfer for Monitoring of the Physiological Signals

AbstractAcquiring physical and mechanical strain information of the human body with wearable strain sensors can provide essential data from personal healthcare to human‐machine interfaces and others. Recent research reveals that CO2 laser scribing can convert polyimide films into porous graphene sponges under ambient atmospheres. However, the electrically conductive laser‐induced graphene (LIG) film mismatches with the tough and rigid plastic substrates when it is employed as stretchable strain sensors. In this work, by leveraging the advantageous properties of atoms‐level configured defects within crystalline LIG and heat transfer printing techniques, a flexible LIG‐SEBS (styrene‐ethylene‐butylene‐styrene) strain sensor is made. It is able to achieve exceptional electromechanical properties including a remarkable sensitivity in terms of gauge factor (413–3118), minimal hysteresis, and a broad strain range (>100% strain). Meanwhile, the SEBS‐LIG strain sensor has a stable and fast dynamic response and good repeatability. Additionally, the sensor can be integrated with a wireless communication module for remote monitoring of physiological signals in a real‐time manner with a smartphone App.

Research based on open space collaborative intelligent fire system

The open space collaborative intelligent fire protection system studied in this article uses STM32F407 as the main control chip of the drone, and the STM32F103 is used as the main control chip of the fire truck. ZigBee wireless communication and other modules. The main innovation of this article is to use OpenMV's ground black line recognition positioning, the attitude fusion algorithm of the main controller module, and the PID control algorithm for real -time positioning of drones and fire trucks in the testing area of the test. After actual testing and verification, this system can complete the full coverage of the patrol area in different environments, fire identification in the patrol area, and fire extinguishing tasks. Through the ZigBee wireless communication module Essence.

Detection of Apparent Defects in HPLC/Dual Mode Portable Sorting Device Based on Deep Learning and Image Processing

Abstract As the growth of automated detection technology, traditional manual detection has gradually been replaced. To improve the effectiveness of defect detection, a HPLC/dual mode portable sorting device with deep learning and image processing is raised for apparent defect detection. The product image is segmented using flood filled mean shift method, and defect detection is achieved using Yolo v3 algorithm. An LME2918 chip is the main component of the communication module in the portable device. Based on experimental data, image segmentation accuracy can range from 80% to 100%, and image matching accuracy can range from 85% to 95%. Under the power line carrier mode, the average success rate of apparent defect detection in portable sorting devices can reach 85%, and the change in success rate is not significant, indicating that the detection is relatively stable; Under wireless communication mode, the average success rate can reach 83%, and the change in success rate is relatively obvious, because wireless communication is easily affected by the external environment. The experimental data shows that the defect detection effect of the HPLC/dual mode portable sorting device based on deep learning and image processing meets the design requirements.

Array Phase Center Dynamics Using Spatial Amplitude Modulation for High-Efficiency Secure Wireless Communication

Array Phase Center Dynamics Using Spatial Amplitude Modulation for High-Efficiency Secure Wireless Communication

Initial Chaotic Value-based Index Modulation for Wireless Communications

Initial Chaotic Value-based Index Modulation for Wireless Communications

Implementation of Wearable IoT Devices for Continuous Physiological Monitoring and Analysis

The development of wearable devices for ongoing physiological monitoring and analysis has been made possible by the emergence of the Internet of Things (IoT), which has completely changed the healthcare industry. This study discusses the use of such wearable IoT devices and their potential to improve healthcare delivery. Our research focuses on the development, manufacture, and implementation of wearable sensors capable of real-time monitoring of vital signs like heart rate, body temperature, blood pressure, and activity levels. These devices leverage the Internet of Things to transmit data wirelessly to a cloud service for further analysis. The core components of these gadgets are miniature sensors, low-power microcontrollers, and wireless communication modules. These developments permit the invisible and continuous collection of data, which aids in the early detection of irregularities and permits urgent medical treatments. Data collected by these devices is processed by sophisticated analytics and machine learning algorithms before being transmitted securely to a cloud-based server. As a result, doctors and nurses are able to anticipate health issues, monitor their patients' physical conditions in real time, and provide individualised care. Los patients have more control over their own medical decisions since they have access to their own data. Frequent use of Internet-connected devices for monitoring and analysing physical phenomena may lead to better medical care, lower hospitalisation costs, and higher quality of life. Additionally, these devices have the potential to revolutionise clinical research by providing extensive real-world data for medical research. These wearable IoT devices have the potential to enhance the management of chronic illnesses, encourage early treatments, and raise general wellbeing. Wearable physiological monitoring technology has a lot of potential for the future of healthcare thanks to the advancements of the internet of things.

