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Knowledge-based virtual outdoor weather event simulator using unity 3D

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Abstract

During the past two decades, 3D simulation models have gained importance in the development of software solutions that aim to mimic real-world events and phenomena with increasing levels of accuracy and detail. In this context, knowledge representation and processing have recently shown a significant contribution to the simulation modeling domain, where knowledge graphs have been used in different fields to build knowledge representations for multiple purposes. In this paper, we introduce VOWES, a Virtual Outdoor Weather Event Simulator to replicate and measure outdoor weather events in vivid 3D visualizations. We design and implement an integrated knowledge graph (KG) representation for VOWES, by creating two constituent KGs: (i) Weather KG describing weather data and events, and (ii) Simulator KG describing 3D simulation components and properties, and connecting them with the (iii) Semantic Sensor Network (SSN) KG to form an integrated structure serving as the knowledge backbone of the VOWES simulation environment. We make use of the Unity 3D engine to build and design the simulator environment and its virtual sensors, and integrate the Mapbox SDK and the WeatherStack API for realistic real-world weather mapping. We have conducted qualitative evaluations involving 13 expert and 30 non-expert testers, to assess the quality of VOWES’ KGs and its simulation environment. Results show that more than 80% of the testers gave a combined quality score ≥ 3 out of 4 on most evaluation criteria. We have also conducted performance evaluations to test VOWES loading, execution, and data search time, among other features. Results show that most operations require almost instantaneous or linear time, where search, refresh, and export operations share almost identical performance levels, with execution time increasing by approximately 179 μs for every added game object. This highlights the simulation tool’s time performance in running large simulation projects, and its ability to simulate complex weather environments with large numbers of sensors and weather phenomena.

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Notes

  1. With respect to.

  2. Institute of Electrical and Electronics Engineers.

  3. Resource Description Framework [27].

  4. Note that the location property can be substituted by any other location definition concept depending on the referential space being used (e.g., from GML [35] or KML [19] in a geo-referential space).

  5. WeatherStack API is utilized by more than 75 k companies worldwide, providing multi-year history data all the way to live information [53].

  6. Physics engines include packages allowing to simulate real-world physical properties in the virtual environment.

  7. http://sigappfr.acm.org/Projects/VOWES/.

  8. Available at: https://forms.gle/KmXeFYru9boqc23F7.

  9. The names of the participating experts are also mentioned in the acknowledgements: Caetano Traina Jr., Ph.D., Full Professor, University of Sao (USP) Paulo, Brazil, William Grosky, Ph.D., Full Professor, University of Michigan (UM), USA, Agma Traina, Ph.D., Full Professor, University of Sao (USP) Paulo, Brazil, Richard Chbeir, Full Professor, University of Pau and Pays Adour (UPPA), France, George Khazen, Ph.D., Associate Professor, Lebanese American University (LAU), Lebanon, Regina Ticona, Ph.D., Associate Professor, Catholic University of San Pablo (UCSP), Peru, Fekade Getahun, Ph.D., Associate Professor, Addis Ababa University (AAU), Ethiopia, Gilbert Tekli, Ph.D., Assistant Professor, University of Balamand (UoB), Lebanon, Khouloud Salameh, Ph.D., American University of Ras AL Khaimah (AURAK), UAE, Nathalie Charbel, Ph.D., Research Engineer, Nobatek, France, Lara Kallab, Ph.D., Research Engineer, OPEN Group, France, Sabri Allani, Ph.D., Post doc, UPPA, France, and Elio Mansour, Ph.D., Post doc, UPPA, France.

  10. https://protege.stanford.edu.

  11. Graphical User Interface.

  12. Available at: https://forms.gle/F6odKynC9pcvmCzq6.

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Acknowledgements

We also like to thank all the experts who helped evaluate our knowledge graphs: Caetano Traina Jr., Ph.D., Full Professor, University of Sao (USP) Paulo, Brazil, William Grosky, Ph.D., Full Professor, University of Michigan (UM), USA, Agma Traina, Ph.D., Full Professor, University of Sao (USP) Paulo, Brazil, Richard Chbeir, Full Professor, University of Pau and Pays Adour (UPPA), France, George Khazen, Ph.D., Associate Professor, Lebanese American University (LAU), Lebanon, Regina Ticona, Ph.D., Associate Professor, Catholic University of San Pablo (UCSP), Peru, Fekade Getahun, Ph.D., Associate Professor, Addis Ababa University (AAU), Ethiopia, Gilbert Tekli, Ph.D., Assistant Professor, University of Balamand (UoB), Lebanon, Khouloud Salameh, Ph.D., American University of Ras AL Khaimah (AURAK), UAE, Nathalie Charbel, Ph.D., Research Engineer, Nobatek, France, Lara Kallab, Ph.D., Research Engineer, OPEN Group, France, Sabri Allani, Ph.D., Post doc, UPPA, France, and Elio Mansour, Ph.D., Post doc, UPPA, France. We are also very grateful to all non-expert testers who helped evaluate our software simulation tool.

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  1. Department of Electrical and Computer Engineering, School of Engineering, Lebanese American University (LAU), Byblos, 36, Lebanon

    Hamza Noueihed, Heba Harb & Joe Tekli

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  1. Hamza Noueihed
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The author is also an adjunct researcher and member of the SPIDER research team, LIUPPA Laboratory, University of Pay and Pays Adour (UPPA), 64,600, Anglet, France.

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Noueihed, H., Harb, H. & Tekli, J. Knowledge-based virtual outdoor weather event simulator using unity 3D. J Supercomput 78, 10620–10655 (2022). https://doi.org/10.1007/s11227-021-04212-6

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