Developing a Robust Emergency Information System for Natural Disasters

Konstantinos Papatheodosiou; Chrissanthi Angeli

doi:doi:10.11648/j.acis.20231101.12

| Peer-Reviewed

Developing a Robust Emergency Information System for Natural Disasters

Konstantinos Papatheodosiou, Chrissanthi Angeli

Published in Automation, Control and Intelligent Systems (Volume 11, Issue 1)

Received: 14 February 2023 Accepted: 7 March 2023 Published: 16 March 2023

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

A lot of Emergency Information Systems have been developed to inform people about impending emergencies. Most of them are part of an integrated system, collaborating with a respective warning system. No matter which technology is employed in the development process, an Emergency Information System aspires to deliver emergency content accurately and rapidly. Most of Emergency Information Systems transmit the emergency content in a predetermined geographical area. In parallel, a typical DRM Emergency Information System doesn’t vouch for transmission accuracy in the case of a possible communication loss or a power outage. This paper presents a DRM-based Emergency Information System that works well in remote areas with rough geographical terrain, offsetting a possible communication loss or a possible power outage. An efficient broadcast selection algorithm has been developed to answer this purpose. The paper also indicates the maximum coverage of the underlying system, in a mountainous area (Vigla), taking advantage of a standard methodology called " LEGBAC”. Specific software was used to come up with the wide area coverage map. The results proved that our system achieved maximum coverage in any antenna calibration (99% approximately) and the value of the respective signal strength was not significantly altered by the increase in the number of kilometers away from the transmission center, indicating the robustness of our system and the competency of the broadcast selection algorithm.

Published in	Automation, Control and Intelligent Systems (Volume 11, Issue 1)
DOI	10.11648/j.acis.20231101.12
Page(s)	8-14
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Warning System, Coverage Prediction, Emergency Information System

