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Computer Science and Education in Computer Science. 19th EAI International Conference, CSECS 2023, Boston, MA, USA, June 28–29, 2023, Proceedings

Research Article

An Approach to Environmental Study from Observations and Sensing Towards a Digital Twin

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-44668-9_20,
        author={Rossitza Goleva and Alexandar Savov and Vasko Tomanov and Valentin Monov and Zhivka Koleva and Radosveta Sokullu and Hristina Kostadinova and Svetoslav Mihaylov and Nuno Garcia},
        title={An Approach to Environmental Study from Observations and Sensing Towards a Digital Twin},
        proceedings={Computer Science and Education in Computer Science. 19th EAI International Conference, CSECS 2023, Boston, MA, USA, June 28--29, 2023, Proceedings},
        proceedings_a={CSECS},
        year={2023},
        month={10},
        keywords={Sensors Digital Twins Data Sharing Edge Dew Fog Cloud Computing Technologies Risk Analyses Disaster Prediction},
        doi={10.1007/978-3-031-44668-9_20}
    }
    
  • Rossitza Goleva
    Alexandar Savov
    Vasko Tomanov
    Valentin Monov
    Zhivka Koleva
    Radosveta Sokullu
    Hristina Kostadinova
    Svetoslav Mihaylov
    Nuno Garcia
    Year: 2023
    An Approach to Environmental Study from Observations and Sensing Towards a Digital Twin
    CSECS
    Springer
    DOI: 10.1007/978-3-031-44668-9_20
Rossitza Goleva1,*, Alexandar Savov, Vasko Tomanov, Valentin Monov, Zhivka Koleva, Radosveta Sokullu, Hristina Kostadinova1, Svetoslav Mihaylov, Nuno Garcia
  • 1: New Bulgarian University
*Contact email: rgoleva@gmail.com

Abstract

Long-term well-living is highly correlated to the level of environmental studies. Arctic ice melting, global warming, storms, and forest fires occur more and more often. In the process of digitalization of life, a new technology of digital twins is becoming appropriate for better studies and prediction of disasters. Many papers and projects have been focused on wildfires last decade and some of them present the idea of forest fire simulation. In this work, we present an IoT-cloud-digital twin solution where a new sensor for environment sensing is developed, integrated with the drone observations of the area, and feeding the database on the server locally and in the cloud with fresh data from the observation. All data collected in real-time, near-real-time, and non-real-time feed a digital twin model where the fires are simulated. The unique combination of real data and simulated data in the virtual environment allows better prediction of disasters, coordination in prevention procedures, and clear analyses of the risk for the environment and citizens.

Keywords
Sensors Digital Twins Data Sharing Edge Dew Fog Cloud Computing Technologies Risk Analyses Disaster Prediction
Published
2023-10-11
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-44668-9_20
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