Integration Of GPS Research Articles

Digital mapping of soil properties using geomatics: integration of GIS, GPS, and remote sensing applications

Digital mapping of soil properties using geomatics: integration of GIS, GPS, and remote sensing applications

Monitoring System Design Using GPS Tracker and Operational Vehicle Maintenance Case Study of PT. Pertamina (Persero)

The Utilization of GPS and GSM technology in operational vehicle monitoring offers convenience and efficiency in management. This research designs a GPS-based vehicle monitoring system that is integrated with vehicle maintenance management to assist companies in making decisions related to fuel efficiency, predictive maintenance scheduling, and safety aspects. By monitoring vehicle position and condition in real-time, companies can optimize travel routes, reduce travel time and reduce operational costs. The system also includes tire pressure and fuel percentage monitoring, which serve as important indicators in an accurate and sustainable vehicle maintenance strategy. This research uses quantitative methods to analyze various aspects in designing a GPS-based monitoring system that is integrated with operational vehicle maintenance management. With the resulting data, managers are able to identify trends that support predictive maintenance as well as preventive steps to reduce the risk of sudden damage. The research results show that the integration of GPS and GSM provides significant benefits in improving performance and reliability for vehicles, especially in the distribution and logistics sectors. The implementation of this system is expected to support the company in maintaining optimal vehicle performance and contribute to operational sustainability.

Revolutionizing Sports Education using AI & ML

In the realm of sports education and performance analysis, there exists a pressing need to overcome barriers such as geographical limitations, cost constraints, and time constraints inherent in traditional teaching methodologies. In response to these challenges, this paper presents a novel sports education system leveraging artificial intelligence (AI) technologies. This allinclusive system allows for easy access to sports academies and training facilities based on geographic proximity by introducing an innovative teaching platform driven by AI and GPS integration. Moreover, it offers an extensive library of sports laws, sophisticated strategies, and professional advice, encouraging ongoing skill development. Setting goals and closely observing performance are made easier by the system's integration of AI-driven forecasts, such as victory probabilities. The central aim of this initiative is to redefine the landscape of sports education by offering a convenient, cost-effective, and highly efficient solution accessible to individuals at all proficiency levels. In addition to its educational advantages, the system is poised to make significant contributions to sports analytics, supplying extensive data and insights for both researchers and practitioners. This proposal advocates a progressive approach that moves beyond traditional methods, heralding a new era in sports education and performance analytics

Monitoring of ground subsidence using PS-InSAR technique in the Southeast Texas (SETX) Region

The southeast Texas (SETX) coastal area, owing to its unique geographical location and geological attributes, is facing a spectrum of geological challenges, such as ground subsidence, flooding, and coastal erosion. This study endeavors to evaluate the recent instances of ground subsidence and their associated rates, focusing on comprehending their implications for flooding within SETX. Employing the Persistence Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique, this study employs Sentinel-1 SAR satellite data with descending orbit observations spanning from January 2020 to March 2023. Our findings indicate that both the northwestern and eastern regions of Houston have been settled with rates up to 2 cm/year. This settlement trend is consistent with data derived from GPS and groundwater level measurements. This investigation explicitly shows the substantial temporal and spatial variations in subsidence rates, predominantly influenced by localized groundwater extraction due to urbanization (e.g., population growth, land development, etc.). By advocating for the integration of InSAR, GPS, and groundwater measurements, this research aspires to make valuable contributions toward the mitigation of subsidence and flood-related hazards in the SETX area.

Turbo Traverse Dispatch Delivery Assistant Cannibalizing Routing Algorithm

This project aims to develop an innovative delivery bot system that leverages GPS navigation, a digital display, and OTP authentication to transform the delivery process. The system integrates advanced route planning algorithms with real-time GPS navigation to optimize delivery routes and ensure efficient package delivery. Additionally, a digital display enhances communication with recipients and bystanders. providing real-time updates and promoting brand visibility. The implementation of OTP authentication adds an extra layer of security, enabling secure confirmation of delivery receipt. Through the seamless integration of these components, the project aims to revolutionize delivery operations, enhance user experience, and set new standards for reliability and security in the delivery industry. A secured box delivery bot, powered by OTP, GPS, and Arduino, integrates cutting-edge technologies to guarantee the safety and efficiency of package delivery. With OTP, recipients authenticate their identity before accessing the secure box. GPS integration ensures accurate navigation, optimizing delivery routes for timely arrivals. Arduino serves as the control system, enabling seamless operation and sensor integration to enhance security and functionality. In sum, this innovative solution offers a dependable and secure approach to delivering packages to recipients.

