GPS Module Research Articles

Enhancing the rocker-bogie Mechanism with automation: A study on sensor integration and Mechanical arm functionality

The rocker-bogie mechanism is a well-known design in robotic mobility, particularly effective for rovers traversing rugged terrains. This research improves upon the traditional rocker-bogie system by integrating ultrasonic sensors, a GPS module, and a mechanical arm to enhance autonomy and versatility. The system is controlled by an Arduino Uno and powered by six 12V DC motors using an L298 2A motor circuit board, ensuring precise and reliable movement in challenging environments. Ultrasonic sensors provide effective obstacle detection by triggering a turn when objects are within 50 cm. This is a simpler alternative to complex AI-based path planning. Additionally, the integration of GPS enhances navigation capabilities. The mechanical arm allows for interaction with the environment, enabling tasks such as object manipulation and repairs. The project aims to enhance autonomous navigation and improve sensor-based obstacle avoidance, motivated by Experimental methods including testing the rover’s obstacle detection capabilities using ultrasonic sensors in controlled environments with varying obstacle distances. The rover’s navigation was evaluated across different terrains, including flat surfaces and uneven terrains to assess their mobility and stability. Optionally, GPS accuracy was tested by guiding the rover to predefined waypoints, while power efficiency was monitored during continuous operation to measure battery life and overall system performance. Results showed that. This work improves robotic autonomy in harsh conditions and uses mechanical parts to reduce the margin of error in fields such as agriculture, disaster response robots, Autonomous Mining Vehicles, Pipeline and Infrastructure Inspection, Volcanoes, Deep Caves, and Extreme Terrains.

A Smart IoT-Based Safety System for Vulnerable Populations: An Innovative Approach Using AI and Blockchain

In an increasingly digital world, safety remains a critical concern, especially for vulnerable populations such as women, children, and the elderly. This research presents an advanced IoT-based smart wearable safety device integrating artificial intelligence (AI) and blockchain technologies to enhance personal security. The system incorporates sensors for monitoring physiological and environmental parameters, a GPS module for real-time location tracking, and a high-frequency alarm. Blockchain ensures secure data transmission and tamper-proof records, while AI enhances threat detection through sentiment analysis and machine learning-based pattern recognition. Experimental results demonstrate an accuracy of 96.8%, a sensitivity of 94.3%, and a robust safety response mechanism. The proposed solution offers scalable, energy-efficient, and cost-effective protection, setting a benchmark for IoT-based safety systems. Keywords: IoT, Blockchain, AI, Personal Safety, Wearable Technology

Electronic instrumentation for the acquisition and visualization of data from multiple sensors in a Graphical User Interface in MATLAB

This paper presents the development of a real-time data acquisition and visualization system based on an ARM microcontroller and a Graphical User Interface (GUI) developed with MATLAB AppDesigner. The microcontroller acquires and processes raw data from multiple sensors, including accelerometers, gyroscopes, temperature and humidity sensors, an atmospheric pressure sensor, and a GPS module. These data are converted into physical units and transmitted via serial communication to the GUI, which displays the information in real-time. GUI enables intuitive monitoring through dynamic graphics and interactive tools such as zoom and pan. Additionally, it offers a data-saving option for later analysis in text files. Results from performance tests indicate reliable system operation, with continuous and stable data transmission, along with clear and precise measurement visualization. This work underscores the effectiveness of hardware-software integration in developing versatile and accessible monitoring systems for instrumentation and control applications.

Implementasi Sistem Keamanan Kendaraan Bermotor Menggunakan GPS Berbasis IoT

<p><em>Rapid technological advancements have driven the development of Internet of Things (IoT)-based products, enabling communication between devices via the internet network. Currently, motor vehicle security system is typically performed in a manual manner, such as through the use of steering locks, chains, or wheel locks. This research aims to design and implement an IoT-based vehicle security system that can be controlled automatically. The system integrates hardware components, such as NodeMCU, relays, GPS modules, and fingerprint sensors, with software including Arduino sketch and the Blynk application. The test results show that the system can generate key data, including control range, follow-up to disconnect the vehicle's electrical system, and vehicle location tracking in the form of coordinates accessible through the Maps application. The research resulted in a security system that can be accessed through two methods: close-range using a fingerprint sensor as a replacement for traditional keys, and remotely through the Blynk application connected to IoT technology.</em></p><p> </p><p> </p>

