Tag: sub-meter

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Recent Methods for Evaluating GNSS Receiver Accuracy and Reliability

https://eos-gnss.com/knowledge-base/gps-overview-1-what-is-gps-and-gnss-positioning

By Shahabuddin Amerudin

Global Navigation Satellite System (GNSS) receivers are vital in Geographic Information Systems (GIS), serving as the foundation for accurate spatial data collection. These systems are integral to a wide range of applications, including urban planning, precision agriculture, infrastructure development, and environmental monitoring, all of which demand high positional accuracy for reliable decision-making. Achieving sub-meter accuracy is essential, as even small positional errors can have significant implications, such as misalignment in land parcel delineation or imprecise application of resources in precision agriculture (Lachapelle & El-Rabbany, 2021). GNSS receivers, however, vary in performance due to factors like environmental conditions, satellite geometry, and receiver quality. This article explores the most recent methods employed to evaluate GNSS accuracy, with a focus on achieving sub-meter precision and reliability.

1. Root Mean Square Error (RMSE) Analysis

Root Mean Square Error (RMSE) is one of the most widely utilized metrics for assessing GNSS receiver accuracy. RMSE calculates the difference between GNSS-measured coordinates and reference coordinates, providing an overall measure of positional error. It has become a standard method for evaluating accuracy across diverse GNSS applications, including those requiring sub-meter precision.

The primary advantage of RMSE is that it offers a single-value summary of the average error, allowing for straightforward comparisons between different receivers or correction methods. For example, in precision agriculture or urban planning, using RMSE enables decision-makers to quantify how much the GNSS-based positional data deviates from known control points (Rizos & Wang, 2022). RMSE is calculated by comparing the deviations in the X, Y, and Z axes and is particularly useful when determining how well a receiver performs under various environmental conditions.

2. Circular Error Probable (CEP)

Circular Error Probable (CEP) is another widely used method for evaluating the accuracy of GNSS receivers, particularly in measuring horizontal accuracy. CEP defines a circle within which 50% of the GPS measurements are expected to fall, offering a simplified yet effective way to assess positional accuracy in two-dimensional space. It is especially useful in GIS applications that rely heavily on horizontal coordinates, such as mapping and navigation (Langley, 2023).

CEP is often applied in tandem with RMSE to provide a more nuanced understanding of GNSS accuracy. While RMSE evaluates overall error, CEP focuses specifically on horizontal accuracy, making it ideal for GIS users interested in the precision of latitude and longitude measurements (Misra & Enge, 2019). By analyzing the distribution of positional errors, CEP gives an intuitive measure of how spread out or clustered the data points are around the true position.

3. Horizontal and Vertical Dilution of Precision (HDOP/VDOP)

Dilution of Precision (DOP) is a critical factor in determining GNSS accuracy, with Horizontal DOP (HDOP) and Vertical DOP (VDOP) values indicating the quality of satellite geometry and its impact on positional accuracy. Low DOP values suggest better satellite configurations, which improve the reliability of positional data.

HDOP and VDOP are particularly useful for assessing how satellite geometry affects horizontal and vertical accuracy, respectively. Many GNSS receivers report HDOP and VDOP values alongside positional data, allowing users to evaluate the quality of the satellite constellation at the time of data collection (Groves, 2020). This makes DOP values essential for understanding how well GNSS receivers perform in varying environmental conditions, such as urban canyons or heavily forested areas, where satellite visibility may be obstructed (Lachapelle & El-Rabbany, 2021).

4. Standard Deviation of Coordinates

The standard deviation of coordinates provides insight into the consistency of GNSS receiver performance by measuring the variation of positional data around a mean value. It is particularly useful in detecting irregularities or errors caused by multipath effects or signal interference. This method allows researchers to evaluate the spread of GNSS measurements and identify outliers that may be affecting overall accuracy.

The standard deviation is calculated by averaging the collected coordinates and determining how much each data point deviates from this average. A low standard deviation indicates that the positional measurements are closely clustered around the mean, reflecting good consistency and reliability (Kaplan & Hegarty, 2017). This method is especially beneficial for applications where long-term consistency is more critical than instantaneous accuracy, such as in environmental monitoring or geodetic surveying (Misra & Enge, 2019).