References

[1]	Endsley, M. R., Bolte, B., & Jones, D. G. (2011). Designing for situation awareness: An approach to human-centered design (2nd ed.). NW, USA: Taylor & Francis.
[2]	Jennex, M. E. (2007). Modeling emergency response systems. In H. I. Waikoloa (Ed.), Proceedings of the 40th Annual Hawaii International Conference on system sciences (HICSS 2007). Washington, DC: IEEE Computer Society.
[3]	Hameed, S. A., Hassan, A., Shabnam, S., Miho, V., & Khalifa, O. (2008). An efficient emergency, healthcare, and medical information system. International Journals of Biometric and Bioinformatics (IJBB), 2 (5), 1-9.
[4]	Bishop, R. O., Patrick, J., & Besiso, A. (2015). Efficiency achievements from a user-developed real-time modifiable clinical information system. Annals of emergency medicine, 65 (2), 133-142.
[5]	Kang, B., Choo, H. (2016). A deep-learning-based emergency alert system. Science Direct.
[6]	Siergiejczyk, M. (2015). Analysis Of The Analogue And Digital Cooperation Of The Railway Radio Communications in the Context of the Emergency Call. Journal of KONES Powertrain and Transport, Vol. 22, No. 4.
[7]	Khalid M., Shafiai S. (2015). Flood Disaster Management in Malaysia: An Evaluation of the Effectiveness Flood Delivery System. Journal of Social Science and Humanity, Vol. 5, No. 4.
[8]	Shabrina, N. H. (2017). Simulation of Digital Radio Mondiale (DRM) Coverage Prediction–A study case with Radio Republic Indonesia (RRI). IJNMT (International Journal of New Media Technology), 4 (1), 32-36.
[9]	Kumar, N., & Khan, R. A. (2017). Emergency Information System Architecture for Disaster Management: Metro City Perspective. International Journal of Advanced Research in Computer Science, 8 (5).
[10]	El-Dinary, A., (2018). Systems and Methods for Emergency Vehicle Proximity Warning Using Digital Radio Broadcast. United States Patent. Pub. No. US 9, 986, 401 B2.
[11]	Kubát, D., Kviz, J., Skrbek J., Žižka, T. (2012). Distributing Emergency Traffic Information. 20th IDMT Conference.
[12]	Isaacson, J. E., Joiner, A. P., Kozhumam, A. S., Caruzzo, N. M., de Andrade, L., Iora, P. H.,... & Vissoci, J. R. N. (2021). Emergency Care Sensitive Conditions in Brazil: A Geographic Information System Approach to Timely Hospital Access. The Lancet Regional Health-Americas, 4, 100063.
[13]	Lien, Y., Jang, H., Chail, T. (2009). A MANET-Based Emergency Communication and Information System for Catastrophic Natural Disasters. In: 29th IEEE International Conference on Distributed Computing Systems Workshops.
[14]	Ngiam J., Coates, A., Lahiri A., Prochnow B., Q. V. Le, A. Y., Ng. (2011). On optimization methods for deep learning. In: Proceedings of the 28th International Conference on Machine Learning (ICML-11), 265–272.
[15]	Ridderinkhof K, Forstmann, S. A., Wylie, B. Burle, W. P. van den Wildenberg. (2011). Neurocognitive mechanisms of action control: resisting the call of the sirens. Wiley Interdiscip. Rev. Cogn. Sci. 2 (2), 174–192.
[16]	Stadelmeier, L., Kan, M., Loghin, D., Schneider, J., Ner, I., Lachlan, B., Shinohara, Y., Atungsiri, S., Gholam, H., Taylor M. (2016). Transmitter and Transmission Method for Transmitting Payload Data and Emergency Information. United States Patent Application. Pub. No. US 2016/0094895 A1.
[17]	Sutskever, I., Martens J., Dahl, G., Hinton, G. (2013). On the importance of initialization and momentum in deep learning. In: Proceedings of the 30th International Conference on Machine Learning, ICML13, 1139–1147.
[18]	Tarchi D., Fantacci, R., and Marabissi D. (2009). The communication infrastructure for emergency management: the integrated system for emergency vision”. In Proceedings of IWCMC.
[19]	Tubtiang, A. (2005). Role of ICT for Disaster Reduction, Bangkok, Thailand.
[20]	Velazquez, L., Ford, J. (2012). Methods and Apparatus for Transmitting Emergency Alert Messages. United States Patent Application. Pub. No. US 8, 250, 598 B2.
[21]	Yang, Y., Yin, J., Ye, M., She, D., & Yu, J. (2020). Multi-coverage optimal location model for emergency medical service (EMS) facilities under various disaster scenarios: a case study of urban fluvial floods in the Minhang district of Shanghai, China. Natural Hazards and Earth System Sciences, 20 (1), 181-195.
[22]	Maryam, H., Javaid, Q., Shah, M., Kamrad M. (2016). A Survey on Smartphones Systems for Emergency Management (SPSEM). International Journal of Advanced Computer Science and Applications, Vol. 7, No. 6.
[23]	Ellingson, St. (2016). Radio Systems Engineering. Cambridge University Press, 1–4. ISBN 978-1316785164.
[24]	Proloy, R., Ahmed, S. Hossain, A. (2017). Comparative Analysis of Various Wireless Digital Modulation Techniques with different Channel Coding Schemes under AWGN Channel. International Journal of Computer Applications (0975 – 8887), Vol. 161, No 3.
[25]	Mattsson, A. (2005). Single frequency networks. In DTV IEEE transactions on broadcasting, 51 (4), 413-422.
[26]	K. Papatheodosiou, C. Angeli (2020). Developing an emergency Information System: A Literature Review, The 34th European Simulation and Modeling Conference ESM (2020), Toulouse, FRANCE, pp. 87-92.
[27]	K. Papatheodosiou, C. Angeli (2021). Designing an emergency Information System for Catastrophic Natural Situations, The 35th European Simulation and Modelling Conference ESM (2021), October 27-29, Rome, ITALY.
[28]	K. Papatheodosiou, C. Angeli (2021) Designing an emergency Information System for Catastrophic Natural Situations, Journal on Policy and Complex Systems, Volume 7, Number 2, Fall 2021, pp. 69-79.
[29]	K. Papatheodosiou, C. Angeli (2022) Efficient Transmission of Emergency Alert Messages in Case of Natural Disasters, The 36th European Simulation and Modelling Conference ESM (2022), October 28-31, Porto, PORTUGAL.
[30]	AIR, All India Radio: AIR–DRM. Available at drm.org.