The integration of GPS and visual navigation for autonomous navigation of an Ackerman steering mobile robot in cotton fields.

Autonomous navigation in agricultural fields presents a unique challenge due to the unpredictable outdoor environment. Various approaches have been explored to tackle this task, each with its own set of challenges. These include GPS guidance, which faces availability issues and struggles to avoid obstacles, and vision guidance techniques, which are sensitive to changes in light, weeds, and crop growth. This study proposes a novel idea that combining GPS and visual navigation offers an optimal solution for autonomous navigation in agricultural fields. Three solutions for autonomous navigation in cotton fields were developed and evaluated. The first solution utilized a path tracking algorithm, Pure Pursuit, to follow GPS coordinates and guide a mobile robot. It achieved an average lateral deviation of 8.3 cm from the pre-recorded path. The second solution employed a deep learning model, specifically a fully convolutional neural network for semantic segmentation, to detect paths between cotton rows. The mobile rover then navigated using the Dynamic Window Approach (DWA) path planning algorithm, achieving an average lateral deviation of 4.8 cm from the desired path. Finally, the two solutions were integrated for a more practical approach. GPS served as a global planner to map the field, while the deep learning model and DWA acted as a local planner for navigation and real-time decision-making. This integrated solution enabled the robot to navigate between cotton rows with an average lateral distance error of 9.5 cm, offering a more practical method for autonomous navigation in cotton fields.

SOLARIS: A Solar-Powered Mobile Charging Kiosk with Mobile Application

This project aims to create an autonomous solar energy-based charging kiosk in response to the growing demand for charging stations and the ubiquity of mobile devices. SOLARIS, the solar-powered mobile charging kiosk, is coupled with a mobile application enriched with features that interface with GPS technology, allowing users to determine kiosk availability. The kiosk caters to the contemporary reliance on mobile devices, especially smartphones, for charging. The kiosk incorporates an RFID card-based security system for locking and unlocking phone lockers. The project’s objectives include the prototyping of SOLARIS, the development of the SOLARIS System mobile application, and comprehensive testing of its input, processing, and output functions. The developers conducted a quantitative research study, developing a Likert-type questionnaire to gather feedback from alpha testers, including teachers and students. The results and subsequent discussion affirm the prototype’s success, supported by its commendable input, processing, and output functionalities. The study validates the viability of both the prototype and the mobile application, demonstrating their alignment with project expectations. The SOLARIS system is established as operationally effective and secure, with the security feature proving its efficacy, and the mobile application showcasing responsiveness to kiosk status. Notably, a significant recommendation is to incorporate a payment system to enhance the project’s self-sufficiency. Keywords: SOLARIS, Solar-Powered Charging Kiosk, Mobile Application, GPS Integration, Prototype Development, User Feedback, Operational Efficacy, Self-Sufficiency Enchantment, RFID

SafeRoutes: Charting a Secure Path-A Holistic Approach to Women’s Safety Through Advanced Clustering and GPS Integration

SafeRoutes: Charting a Secure Path-A Holistic Approach to Women’s Safety Through Advanced Clustering and GPS Integration

ECONOMIC BENEFITS OF ROUTE MONITORING: GPS TRACKING IN KAZAKHSTAN’S RAILWAYS

In the context of Kazakhstan's railway operations, this study explores the economic advantages derived from the implementation of GPS tracking technology focused on route monitoring. Employing Extreme Programming (XP) principles, a case study within a national railway company details the process, challenges, and outcomes of integrating GPS trackers on mobile phones for workforce location tracking and geo-fencing. Results demonstrate the significant improvement in monitoring workforce activities and precise payroll calculation based on actual working hours. Emphasizing the role of the XP methodology, the study showcases enhanced stakeholder communication, iterative development, and continuous system improvement. Technical aspects of the GPS tracking system, including architecture, data flow, and integration with existing railway management systems, are examined. Moreover, the study delves into encountered challenges such as privacy concerns, data security, and user acceptance during implementation. This case study presents valuable insights for transportation organizations aiming to implement location-tracking and geo-fencing technologies, providing a blueprint for effective project management, iterative development, and stakeholder engagement in pursuit of economic benefits through route monitoring.