A self‐powered biosensor based on triboelectric nanogenerator for dual‐specificity bacterial detection

AbstractPathogenic and corrosive bacteria pose a significant risk to human health or economic well‐being. The specific, sensitive, and on‐site detection of these bacteria is thus of paramount significance but remains challenging. Taking inspiration from immunoassays with primary and secondary antibodies, we describe here a rational design of microbial sensor (MS) under a dual‐specificity recognition strategy using Pseudomonas aeruginosa (P. aeruginosa) as the detection model. In the MS, engineered aptamers are served as the primary recognition element, while polydopamine‐N‐acetyl‐D‐galactosamine (PDA‐Gal NAc) nanoparticles are employed as the secondary recognition element, which will also generate and amplify changes in the output voltage signal. To achieve self‐powering capability, the MS is constructed based on a triboelectric nanogenerator (TENG) with the specific aptamers immobilized on the TENG electrode surface. The as‐prepared MS‐TENG system exhibits good stability in output performance under external forces, and high specificity toward P. aeruginosa, with no cross‐reactivity observed. A linear relationship (R2 = 0.995) between the output voltage and P. aeruginosa concentration is established, with a limit of detection estimated at around 8.7 × 103 CFU mL−1. The utilization of PDA‐Gal NAc nanoparticles is found to play an important role in enhancing the specific and reliability of detection, and the underlying mechanisms are further clarified by computational simulations. In addition, the MS‐TENG integrates a wireless communication module, enabling real‐time monitoring of bacterial concentration on mobile devices. This work introduces a pioneering approach to designing self‐powered smart microbial sensors with high specificity, using a double recognition strategy applicable to various bacteria beyond P. aeruginosa.image

Wireless network handheld terminal-based green ecological sustainable design evaluation system: Improved data communication and reduced packet loss rate

Abstract In response to the challenge of high packet loss rates due to poor mobility of PCs, we introduce a sustainable design evaluation system centered around wireless network handheld terminals. This system combines hardware components, including microprocessor and wireless communication modules, to achieve wireless data transmission and program debugging. In the software domain, a configurable communication protocol is employed to establish an ecological data communication module supporting wireless network handheld terminals. Leveraging real-time monitoring data from multiple points, we introduce an information fusion algorithm and construct a green ecological sustainability design evaluation model. Notably, experimental results reveal that our system outperforms alternatives based on sensor and RFID technologies. It exhibits a lower packet loss rate and extends the distance of zero packet loss, highlighting its advantages in data communication.

An Intelligent Water Monitoring IoT System for Ecological Environment and Smart Cities.

Global precipitation is becoming increasingly intense due to the extreme climate. Therefore, creating new technology to manage water resources is crucial. To create a sustainable urban and ecological environment, a water level and water quality control system implementing artificial intelligence is presented in this research. The proposed smart monitoring system consists of four sensors (two different liquid level sensors, a turbidity and pH sensor, and a water oxygen sensor), a control module (an MCU, a motor, a pump, and a drain), and a power and communication system (a solar panel, a battery, and a wireless communication module). The system focuses on low-cost Internet of Things (IoT) devices along with low power consumption and high precision. This proposal collects rainfall from the preceding 10 years in the application region as well as the region's meteorological bureau's weekly weather report and uses artificial intelligence to compute the appropriate water level. More importantly, the adoption of dynamic adjustment systems can reserve and modify water resources in the application region more efficiently. Compared to existing technologies, the measurement approach utilized in this study not only achieves cost savings exceeding 60% but also enhances water level measurement accuracy by over 15% through the successful implementation of water level calibration decisions utilizing multiple distinct sensors. Of greater significance, the dynamic adjustment systems proposed in this research offer the potential for conserving water resources by more than 15% in an effective manner. As a result, the adoption of this technology may efficiently reserve and distribute water resources for smart cities as well as reduce substantial losses caused by anomalous water resources, such as floods, droughts, and ecological concerns.

IoT-based health care system for emotional and heart rate monitoring

An IoT-based remote health monitoring system helps patient’s especially older adults and non-communicable disease (NCD) patients to get medical assistance or advice without being physically present in the hospital or medical centre. This system provides regular health monitoring from anywhere by having access to the Internet. One of the important elements is the physiological parameters which indicate the health status of the monitored patients. Literature study shows that most of the previous works monitor blood pressure, respiratory rate, temperature, ECG, blood oxygenation, diabetes, and hypertension. There have been little works paid attention to measuring the emotional level of the patient. Therefore, this paper explains the development of an IoT-based health monitoring system that measures the emotional level of the patient apart from other essential physiological parameters. The system consists of a microcontroller, two sensors, a wireless communication module, and an IoT cloud display, focusing on measuring the heart rate, body temperature, SpO2, and emotional level. For the heart rate and body temperature readings, the measurements acquired from the developed system show a close agreement with those of the established brand ROSSMAX with an error of less than 5%. For the emotional level test, there are 83.3% out of twelve subjects agree that the GSR value shows her feeling.