5. Kinematic vs. Static Testing

In addition to static testing, where the GNSS receiver remains stationary at a known point, kinematic testing evaluates receiver performance during movement. Kinematic testing simulates real-world applications, such as vehicle tracking or navigation, where the receiver must maintain accuracy while in motion.

Kinematic testing provides valuable insights into how well a GNSS receiver performs under dynamic conditions, making it essential for assessing performance in navigation-based applications. In these tests, the receiver is moved along a predetermined path, and its recorded positions are compared to the known path using metrics like RMSE and CEP. This method is crucial for understanding how well a receiver can maintain accuracy while compensating for motion, an essential consideration in vehicle-based GIS applications (Li & Zhang, 2022).

6. Multi-Constellation GNSS Evaluation

Modern GNSS receivers have the ability to track multiple satellite constellations, such as GPS, GLONASS, Galileo, and BeiDou, which improves the accuracy and reliability of positional data. Evaluating performance across multiple constellations allows researchers to identify which satellite systems and combinations provide the best accuracy in various environments.

Multi-constellation tracking has become particularly important in environments where satellite visibility is limited, such as urban areas with tall buildings or dense forests. By using multiple constellations, GNSS receivers can compensate for the limitations of individual systems, leading to improved accuracy and reliability (Wubbena & Seeber, 2021). Performance is evaluated by comparing data collected from different constellations and analyzing the impact on positional accuracy using metrics such as RMSE and standard deviation (Hofmann-Wellenhof & Lichtenegger, 2020).

7. Positional Accuracy Improvement with Differential Correction

Differential correction techniques such as Real-Time Kinematic (RTK), Satellite-Based Augmentation Systems (SBAS), and Precise Point Positioning (PPP) are commonly used to improve GNSS accuracy. These methods provide correction data that compensates for satellite and atmospheric errors, significantly enhancing the precision of positional measurements.

RTK, for example, can achieve sub-centimeter accuracy, making it an invaluable tool for applications requiring high precision, such as cadastral mapping or infrastructure development. The effectiveness of differential correction is often assessed by comparing data collected with and without correction, with accuracy improvements quantified through RMSE and other metrics (Ge & Xie, 2023). These correction methods are crucial for ensuring reliable GNSS data in areas where uncorrected GNSS signals may be insufficient for sub-meter accuracy.

8. Geostatistical Analysis

Geostatistical methods, such as Kriging and Spatial Autocorrelation, are increasingly used to analyze the spatial distribution of GNSS errors. These techniques help identify areas where errors cluster and understand how environmental factors, such as building density or tree cover, influence GNSS accuracy.

By adding a spatial dimension to error analysis, geostatistical methods offer valuable insights into the environmental variables that affect GNSS performance. Kriging, for instance, can model the spatial distribution of errors, allowing researchers to predict where inaccuracies are likely to occur based on environmental conditions (Ge & Xie, 2023). This approach is particularly useful for urban planners and environmental scientists who need to account for spatial biases in their data.

9. Machine Learning-Based Accuracy Prediction

In recent years, machine learning techniques have emerged as a powerful tool for predicting GNSS accuracy based on environmental factors. Models such as decision trees, random forests, and neural networks use historical GNSS data and environmental conditions to predict likely accuracy levels before data collection occurs.

Machine learning models can analyze vast amounts of data to identify patterns and predict GNSS performance in challenging environments, such as areas with poor satellite visibility or extreme weather conditions (Kim & Park, 2022). This predictive capability enables GIS professionals to anticipate accuracy issues and adjust their data collection strategies accordingly, making machine learning an invaluable tool for improving GNSS reliability.

Conclusion

The evaluation of GNSS receiver accuracy is critical to ensuring the reliability of spatial data in GIS applications. Recent advancements in evaluation methods, such as RMSE, CEP, DOP analysis, and machine learning-based prediction, provide powerful tools for assessing and improving GNSS accuracy. These methods allow GIS professionals to make informed decisions about the reliability of their GNSS receivers, ensuring that spatial data collection workflows are optimized for accuracy and precision. The growing use of multi-constellation GNSS receivers and differential correction techniques further enhances the accuracy of positional data, making these methods indispensable for modern GIS applications.