IOT-based Accident Detection and Alert System

Speed is the one of the basic reasons for vehicle accident in India. To reducing the accidents the system is used that is `Accident Detection and Alert System'. This system alert when accident occurred and immediately contact to the emergency unit. Arduino UNO is processor of this system. It control the whole system. The input are Acceleration meter , Gyroscope, Vibration Sensor and output are LCD , Buzzer, GSM module, GPS module .When accident occurred their vibrations are detected by vibration sensor and accelerometer detects sudden changes in speed that may indicate an accident or crash. Gyroscope monitors changes in orientation or rotation of the vehicle, which can be useful for detecting rollovers or sudden swerving. GPS module provides real-time location data, which is useful for sending SMS of accident locations to emergency unit. GSM module get accident location and data send it to emergency unit. And Buzzer get ON and LCD display danger message

Automatic Drainage Monitoring and Control System

This paper presents the development and implementation of an automatic monitoring and control system for manholes. The system integrates sensors to monitor temperature, altitude, pressure, and gas levels in drain water. An ultrasonic sensor, controlled by Arduino, detects water levels, triggering a motor to pump out water when a specific threshold is exceeded, thereby preventing clogs. A GPS module provides real-time location data, aiding municipal personnel in efficient management. The system aims to enhance urban drainage maintenance, ensuring prompt response to potential hazards and maintaining optimal functionality of the drainage network.

Key to Safety: A Multi-Functional Smart Keychain for Real-Time Women\'s Security

Abstract: The increasing need for women's safety in public areas has provided the base for innovation in creating compact, efficient personal security tools. This paper explores an intelligent keychain device tailored and designed with a combination of various defensive and alerting technologies with applications specifically for women's safety. The input involves GPS and GSM modules integrated with the A9G board. It has a LiPo battery, which is fitted with a push button. A preset alarm would immediately be sent to contacts in case of emergency. Other hardware installed was the taser for personal defense and a buzzer, to ensure a sufficiently audible alarm. The system is programmed with information through a USB to TTL converter. The methodology used here was to couple hardware with software, monitor locations, and communicate real-time information to the emergency contacts. The GPS/ GSM modules are selected to allow for global coverage, and the push button allows easy usage in emergencies, so taser modules with a further number of added security features. It is designed to be compact yet cost-effective, consumer-friendly, and also available with a reduction in power consumption based on an efficient selection of components.

A Fuzzy Logic Approach to Enhance GPS Accuracy for Blood Cooler Box Tracking

An innovative technological development, the position tracking system uses latitude and longitude coordinates to determine the GPS's location. The covid-19 pandemic has caused the demand for cool box delivery for convalescent blood plasma to increase significantly. The obstacle in the field is the hospital's position and patient rooms far from the reach convalescent donors, so they require a cool box for delivery. The problem is tracking the cool box accurately and precisely so that it can be monitored by the hospital properly. For this reason, it is necessary to increase the accuracy of the GPS position in the cool box by using fuzzy logic algorithms The Ublox NEO-6M is one GPS module that can be utilized for navigation. This module uses UART connection using the NMEA 0183 protocol and has an accuracy level of around 2.5 meters to 10 meters. In this research, validation of the accuracy of the GPS coordinate position was carried out on a Blood Cool Box device which was designed using the fuzzy logic method. The Sugeno method fuzzy logic algorithm is used to validate the accuracy of GPS coordinate positions based on latitude and longitude obtained from the GPS sensor module. The test results show a Mean Absolute Percent Error (MAPE) value of 21.66% which can be concluded that the Sugeno fuzzy logic method algorithm has forecasting model capabilities that are suitable for use as a validation method for testing GPS position coordinates.