Advanced Vehicle Safety: A Prototype Circuit for Accident Prevention and Emergency Response

In contemporary society, the pursuit of robust accident prevention, detection, and reporting systems is paramount, particularly within the context of vehicular safety. This study introduces a meticulously designed prototype circuit, adaptable for deployment across diverse vehicle types. This intelligent circuitry endeavors to mitigate accidents and safeguard human lives by employing a multifaceted approach.The system's primary functions encompass the verification of seat belt usage and the assessment of alcohol consumption by the driver. Additionally, it incorporates a vibration sensor to detect accidents promptly. Complementing these features, the integration of GPS and GSM modules facilitates the rapid notification of emergency services, ensuring prompt assistance in the event of an accident.The core of this system is an Arduino microcontroller, orchestrating the interconnected components to process data and trigger actions based on predefined conditions. The circuit's performance has been rigorously tested, initially through simulation in Proteus software, and subsequently via real-world hardware implementation. Comparative analysis of software and hardware results lends insights into the system's functionality and reliability.The overarching objective of this study is to curtail accidents arising from intoxicated driving, unforeseen driver fatigue, and road obstructions. In instances of accidents, the electronic apparatus employed has the capacity to dispatch spontaneous and precise distress signals to law enforcement and medical personnel, thereby expediting casualty recovery and potentially saving lives. This research advances the fusion of technology and safety measures to augment road safety comprehensively.[6] Upadhyay, V., Gupta, S., Chaturvedi, S. and Singh, D. [2020], ‘Integrated accident prevention detectionand response system (iapdrs)’,International journal of engineering and advanced technology9(3), 2086–2089.[7] Vitkar, S. P., Banare, A. and Nadar, J. [2022], ‘Conceptual framework for accident detection and pre-vention’,Journal of Pharmaceutical Negative Resultspp. 7449–7455.[8] Wu, C., Zhang, P., Zhang, Z., Zheng, W., Xu, B., Wang, W., Yu, Z., Dai, X., Zhang, B. and Zang, K. [2023],‘Slip partitioning and crustal deformation patterns in the tianshan orogenic belt derived from gpsmeasurements and their tectonic implications’,Earth-Science Reviewsp. 104362.[9] Xu, X., Hu, X., Zhao, Y., Lü, X. and Aapaoja, A. [2023], ‘Urban short-term traffic speed prediction withcomplicated information fusion on accidents’,Expert Systems with Applicationsp. 119887.

Analysis of GNSS and IMU Sensor Data Fusion Using the Unscented Kalman Filter Method on Medical Drones in Open Air

Accurate and efficient position estimation is an important element in flight missions for autonomous aerial vehicles such as Unmanned Aerial Vehicles (UAVs). UAVs rely on sensors that provide information regarding position, speed, and orientation. GPS and IMU are sensors that can provide navigation information, where each sensor has characteristics that can complement each other’s shortcomings. Research related to the integration of GPS and IMU sensors for positioning with increasingly higher accuracy has been widely applied, one of which is the Kalman Filter method. Kalman filter not only performs digital signal filtering but is also capable of smoothing and predicting recursion to obtain the most accurate estimation results. Along with the development of the modification of the Kalman Filter, the Unscented Kalman Filter (UKF) method is a solution in overcoming nonlinear systems with estimation results approaching the actual value, so that the positioning accuracy is higher and convergent. This study intends to analyze the fusion performance of GPS and IMU sensor data using the UKF method on Medical Drones in an open space in order to obtain a position with high accuracy. UKF simulations on Medical Drones were carried out using a mathematical model on a 6 DOF (Degree of Freedom) UAV. The sensor data fusion performance was tested by comparing the results of the UKF method with the EKF on the Geopointer software. The results showed that the UKF simulation gave a positional accuracy of 0.022 m to the measurement data. The UKF simulation results in a better positioning accuracy when compared to EKF processing on the Geopointer software which only achieves a position accuracy of 8.467 m. The low accuracy of the EKF processing results is due to the mismatch of the IMU parameters obtained with the actual Medical Drone parameters.

Smart Accident Detection and Emergency Notification System with GPS and GSM Integration

In the aftermath of an incident, numerous valuable lives are tragically forfeited due to the lack of timely and adequate emergency response services. Hence, there arises a necessity for a device to be installed in vehicles that are capable of detecting any untoward incidents and promptly notifying the nearest emergency services providers such as hospitals, ambulance services, and police stations. This paper outlines the development of an Internet of Things (IoT)-based device that comprises an Arduino UNO R3 microcontroller, an accelerometer sensor, a GPS module, and a GSM module. Real-time information about the accident's location, time, and date are sent using GPS and communicated to the emergency service provider through GSM. Upon receiving this crucial information, the emergency service provider can promptly take appropriate action, thereby potentially saving numerous lives affected by the accident.