References

Ge, M., & Xie, X. (2023). Geostatistical Approaches in GNSS Accuracy Analysis. GIScience Journal.

Groves, P. (2020). Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems.

Hofmann-Wellenhof, B., & Lichtenegger, H. (2020). GNSS: Global Navigation Satellite Systems – Applications and Challenges.

Kaplan, E. D., & Hegarty, C. (2017). Understanding GPS/GNSS: Principles and Applications.

Kim, Y. K., & Park, S. H. (2022). Machine Learning for GNSS Accuracy Prediction in Challenging Environments. Sensors.

Lachapelle, G., & El-Rabbany, A. (2021). Understanding GNSS Errors and Performance Metrics. GNSS Solutions.

Langley, R. B. (2023). Circular Error Probable in GNSS Accuracy Assessment. Navigation Journal.

Li, Y., & Zhang, L. (2022). Kinematic Testing for GNSS Receivers: A Review. International Journal of Navigation and Observation.

Misra, P., & Enge, P. (2019). Global Positioning System: Signals, Measurements, and Performance.

Rizos, C., & Wang, J. (2022). Evaluating GNSS Receiver Accuracy Using RMSE. Journal of Geodesy.

Wubbena, G., & Seeber, G. (2021). Multi-Constellation GNSS in Complex Environments. Journal of GNSS Engineering.

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Enhancing Smartphone GNSS Accuracy with External Receivers

By Shahabuddin Amerudin

In an era driven by digital navigation and geospatial accuracy, the fusion of smartphones and external GNSS receivers has revolutionized positioning capabilities. With the proliferation of location-based services, achieving sub-meter accuracy with smartphones has become a tantalizing possibility. In this article, we explore how to realize this feat, including a dive into cost-effective external receivers that can elevate your smartphone’s positioning prowess.

Smartphone GNSS: The Foundation

Modern smartphones are equipped with built-in GNSS modules that tap into constellations like GPS, GLONASS, Galileo, and BeiDou, providing basic positioning services. However, their inherent limitations, such as susceptibility to signal obstructions and variations in accuracy, have led to the exploration of supplementary solutions.

The Pursuit of Sub-Meter Accuracy

To bridge the gap to sub-meter accuracy, external GNSS receivers come into play. These devices are designed to amplify smartphone GNSS capabilities by leveraging advanced technologies and precision-focused designs. By coupling the external receiver with your smartphone, you’re set to unlock unparalleled accuracy across various applications.

Selecting the Right External Receiver

Cost-effectiveness is a key consideration, as professional-grade accuracy doesn’t have to come at exorbitant prices. Here are some external GNSS receivers that strike a balance between performance and affordability:

  1. Emlid Reach RS2: A popular choice in the surveying and mapping community, the Reach RS2 offers RTK functionality at a reasonable price point. With sub-centimeter accuracy and real-time corrections via LoRa radio, it empowers precision.
  2. Bad Elf GNSS Surveyor: This Bluetooth-enabled receiver is a versatile solution for sub-meter accuracy. It pairs seamlessly with smartphones and tablets, serving applications ranging from agriculture to outdoor recreational activities.
  3. Geneq iSXBlue RTN: Featuring real-time kinematic capabilities, the iSXBlue RTN offers a cost-effective entry into high-accuracy positioning. Its robust performance makes it a reliable companion for GIS data collection.
  4. Swift Navigation Piksi Multi: Combining affordability with centimeter-level accuracy, the Piksi Multi stands out with multi-constellation support and the flexibility to cater to a variety of industries.
  5. Trimble R1 GNSS Receiver: This compact device pairs with smartphones via Bluetooth, enhancing accuracy with sub-meter precision. Its rugged design suits outdoor environments.

Achieving Sub-Meter Accuracy: The Process

The journey toward sub-meter accuracy involves a sequence of steps:

  1. Research and Compatibility: Select an external receiver compatible with your smartphone’s operating system and connectivity options (Bluetooth, USB, etc.).
  2. Receiver Setup: Follow manufacturer guidelines to set up the external receiver. This typically involves connecting it to your smartphone and installing relevant apps or software.
  3. Signal Optimization: Ensure unobstructed line-of-sight to the sky. Minimize interference from surrounding structures and electronic devices.
  4. Augmentation Services: Some external receivers support correction services like SBAS/WAAS. Enable these services to enhance accuracy further.
  5. App Integration: Download and configure compatible apps that leverage the external receiver’s capabilities. These apps might provide real-time positioning data and error correction.
  6. Data Collection: Engage in data collection activities, leveraging the enhanced accuracy of the external receiver. Record and store data for analysis and mapping.