Innovative navigation: a smart cane solution with GPS, GSM, and real-time image capture

Our article presents the design, study, and implementation of a smart cane aimed at enhancing the autonomy and safety of individuals who are blind or visually impaired. The solution is built around an Arduino board, integrated with various sensors and modules, to provide real-time tactile and auditory feedback to the user. Utilizing a combination of basic and advanced technologies, this smart cane detects obstacles at varying distances, triggering sound and vibration alerts to assist the user in navigation. Beyond these essential functions, the cane offers advanced features such as real-time image capture and obstacle recognition through the ESP32-CAM module. Additionally, the system is equipped with a GSM module that facilitates emergency communication by sending SMS messages with the user’s GPS location, obtained via the Neo-6M GPS module. These technological enhancements improve user safety by streamlining obstacle detection and enabling remote assistance when needed. The primary objective is to create a comprehensive solution that not only detects and avoids obstacles but also provides visual information and supports communication with caregivers or emergency services. By doing so, the smart cane contributes to a higher degree of independence and an improved quality of life for blind and visually impaired individuals.

Fault Detection in Transmission Line

Abstract: This project focuses on the design and implementation of an advanced fault detection system for overhead transmission lines, utilizing key components such as the ESP 8266 microcontroller, current sensors, a GPS module, and IoT integration. The system is capable of detecting and classifying four major fault types: single line to ground (L-G), line to line (LL), double line to ground (L-L-G), and three-phase faults (L-L-LG). By placing current sensors at the transmission line's sending end, the system identifies faults and accurately determines their location through GPS coordinates .Simulations using protect us software were conducted to verify the system’s performance prior to building a hardware prototype. Upon fault detection, the system provides alerts via an LCD display and a buzzer, while real-time fault data is transmitted to an Android app and web server through the arduino IoT cloud. Testing confirmed the system’s precision in fault identification and location tracking, ensuring timely notifications for control room and remote device operators. This successful implementation highlights the system's potential for improving safety and efficiency in power transmission networks. the project lays the groundwork for further exploration into advanced fault detection and real-time monitoring solutions in electrical engineering.

Expanding the field of view - a simple approach for interactive visualisation of electron microscopy data.

The unparalleled resolving power of electron microscopy is both a blessing and a curse. At 30,000× magnification, 1 µm corresponds to 3 cm in the image and the field of view is only a few micrometres or less, resulting in an inevitable reduction in the spatial data available in an image. Consequently, the gain in resolution is at the cost of loss of the contextual 'reference space', which is crucial for understanding the embedded structures of interest. This problem is particularly pronounced in immunoelectron microscopy, where the detection of a gold particle is crucial for the localisation of specific molecules. The common solution of presenting high-magnification and overview images side by side often insufficiently represents the cellular environment. To address these limitations, we propose here an interactive visualization strategy inspired by digital maps and GPS modules which enables seamless transitions between different magnifications by dynamically linking virtual low magnification overview images with primary high-resolution data. By enabling dynamic browsing, it offers the potential for a deeper understanding of cellular landscapes leading to more comprehensive analysis of the primary ultrastructural data.

An intelligent and portable fiber optic real-time fluorescence detection system for pathogenic microorganisms detection

The detection of pathogenic microorganisms poses an increasingly serious challenge to food safety. This paper proposes an intelligent fiber optic fluorescence sensing system for detection of pathogenic microorganisms. The system integrates light-emitting diodes and fiber optic sensing arrays. Compact and multi-channel detection is achieved by this kind of design. Environmental parameters such as temperature, humidity, and location are intelligently analyzed together with sampled fluorescence signal, which successfully achieved a high accuracy detection result without affected or interfered by environmental parameters. A Radial Basis Function Neural Network (RBFNN) algorithm is utilized for intelligent analysis and prediction of pathogenic microorganisms’ concentration with environmental parameters. Under different environmental parameters, the system has successfully detected African swine fever virus or salmonella in real-time with high accuracy and sensitivity. Since location of the sensing system can be determined by GPS module integrated in the system, the change of pathogenic microorganisms with different locations can be determined even during transportation. This innovative solution provides a convenient and accurate method for high accurate on-site real time sensing of pathogenic microorganisms.

IoT-Based Women Safety Device

Abstract: Women's Safety has always been a major problem even in these modern times with a lot of advancements in technology. The existing system provides safety bands for women which can be activated either manually or automatically, but both options are not available leading to more chances of false alarms. The proposed system “IoT-based Women Safety Device” mainly focuses on providing a reliable, fast and very effective system for the safety of women. It provides a platform that will be actively available 24/7 for their help to avoid any unfortunate situations. The user can activate the device manually by pressing the activation button or automatically depending upon pulse rate and motion sensor value. On activation, the location of the user can be traced using the GPS module and alert messages will be sent to registered contacts using the GSM module. The mobile application remains connected to the Safety Device for User Authentication and storing user data in the Firebase real-time database.