Mobile augmented reality system for object detection, alert, and safety

The usefulness of mobile devices has increased greatly in recent years allowing users to perform more tasks in daily life. Mobile devices and applications provide many benefits for users, perhaps most significantly is the increased access to point-of-use tools, navigation, and alert systems. This paper presents a prototype of a cross-platform mobile augmented reality (AR) system with the core purpose of finding a better means to keep the campus community secure and connected. The mobile AR System consists of four core functionalities – an events system, a policing system, a directory system, and a notification system. The events system keeps the community up-to-date on current events that are happening or will be happening on campus. The policing system allows the community to stay in arms reach of campus resources that will allow them to stay secure. The directory system serves as a one-stop-shop for campus resources, ensuring that staff, faculty, and students will have a convenient and efficient means of accessing pertinent information on the campus departments. The mobile augmented reality system includes integrated guided navigation system that users can use to get directions to various destinations on campus. The various destinations are different buildings and departments on campus. This mobile augmented reality application will assist the students and visitors on campus to efficiently navigate the campus as well as send alert and notifications in case of emergencies. This will allow campus police to respond to the emergencies in a quick and timely manner. The mobile AR system was designed using Unity Game Engine and Vuforia Engine for object detection and classification. Google Map API was integrated for GPS integration in order to provide location-based services. Our contribution lies in our approach to create a user specific customizable navigational and alert system in order to improve the safety of the users at their workplace. Specifically, the paper describes the design and implementation of the proposed mobile AR system and reports the results of the pilot study conducted to evaluate their perceived ease-of-use, and usability.

Evaluation of Sources of Artificial Light at Night With an Autonomous Payload in a Sounding Balloon Flight

The presence of artificial light at night is not only limiting astronomical observations but has been linked to negative effects on human health and behavior of wildlife. New measurement systems are therefore needed to monitor artificial light emissions and their time evolution; MINLU autonomous payload has been designed and tested at University of Padova to provide complete aerial observations of artificial light sources over extended areas, with the capability to be integrated either on stratospheric balloons or drones. The implemented architecture is based on commercial components and is controlled by a Raspberry PI single board computer with the capability of uninterrupted operation up to 5 hours. The payload was successfully launched with a stratospheric sounding balloon on July 8th 2021 from Lajatico (Tuscany) and performed continuous analysis of emission sources up to the burst altitude of 34 km. The work will describe the calibration activity of the imaging unit which includes commercial cameras with dedicated filters used as luminance measuring device and raw spectrometer and present the elaboration of georeferenced images after reconstruction of the unit's inertial pointing along flight trajectory using combined GPS and IMU data integration.

Real-time GPS Tracking System for IoT-Enabled Connected Vehicles

This paper presents a real-time GPS tracking solution for connected vehicle networks, leveraging IoT, V2X communication, and VANET technologies. The system uses Arduino Uno R3, SIM800L, NEO6M GPS, Node.js, socket, and Firebase for seamless real-time GPS data collection, storage, and visualization. Users can access and monitor GPS data on a web interface. Integration of Node.js and sockets ensures efficient hardware-software communication, while Firebase enables realtime data storage and synchronization for resource management and tracking. The paper explores the system’s applications in dynamic routing for energy efficiency, eco-driving feedback, smart charging stations, environmental data collection, intelligent traffic management, and fleet emissions reduction. These applications highlight the system’s versatility, promoting energy efficiency and sustainability across industries. By incorporating IoT, VANET, and V2X communication, the system enables seamless connectivity and data exchange among vehicles, infrastructure, and the cloud, enhancing decision-making and system efficiency. Insights into system implementation, including IoT, VANET, and real-time GPS integration, are provided. The paper discusses transportation, logistics, and vehicule tracking as potential application domains, which hold promise for optimizing energy consumption. The presented solution offers an efficient, reliable platform for real-time GPS tracking in connected vehicle networks, harnessing IoT, VANET, and V2X communication for enhanced decisionmaking and sustainable transportation systems.