Balancing Performance and Budget

Cost considerations play a pivotal role when selecting an external receiver. While high-end solutions exist, an array of mid-range options empowers users with remarkable sub-meter accuracy without straining their wallets.

In your quest for sub-meter accuracy, the alliance between smartphones and external GNSS receivers holds transformative potential. The landscape of navigation, mapping, and surveying is evolving, and achieving pinpoint accuracy has never been more accessible. With a calculated approach to selecting the right receiver and optimizing your smartphone’s capabilities, you’re poised to navigate the realms of sub-meter accuracy in the palm of your hand.

Suggestion for Citation:
Amerudin, S. (2023). Enhancing Smartphone GNSS Accuracy with External Receivers. [Online] Available at: https://people.utm.my/shahabuddin/?p=6620 (Accessed: 14 August 2023).
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Unleashing Sub-Meter Accuracy with L1 and L5 GNSS Frequencies

By Shahabuddin Amerudin

Introduction

In the realm of modern navigation and geospatial technology, achieving unparalleled accuracy has become a driving force. As industries and individuals seek to unlock the potential of location-based services, the fusion of advanced GNSS technology with smartphones and external receivers has become a game-changer. One of the pivotal benchmarks in this quest is the pursuit of sub-meter accuracy – a feat that was once confined to specialized equipment but is now within reach through innovative approaches.

The confluence of two significant GNSS frequency bands, L1 and L5, stands as a beacon of hope for realizing sub-meter accuracy. These bands, each with its unique advantages, offer the promise of enhanced precision by addressing challenges like ionospheric delays and multipath interference. In this article, we embark on a journey to explore how the strategic combination of L1 and L5 frequencies, harnessed through dual-frequency GNSS receivers, holds the key to unlocking sub-meter accuracy. We delve into the science behind the synergy and the tangible benefits it brings to a range of applications that demand precision.

Let’s delve into how this can be accomplished:

  1. L1 and L5 Bands Overview
    • L1 Band (1575.42 MHz): This is the primary frequency used by most GNSS constellations (GPS, Galileo, BeiDou, and QZSS). L1 provides standard positioning accuracy, typically ranging from a few meters to around a meter.
    • L5 Band (1176.45 MHz): The L5 frequency is designed to improve accuracy and reliability. It is used by some modernized GNSS systems, such as GPS L5 and Galileo E5a. L5 offers better resistance to ionospheric disturbances and multipath interference, contributing to enhanced accuracy.
  2. Combining L1 and L5 for Sub-Meter Accuracy
    • Ionospheric Correction: The L5 band’s resistance to ionospheric delays is a key advantage. Ionospheric delays can cause inaccuracies in positioning, especially for signals in the L1 band. By combining L1 and L5 measurements, you can mitigate the effects of ionospheric delays and improve overall accuracy.
    • Multipath Reduction: Multipath interference occurs when GNSS signals reflect off surfaces before reaching the receiver. The L5 band’s design helps reduce multipath effects, contributing to more accurate positioning.
  3. Dual-Frequency Receivers
    • Achieving sub-meter accuracy with L1 and L5 involves using dual-frequency GNSS receivers. These receivers track signals from both L1 and L5 bands simultaneously.
    • Dual-frequency receivers leverage the different signal propagation characteristics of L1 and L5 to correct for ionospheric delays and multipath effects. This leads to more accurate position solutions.
  4. RTK and Precise Point Positioning (PPP)
    • Real-Time Kinematic (RTK) and Precise Point Positioning (PPP) techniques benefit significantly from dual-frequency GNSS receivers.
    • RTK involves receiving real-time corrections from a base station to achieve centimeter-level accuracy. Dual-frequency receivers enhance the accuracy of RTK solutions by leveraging L1 and L5 measurements.
    • PPP uses precise satellite orbit and clock data to achieve high accuracy without real-time corrections. Dual-frequency receivers improve PPP solutions by providing more accurate measurements to the positioning algorithm.
  5. Additional Considerations
    • While L1 and L5 combination enhances accuracy, the performance also depends on the overall quality of the GNSS receiver, signal environment, and the availability of augmentation services like SBAS.
    • Check whether your smartphone or external receiver supports tracking L1 and L5 signals and whether it can leverage the benefits of these frequencies for enhanced accuracy.