Cite This Article

Plain Text BibTeX RIS

APA Style

Konstantinos Papatheodosiou, Chrissanthi Angeli. (2023). Developing a Robust Emergency Information System for Natural Disasters. Automation, Control and Intelligent Systems, 11(1), 8-14. https://doi.org/10.11648/j.acis.20231101.12

Copy | Download

ACS Style

Konstantinos Papatheodosiou; Chrissanthi Angeli. Developing a Robust Emergency Information System for Natural Disasters. Autom. Control Intell. Syst. 2023, 11(1), 8-14. doi: 10.11648/j.acis.20231101.12

Copy | Download

AMA Style

Konstantinos Papatheodosiou, Chrissanthi Angeli. Developing a Robust Emergency Information System for Natural Disasters. Autom Control Intell Syst. 2023;11(1):8-14. doi: 10.11648/j.acis.20231101.12

Copy | Download

@article{10.11648/j.acis.20231101.12,
  author = {Konstantinos Papatheodosiou and Chrissanthi Angeli},
  title = {Developing a Robust Emergency Information System for Natural Disasters},
  journal = {Automation, Control and Intelligent Systems},
  volume = {11},
  number = {1},
  pages = {8-14},
  doi = {10.11648/j.acis.20231101.12},
  url = {https://doi.org/10.11648/j.acis.20231101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20231101.12},
  abstract = {A lot of Emergency Information Systems have been developed to inform people about impending emergencies. Most of them are part of an integrated system, collaborating with a respective warning system. No matter which technology is employed in the development process, an Emergency Information System aspires to deliver emergency content accurately and rapidly. Most of Emergency Information Systems transmit the emergency content in a predetermined geographical area. In parallel, a typical DRM Emergency Information System doesn’t vouch for transmission accuracy in the case of a possible communication loss or a power outage. This paper presents a DRM-based Emergency Information System that works well in remote areas with rough geographical terrain, offsetting a possible communication loss or a possible power outage. An efficient broadcast selection algorithm has been developed to answer this purpose. The paper also indicates the maximum coverage of the underlying system, in a mountainous area (Vigla), taking advantage of a standard methodology called " LEGBAC”. Specific software was used to come up with the wide area coverage map. The results proved that our system achieved maximum coverage in any antenna calibration (99% approximately) and the value of the respective signal strength was not significantly altered by the increase in the number of kilometers away from the transmission center, indicating the robustness of our system and the competency of the broadcast selection algorithm.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Developing a Robust Emergency Information System for Natural Disasters
AU  - Konstantinos Papatheodosiou
AU  - Chrissanthi Angeli
Y1  - 2023/03/16
PY  - 2023
N1  - https://doi.org/10.11648/j.acis.20231101.12
DO  - 10.11648/j.acis.20231101.12
T2  - Automation, Control and Intelligent Systems
JF  - Automation, Control and Intelligent Systems
JO  - Automation, Control and Intelligent Systems
SP  - 8
EP  - 14
PB  - Science Publishing Group
SN  - 2328-5591
UR  - https://doi.org/10.11648/j.acis.20231101.12
AB  - A lot of Emergency Information Systems have been developed to inform people about impending emergencies. Most of them are part of an integrated system, collaborating with a respective warning system. No matter which technology is employed in the development process, an Emergency Information System aspires to deliver emergency content accurately and rapidly. Most of Emergency Information Systems transmit the emergency content in a predetermined geographical area. In parallel, a typical DRM Emergency Information System doesn’t vouch for transmission accuracy in the case of a possible communication loss or a power outage. This paper presents a DRM-based Emergency Information System that works well in remote areas with rough geographical terrain, offsetting a possible communication loss or a possible power outage. An efficient broadcast selection algorithm has been developed to answer this purpose. The paper also indicates the maximum coverage of the underlying system, in a mountainous area (Vigla), taking advantage of a standard methodology called " LEGBAC”. Specific software was used to come up with the wide area coverage map. The results proved that our system achieved maximum coverage in any antenna calibration (99% approximately) and the value of the respective signal strength was not significantly altered by the increase in the number of kilometers away from the transmission center, indicating the robustness of our system and the competency of the broadcast selection algorithm.
VL  - 11
IS  - 1
ER  -

Copy | Download

Author Information

Konstantinos Papatheodosiou

School of Engineering, Department of Mechanical Engineering, University of West Attica, Athens, Greece
Chrissanthi Angeli