EVALUASI KINERJA DAN EFISIENSI JARINGAN LORAWAN UNTUK APLIKASI IOT DI LINGKUNGAN SUBURBAN

The current era of digitalization is rapidly advancing, especially in the utilization of Internet of Things (IoT) technology for various purposes, including in the transportation and vehicle rental sectors. This research focuses on the application of the LoRaWAN network in supporting the electric scooter rental system in suburban environments, particularly in the Kintamani area. The designed system allows real-time monitoring of electric scooter locations through the integration of GPS modules, and also provides additional security features with an emergency button for urgent situations. The system is also equipped with rental time settings to maximize efficiency in managing electric scooter rentals. LoRaWAN was chosen for its ability to transmit data over long distances with low power consumption, which is highly suitable for suburban areas with wide coverage and limited infrastructure. This research not only evaluates the network's performance in terms of communication but also reviews the system's efficiency in terms of the number of devices that can be connected simultaneously. The evaluation focuses on how optimally this system can be used on a larger scale, especially in supporting the growing needs of IoT. This study provides insights into the potential development of a safer and more efficient IoT-based bike rental system in suburban environments.

Rancang Bangun Pendeteksi Pencemaran Air Laut Berbasis Microprocessor

Sea water pollution is an increasingly urgent global issue, caused by various factors such as industrial waste, household waste, and ship activities. One of the solutions needed to overcome this pollution is the development of a detection system that is able to monitor polluting substances quickly, accurately, and efficiently. This research aims to design and build a microcontroller-based seawater pollution detection system, which can identify various pollution parameters in real-time. This research uses the Research and Development (R&D) method to develop a system consisting of several main components, including a pH sensor, turbidity sensor, Arduino Uno, GPS module, Raspberry Pi 4, USB camera, LiPo battery, and step-down converter. Each component is tested individually before being integrated into the overall system. The results of testing in a real environment show that the system is able to detect seawater pollution parameters with high accuracy. However, there are some errors in data collection, especially in the camera sensor with a percentage error of 32%, turbidity sensor 20%, and pH sensor 24%. Further improvements and developments were made based on the evaluation results to enhance system performance. The resulting system is considered accurate, reliable and easy to use, making an important contribution to efforts to protect seawater quality and mitigate the negative impacts of pollution on the environment and human health.

IoT-GChain: Internet of Things-Assisted Secure and Tractable Grain Supply Chain Framework Leveraging Blockchain

The grain supply chain is crucial for any nation’s self-sustainability due to its huge impact on food security, economic stability, and the livelihoods of several people. The path grain takes from farmers to consumers is opaque and complicated, due to which consumers cannot trust grain quality and its origin. Although blockchain is widely used for fair and secure transactions between farmers and buyers, issues related to transparency and traceability in the grain supply chain, such as counterfeiting and middlemen involvement, have not been adequately addressed. To tackle these issues, a blockchain-based solution is proposed that unites farmers, warehouses, government central and state agencies, transporters, and food corporations on a single platform to enhance transparency, traceability, and trust among all parties. This system involves minting a non-fungible token (NFT) corresponding to each lot of grain approved by government officials. The NFT comprises grain quality, type, temperature data from sensors, weight, and ownership information, which updates as the grain lot moves across the supply chain from central agencies to state agencies and so on. NFTs enable stakeholders to track the grain lot from cultivation to end-users, providing insights into grain conditions and quality. An Internet of Things-based circuit is designed using a Digital-output relative humidity & temperature (DHT22) sensor, which offers real-time temperature and humidity readings, and geolocation coordinates are gathered from the GPS module across the supply chain. Farmers can directly interact with warehouses to sell grains, eliminating the need for middlemen and fostering trust among all parties. The proposed four-tier framework is implemented and deployed on the Ethereum network, with smart contracts interacting with React-based web pages. Analysis and results of the proposed model illustrate that it is viable, secure, and superior to the existing grain supply chain system.

