Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

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 served as...
Orthogonal Trajectories01:26

Orthogonal Trajectories

Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

From vibe coding to vibe caring: what clinicians can learn.

Lancet (London, England)·2025
Same author

Relationships between fixed-site ambient measurements of nitrogen dioxide, ozone, and particulate matter and personal exposures in Grand Paris, France: the MobiliSense study.

International journal of health geographics·2025
Same author

Should AI models be explainable to clinicians?

Critical care (London, England)·2024
Same author

Corticosteroid sensitivity detection in sepsis patients using a personalized data mining approach: A clinical investigation.

Computer methods and programs in biomedicine·2024
Same author

NO<sub>2</sub>, BC and PM Exposure of Participants in the Polluscope Autumn 2019 Campaign in the Paris Region.

Toxics·2023
Same author

Understanding who talks about what: comparison between the information treatment in traditional media and online discussions.

Scientific reports·2023

Related Experiment Video

Updated: Jul 8, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.9K

Towards a semantic indoor trajectory model: application to museum visits.

Alexandros Kontarinis1,2, Karine Zeitouni2, Claudia Marinica1

  • 1ETIS UMR8051, ENSEA, CNRS, CY Cergy Paris University, F-95000 Cergy, France.

Geoinformatica
|March 10, 2021
PubMed
Summary

This study introduces a novel model for indoor trajectories, integrating semantic and spatial data for advanced mobility data mining. It enables new context-aware analytics for indoor spaces, demonstrated with a museum case study.

Keywords:
Big dataIndoor trajectoryLouvre museumMuseum visitor studySemantic trajectoryTrajectory modelingTrajectory pattern mining

More Related Videos

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.9K
Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects
06:36

Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects

Published on: October 18, 2024

1.2K

Related Experiment Videos

Last Updated: Jul 8, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.9K
Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.9K
Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects
06:36

Author Spotlight: Insights into the Analysis of Human Interaction with 3D Virtual Objects

Published on: October 18, 2024

1.2K

Area of Science:

  • Geographic Information Science
  • Data Mining
  • Spatial Analytics

Background:

  • Limited research exists on indoor trajectory modeling, hindering context-aware data mining.
  • Existing outdoor trajectory models do not adequately capture indoor space semantics and hierarchy.
  • Museums present complex indoor environments requiring specialized trajectory analysis.

Purpose of the Study:

  • To propose a new conceptual model for indoor trajectories incorporating semantic and spatial information.
  • To support the development of context-aware mobility data mining and statistical analytics for indoor spaces.
  • To address overlooked modeling issues in indoor trajectory research.

Main Methods:

  • Combined state-of-the-art semantic outdoor trajectory models with a semantically-enabled hierarchical symbolic representation of indoor space.
  • Utilized the OGC's IndoorGML standard for indoor space representation.
  • Illustrated the model with a case study of the Louvre Museum, including visiting data analysis.

Main Results:

  • Demonstrated the applicability of state-of-the-art data mining algorithms on the proposed indoor trajectory model.
  • Showcased the advantages and limitations of the model through experimental results.
  • Presented a formal outline of a new sequential pattern mining algorithm for trajectory patterns.

Conclusions:

  • The proposed model effectively integrates semantic and indoor space information for trajectory analysis.
  • The model facilitates context-aware mobility data mining and statistical analytics in complex indoor environments.
  • The new sequential pattern mining algorithm offers enhanced capabilities for extracting meaningful trajectory patterns.