Conclusion

In the dynamic landscape of spatial data, the symbiosis of L1 and L5 GNSS frequency bands has ushered in a new era of precision. The pursuit of sub-meter accuracy, once a distant goal, has become a tangible reality for professionals and enthusiasts alike. By harnessing the power of dual-frequency GNSS receivers, we’ve uncovered a pathway to transform smartphones and external devices into instruments of remarkable accuracy.

As we conclude our exploration, it’s evident that the sub-meter accuracy achieved through L1 and L5 integration is not just a technical achievement, but a catalyst for innovation. It empowers sectors as diverse as surveying, agriculture, emergency response, and infrastructure management to operate with precision that was once unattainable. The convergence of technology and ingenuity, epitomized by the harmonious blend of L1 and L5 frequencies, has opened doors to possibilities that resonate across industries and applications.

In a world where accuracy is paramount, the amalgamation of L1 and L5 stands as a testament to human ingenuity’s capacity to redefine what’s achievable. As we navigate toward a future where sub-meter accuracy is the new normal, we’re reminded that the quest for precision knows no bounds – and the journey has only just begun.

Suggestion for Citation:
Amerudin, S. (2023). Unleashing Sub-Meter Accuracy with L1 and L5 GNSS Frequencies. [Online] Available at: https://people.utm.my/shahabuddin/?p=6618 (Accessed: 14 August 2023).
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GIS Applications That Demand Sub-Meter Accuracy

By Shahabuddin Amerudin

Sub-meter accuracy is essential for a variety of Geographic Information System (GIS) applications that require precise spatial data collection, mapping, and analysis. Here are some GIS applications that benefit from sub-meter accuracy:

  1. Surveying and Mapping: Sub-meter accuracy is crucial for professional land surveying, cadastral mapping, and creating accurate property boundaries. Surveyors rely on sub-meter accuracy to establish accurate control points and measurements.
  2. Utility Infrastructure Management: Managing utility networks, such as water, gas, and electric, requires accurate spatial data. Sub-meter accuracy ensures precise location and mapping of utility assets, helping with maintenance and network planning.
  3. Agriculture and Precision Farming: Sub-meter accuracy is vital for precision agriculture, where farmers use GIS to optimize planting, irrigation, and fertilization. Accurate data collection aids in crop monitoring and yield estimation.
  4. Environmental Monitoring: Sub-meter accuracy is crucial for tracking changes in the environment, such as habitat mapping, erosion monitoring, and vegetation analysis. Precise data collection helps in understanding ecological changes over time.
  5. Natural Resource Management: GIS applications related to forestry, mining, and wildlife management benefit from sub-meter accuracy. Accurate data is essential for sustainable resource utilization and monitoring.
  6. Transportation and Infrastructure Planning: Sub-meter accuracy aids in transportation planning, road design, and traffic management. It ensures accurate representation of road networks and helps in optimizing traffic flow.
  7. Emergency Response and Public Safety: GIS applications for emergency response require precise location data for incident management, evacuation planning, and resource allocation during disasters.
  8. Urban Planning: Urban planners use sub-meter accuracy to create accurate base maps, analyze land use patterns, and design infrastructure projects within urban environments.
  9. Construction and Engineering: Sub-meter accuracy is essential in construction layout and engineering design to ensure that structures are built to accurate specifications.
  10. Archaeology and Cultural Heritage: Sub-meter accuracy helps archaeologists and preservationists document historical sites and cultural heritage with precision, aiding in conservation efforts.
  11. Geological and Geophysical Analysis: Geologists use sub-meter accuracy to map geological formations, study fault lines, and analyze terrain characteristics.
  12. Remote Sensing and Imagery Analysis: Accurate ground control points obtained through sub-meter accuracy enhance the quality of remote sensing data analysis, such as satellite and aerial imagery interpretation.
  13. GIS Data Integration: Sub-meter accuracy ensures seamless integration of GIS data from different sources, enabling accurate overlay and analysis of spatial datasets.

