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GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
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Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Updated: Sep 10, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
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A fog-assisted group-based truth discovery framework over mobile crowdsensing data streams.

Bayan Hashr Saeed Alamri1,2, Muhammad Mostafa Monowar2, Suhair Alshehri2

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This study introduces a novel Two-layer Group-based Truth Discovery (TGTD) framework for mobile crowdsensing (MCS) data streams. TGTD enhances data accuracy in group-based MCS applications by improving truth discovery.

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Area of Science:

  • Computer Science
  • Data Science
  • Mobile Computing

Background:

  • Mobile crowdsensing (MCS) faces data inconsistency challenges due to diverse data sources.
  • Group behavior and community-level participation are increasingly influencing MCS applications.
  • Existing truth discovery (TD) methods struggle with the scale and real-time demands of MCS data streams.

Purpose of the Study:

  • To propose a novel Fog-assisted Group-based Truth Discovery Framework for MCS data streams.
  • To address data inconsistency and group dynamics in real-time MCS applications.
  • To enhance the accuracy and efficiency of truth discovery in large-scale, dynamic MCS environments.

Main Methods:

  • Developed a Two-layer Group-based Truth Discovery (TGTD) mechanism.
  • Initialized participant weights using credibility levels.
  • Integrated a fog-assisted architecture for real-time processing of MCS data streams.

Main Results:

  • The TGTD framework demonstrated superior truth discovery accuracy compared to existing streaming TD approaches.
  • The proposed framework maintained a reasonable running time, proving its efficiency.
  • Extensive experiments on synthetic and real-world datasets validated the framework's effectiveness.

Conclusions:

  • The Fog-assisted Group-based Truth Discovery Framework offers an effective solution for data inconsistency in MCS.
  • TGTD successfully handles group dynamics and real-time processing requirements.
  • Further investigation into fog architecture simulation for streaming processes is recommended for future work.