Development Status and Service Performance Preliminary Analysis for BDSBAS

The BeiDou global navigation satellite system (BDS-3) provides positioning, navigation and timing services for global users, moreover, it provides BDS satellite-based augmentation system (BDSBAS) single-frequency (SF) and dual-frequency multi-constellation (DFMC) services for users in China and its surrounding areas. The BDSBAS SF service is in accordance with Radio Technical Commission for Aeronautics (RTCA) standard protocol (RTCA MOPS) and augment GPS constellation, while the BDSBAS DFMC service is in line with SBAS L5 DFMC standard protocol and is aimed at supporting any combination of BDS/GPS/Galileo/GLONASS constellations, including only a single constellation operation. We introduced the development status of the BDSBAS system, including the system architecture and navigation user algorithms. Based on the GPS measurements, the accuracy, integrity and availability of the BDSBAS SF service were evaluated, and with the BDS measurements, the accuracy of the BDSBAS DFMC service was preliminarily analyzed. The integrity and availability of the BDSBAS DFMC service will be discussed in future work as some of the DFMC integrity parameters are still under discussion for optimization. The results show that, for BDSBAS SF service, the horizontal and vertical position accuracy were about 1.0 m and 2.0 m (95%), respectively, which were improved by 39% and 33%, respectively, compared with the GPS SF position accuracy. For BDSBAS DFMC service, the horizontal and vertical position accuracy were about 0.6 m and 1.2 m (95%), respectively, which were improved by about 25% and 20% compared with the BDS dual-frequency position accuracy. No system integrity risk event was detected during the testing period for BDSBAS SF service. The average availability of the BDSBAS SF service was about 98% which was mainly affected by the availability of ionospheric grid delay corrections.

Low-Cost Attitude Estimation Using GPS/IMU Fusion Aided by Land Vehicle Model Constraints and Gravity-Based Angles

This paper details a method to improve accuracy of the land vehicle attitude estimation. It employs the vehicle model constraints to enhance the integration of GPS and a low-cost MEMS inertial measurement unit (MIMU) (GPS/MIMU). To improve the yaw angle estimation, we propose a lateral velocity constraint (LVC) aided method based on the observability analysis for the integrated fusion system. The theoretical analysis indicates that the yaw angle will be directly observed if LVC is augmented into the GPS/MIMU fusion algorithm. Furthermore, for LVC/MIMU system without GPS, the roll angle is always well estimated regardless of whether the vehicle is moving or stationary, and, surprisingly, the pitch angle can also be relatively accurately estimated if the vehicle is moving. Thus, when GPS is unavailable, the LVC/MIMU fusion is proposed by replacing the GPS measurement with the virtual measurement LVC. It is an encouraging improvement since the accumulating errors induced by gyro bias can be suppressed using MIMU alone. Moreover, to overcome the shortage that the pitch angle is not observed if the vehicle is stationary, we propose to fuse the gyros with gravity-based angles by Kalman filtering if the vehicle is detected motionless based on a switching rule. The experimental results compare favorably to theoretical analysis, showing that the proposed method can effectively improve the accuracy for land vehicle attitude estimation.

Improved design of automatic solar tracking system based on integration of accelerometer, compass sensor, and GPS

Improved design of automatic solar tracking system based on integration of accelerometer, compass sensor, and GPS

Automatic Vehicle Accident Detection and Healthcare Unit Notification using IoT Technology with ESP32

In developing countries the whopping increase in population has indirectly contributed in rapid motorization and extensive growth of vehicles. Due to this, the road accidents have become unavoidable that is causing a high rate of fatalities and severe injuries. The drastic influence of modern technologies has significantly played the vital role in preventing accidents by automizing the vehicle and making it completely smart. This paper mainly discuss about the system which is developed using IoT technology with the integration of ESP32 Microcontroller, Smart Sensors, GPS, GSM and Blynk Application to detect accident and to send immediate notification to the nearby healthcare centers and emergency contacts for the rescue operation.

Study on the Method of Retrieving Surface Soil Moisture in Western Semi-arid Area by Remote Sensing

Soil moisture is a very important index parameter in the field of hydrology and meteorology, which plays a very important role in the development of agriculture. Large scale monitoring and retrieval of soil moisture is the main component of agricultural research and ecological environment assessment. The region of the soil water environment is one of the essential parameters in examining the land surface process model. Therefore, remote sensing inversion of soil moisture is a very convincing research topic, and it is also the boundary field of remote sensing technology application research, which is one of the global recognized research problems. With the development of remote sensing technology and GIS, GPS and 3S integration and other related disciplines, not only can the large-scale real-time monitoring of soil moisture dynamics be carried out, but also the accuracy of soil moisture inversion has been greatly improved. Looking back on the development of several decades, several remote sensing methods of soil moisture retrieval have appeared, and these methods have been well verified and applied in corresponding areas.