School of Engineering, Department of Electrical and Electronics Engineering, University of West Attica, Athens, Greece

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Konstantinos Papatheodosiou, Chrissanthi Angeli. (2023). Developing a Robust Emergency Information System for Natural Disasters. Automation, Control and Intelligent Systems, 11(1), 8-14. https://doi.org/10.11648/j.acis.20231101.12

Copy | Download

ACS Style

Konstantinos Papatheodosiou; Chrissanthi Angeli. Developing a Robust Emergency Information System for Natural Disasters. Autom. Control Intell. Syst. 2023, 11(1), 8-14. doi: 10.11648/j.acis.20231101.12

Copy | Download

AMA Style

Konstantinos Papatheodosiou, Chrissanthi Angeli. Developing a Robust Emergency Information System for Natural Disasters. Autom Control Intell Syst. 2023;11(1):8-14. doi: 10.11648/j.acis.20231101.12

Copy | Download

@article{10.11648/j.acis.20231101.12,
  author = {Konstantinos Papatheodosiou and Chrissanthi Angeli},
  title = {Developing a Robust Emergency Information System for Natural Disasters},
  journal = {Automation, Control and Intelligent Systems},
  volume = {11},
  number = {1},
  pages = {8-14},
  doi = {10.11648/j.acis.20231101.12},
  url = {https://doi.org/10.11648/j.acis.20231101.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20231101.12},
  abstract = {A lot of Emergency Information Systems have been developed to inform people about impending emergencies. Most of them are part of an integrated system, collaborating with a respective warning system. No matter which technology is employed in the development process, an Emergency Information System aspires to deliver emergency content accurately and rapidly. Most of Emergency Information Systems transmit the emergency content in a predetermined geographical area. In parallel, a typical DRM Emergency Information System doesn’t vouch for transmission accuracy in the case of a possible communication loss or a power outage. This paper presents a DRM-based Emergency Information System that works well in remote areas with rough geographical terrain, offsetting a possible communication loss or a possible power outage. An efficient broadcast selection algorithm has been developed to answer this purpose. The paper also indicates the maximum coverage of the underlying system, in a mountainous area (Vigla), taking advantage of a standard methodology called " LEGBAC”. Specific software was used to come up with the wide area coverage map. The results proved that our system achieved maximum coverage in any antenna calibration (99% approximately) and the value of the respective signal strength was not significantly altered by the increase in the number of kilometers away from the transmission center, indicating the robustness of our system and the competency of the broadcast selection algorithm.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Developing a Robust Emergency Information System for Natural Disasters
AU  - Konstantinos Papatheodosiou
AU  - Chrissanthi Angeli
Y1  - 2023/03/16
PY  - 2023
N1  - https://doi.org/10.11648/j.acis.20231101.12
DO  - 10.11648/j.acis.20231101.12
T2  - Automation, Control and Intelligent Systems
JF  - Automation, Control and Intelligent Systems
JO  - Automation, Control and Intelligent Systems
SP  - 8
EP  - 14
PB  - Science Publishing Group
SN  - 2328-5591
UR  - https://doi.org/10.11648/j.acis.20231101.12
AB  - A lot of Emergency Information Systems have been developed to inform people about impending emergencies. Most of them are part of an integrated system, collaborating with a respective warning system. No matter which technology is employed in the development process, an Emergency Information System aspires to deliver emergency content accurately and rapidly. Most of Emergency Information Systems transmit the emergency content in a predetermined geographical area. In parallel, a typical DRM Emergency Information System doesn’t vouch for transmission accuracy in the case of a possible communication loss or a power outage. This paper presents a DRM-based Emergency Information System that works well in remote areas with rough geographical terrain, offsetting a possible communication loss or a possible power outage. An efficient broadcast selection algorithm has been developed to answer this purpose. The paper also indicates the maximum coverage of the underlying system, in a mountainous area (Vigla), taking advantage of a standard methodology called " LEGBAC”. Specific software was used to come up with the wide area coverage map. The results proved that our system achieved maximum coverage in any antenna calibration (99% approximately) and the value of the respective signal strength was not significantly altered by the increase in the number of kilometers away from the transmission center, indicating the robustness of our system and the competency of the broadcast selection algorithm.
VL  - 11
IS  - 1
ER  -

Copy | Download