While sub-meter accuracy is critical for these applications, it’s important to choose the appropriate level of accuracy based on the specific requirements of the project. In many cases, sub-meter accuracy provides a balance between precision and cost-effectiveness, making it a valuable asset in various GIS applications.

Suggestion for Citation:
Amerudin, S. (2023). GIS Applications That Demand Sub-Meter Accuracy. [Online] Available at: https://people.utm.my/shahabuddin/?p=6616 (Accessed: 14 August 2023).
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How to Achieve Sub-Meter Positioning Accuracy using Smartphone

By Shahabuddin Amerudin

Achieving sub-meter positioning accuracy using a smartphone involves utilizing a combination of techniques, technologies, and tools that optimize the device’s built-in Global Navigation Satellite System (GNSS) capabilities. While smartphones typically offer less precise positioning compared to dedicated high-end GNSS receivers, advancements in hardware and software have enabled the enhancement of smartphone-based positioning accuracy. Here’s how to achieve sub-meter accuracy:

  1. Utilize Multiple GNSS Constellations: Modern smartphones support multiple GNSS constellations, such as GPS (USA), GLONASS (Russia), Galileo (Europe), and BeiDou (China). Enabling multiple constellations improves signal reception, reduces signal obstructions, and enhances accuracy.
  2. Enable High-Precision Modes: Some smartphones have high-precision or enhanced GNSS modes that combine signals from different constellations, resulting in better accuracy. Enable these modes if available in your smartphone’s settings.
  3. Augmentation Services: Utilize augmentation services like Wide Area Augmentation System (WAAS) in the USA or Satellite-Based Augmentation System (SBAS) in other regions. These services provide correction data to enhance positioning accuracy.
  4. External GNSS Receivers: Attach an external high-precision GNSS receiver to your smartphone. These receivers offer better accuracy than built-in smartphone GNSS modules, often achieving sub-meter accuracy.
  5. Real-Time Kinematic (RTK) and Differential GNSS (DGNSS): If you’re looking for even higher accuracy, consider using RTK or DGNSS solutions. These techniques involve receiving corrections from a base station to enhance positioning accuracy. Some companies offer RTK kits that can be connected to smartphones via Bluetooth.
  6. Post-Processing: Record raw GNSS data with your smartphone and use post-processing software to enhance accuracy later. This involves comparing the raw data to reference data and applying correction algorithms.
  7. Use External Antennas: External antennas, designed for improved GNSS signal reception, can significantly enhance the accuracy of smartphone positioning. These antennas reduce signal interference caused by the human body and other obstructions.
  8. Optimize Signal Conditions: Clear line-of-sight to the sky is crucial for accurate positioning. Avoid obstructions such as buildings, trees, and tall structures that can block or reflect GNSS signals.
  9. Avoid Interference: Interference from electronic devices can affect GNSS signals. Turn off Wi-Fi, Bluetooth, and other wireless connections when using GNSS for positioning.
  10. Calibrate Sensors: Some smartphones use sensor fusion techniques to improve positioning accuracy. Calibrating sensors like accelerometers and gyroscopes can enhance the accuracy of the GNSS system.
  11. Use GNSS Positioning Apps: There are several smartphone apps available that optimize GNSS performance. These apps provide real-time information about satellite visibility, signal quality, and accuracy.
  12. Combine with Other Sensors: Integrating data from other sensors like accelerometers, gyroscopes, and barometers can improve positioning accuracy, especially in areas with weak GNSS signal reception.

It’s important to note that achieving sub-meter accuracy with a smartphone might still have limitations, especially in challenging environments like urban canyons or densely vegetated areas. The choice of method depends on the specific requirements of your application and the level of accuracy needed. Always stay updated with the latest software updates and improvements for your smartphone’s GNSS capabilities.

Suggestion for Citation:
Amerudin, S. (2023). How to Achieve Sub-Meter Positioning Accuracy using Smartphone. [Online] Available at: https://people.utm.my/shahabuddin/?p=6614 (Accessed: 14 August 2023).