VSAT Pointing Parameter Calculation Programming with Trigonometry Principles Using NEO6M GPS Module as Coordinate Detection Using C++ Programming Language

Very Small Aperture Terminal or VSAT is a type of telecommunications technology that uses satellites as a transmission medium. In the VSAT installation process there is a process called pointing, which is the process of directing the VSAT vertically and horizontally in the direction of the target satellite. This is very important to do to get good signal quality, so that the service output from the VSAT is good. The position of the VSAT device on earth, while the satellite is in outer space, creates complexity in the pointing process. The parameters to pay attention to when pointing are the azimuth value, namely the direction formed horizontally between the VSAT device and the point 0 degrees north of the earth, as well as the elevation value, namely the angle formed vertically between the VSAT device and the satellite towards the 0 degree point in the horizon plane. To obtain the azimuth and elevation parameters, previous scientists had written them in a mathematical formula with complex trigonometry elements. By using quantitative methods, this journal summarizes the programming of these formulas using the C++ language. This is useful in the future to determine the suitability of calculation results and can be developed further by direct integration into VSAT devices. This research also uses the NEO6M GPS module which can provide coordinate information because it is needed in calculating the formulation. The results of this research are that C++ can be used to program complex trigonometric mathematical calculations and the accuracy of the programmed parameters can be adjusted according to the type of data used. In conclusion, the C++ language can be used to carry out VSAT pointing parameter calculation programs in collaboration with GPS sensor readings with appropriate results.

Implementation of a low-cost comprehensive pavement inspection system

Assessing the condition of roads is crucial to the maintenance and rehabilitation process as a country's progress is closely linked to its transport infrastructure. Therefore, it is essential to have well-maintained roads and to be able to control and monitor them properly. Technological advancements have transformed the way pavement inspections are carried out. This study presents an innovative approach that combines stereo cameras and a GPS module for efficient and accurate data collection. This integration of low-cost technologies provides a detailed three-dimensional view of pavements, complemented by accurate geospatial information. The experimental results showed that the 3D images of pavement damage had a relative volume measurement error of 0.80 %. Unlike traditional systems such as LIDAR and ground-penetrating radar, which involve more expensive technologies, the proposed method offers a cost-effective solution. This methodology not only simplifies the inspection process but also improves the planning and execution of road maintenance and repair activities. Its low cost makes it a viable option for various projects and applications in road infrastructure.

Intelligent Street Lighting: An IoT-based System for Adaptive Brightness and Fault Management

The research aims to develop an intelligent fault detection and control system for street lights using an STM32 microcontroller and Internet of Things (IoT) technologies. The system uses various sensors and communication methods to manage lighting more effectively and maintain infrastructure better. Light-Dependent Resistors (LDRs), which turn lights on automatically at nightfall and off at dawn, are essential to the system's operation. Moreover, motion is detected by the infrared (IR) sensors on the street, allowing the lighting to save energy by dimming during times of low traffic and brightening when movement is detected. By using control logic and sensor readings, a relay functions as an electronically controlled switch to turn the lights on and off. To process sensor data, the STM32 microcontroller is used in the main functionality. Energy savings are facilitated by the automated on/off switching based on ambient light levels, enabled by the LDR sensor data. In addition, the device includes a GPS module for precise street light location tracking. An IoT platform transmits this location data as well as operational status and real-time sensor readings. Maintenance staff can access regional data on light quality and sensor readings through an LCD display. This extensive data enables maintenance team to focus better, use resources efficiently, and enable remote monitoring and fault identification (e.g., burned-out bulbs). This Internet-of-Things (IoT) system provides an economical and environmentally friendly approach to efficient street light management by integrating automation, remote control, and real-time monitoring.

Accident Prevention System

Accident prevention system represents a groundbreaking innovation in vehicular safety technology. This advanced system integrates cutting- edge technologies such as eye blink sensors, GPS modules, Arduino and GSM communication to detect and mitigate potential hazards during driving. The accident prevention system incorporates a GPS module, enabling precise location tracking and providing crucial data for emergency responders. The integration of these technologies aims to significantly reduce the risk of accidents caused by driver inattention, fatigue, or other safety-critical factors. This abstract outline the comprehensive approach of accident prevention system, highlighting its potential to revolutionize road safety by leveraging state-of-the-art sensor technologies and intelligent communication systems. Key Words: Eye blink sensor, Arduino, GPS Module, GSM Module.