First Responders' Localization and Health Monitoring During Rescue Operations


  • Attila Simo Politehnica University Timisoara, Faculty of Electrical and Power Engineering, Romania
  • Simona Dzitac University of Oradea, Department of Energy Engineering, Romania
  • Domnica Dzitac New York University Abu Dhabi, UAE



fuzzy set theory, probabilistic graphical model, simultaneous localization and mapping


Currently, first responders’ coordination and decision-making during res-cue, firefighting or police operations is performed via radio/GSM channels with some support of video streaming. In unknown premises, officers have no global situational awareness on operation status, which reduces coordination efficiency and increases decision making mistakes. This paper pro-poses a solution enabling the situational awareness by introducing an integrated operation workflow for actors localization and health monitoring. The solution will provide global situational awareness to both coordinators and actors, thereby increasing efficiency of coordination, reducing mistakes in decision making and diminishing risks of unexpected situations to appear. This will result in faster operation progress, lower number of human casualties and financial losses and, the most important, saved human lives in calamity situations.


[1] World Health Organization Global Burden of Disease Database, 2019

[2] Fire Brigade Union, Inclusive Fire Service Group Report, 2021

[3] Fire Brigade Union, Labour Research Department, 2020

[4] INFRA project report, FP7-Security.;

[5] R. B. Rusu, S. Cousins (2011). 3D is here: Point Cloud Library (PCL). In IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China.

[6] K. Lin, C. Wang (2010). Stereo-based Simultaneous Localization, Mapping and Moving Object Tracking. IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan.

[7] A.J Davison, I. D. Reid, SN. D. Molton, O. Stasse (2007). MonoSLAM: Real-Time Single Camera SLAM, Pattern Analysis and Machine Intelligence. IEEE Transactions on pattern analysis and machine intelligence, vol.29, no.6, pp.1052-1067.

[8] F. Endres, J. Hess, N. Engelhard, J. Sturm, D. Cremers, W. Burgard (2012). An Evaluation of the RGB-D SLAM System. IEEE International Conference on Robotics and Automation (ICRA), Saint Paul, USA

[9] MoD - Mapping on Demand DFG Research Unit FOR 1505 11/2011-10/2017 -;

[10] CONTRUCT - Modelling and Surveying Large Construction Sites, 2019,;

[11] Pegasus - Mobile Vision System for Overhead Power Line Inspection, 2020,;

[12] Point Cloud Library - standalone, large scale, open project for 3D point cloud pro-cessing.;

[13] 13. T. Whelan Kaess, M. Fallon, M. Johannsson, H. Leonard, J. McDonald (2012). Kintinuous: Spatially Extended KinectFusion. Computer Science and Artificial Intelligence Lab (CSAIL).

[14] 14. F. Heredia, R. Favier (2021). Tutorial: Using Kinfu Large Scale to Generate a Textured Mesh.;

[15] N. Palmer, R. Kemp, T. Kielmann, H. Bal, Raven (2012). Using smartphones for collaborative disaster data collection. in 9th International Conference on Information Systems for Crisis Response and Management.

[16] V. Stefanidis, Y. Verginadis, I. Patiniotakis, G. Mentzas (2018). Distributed Complex Event Processing in Multiclouds. European Conference on Service-Oriented and Cloud Computing

[17] M. Shaikh, P. Helmut, K. Hirose, I. Mitsuru (2019). Easy living in the virtual world: A noble approach to integrate real world activities to virtual worlds. In: Web Intelligence and Intelligent Agent Technologies, IEEE/WIC/ACM Interna-tional Joint Conferences, 2019, volume 2

[18] S. Fleck, W. Strasser (2018). Smart camera based monitoring system and its application to assisted living. Proceedings of the IEEE, 2018 Vol. 96 (10), pp. 1698-1714.

[19] R. Maciejewski, S. Rudolph, R. Hafen, A. Abusalah, M. Yakout, M. Ouzzani, W.S. Cleveland , S.J. Grannis, D.S. Ebert. A Visual Analytics Approach to Understanding Spatiotemporal Hotspots. IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 2.

[20] S.Vashi, J. Ram, J. Modi, S. Verma, C. Prakash (2017). Internet of Things (IoT): A vision, architectural elements, and security issues. International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC),Palladam, India

[21] L.M.C. Herrera, W. Y. Campo-Muñoz, A. D. Torres (2021). First Responders' Localization and Health Monitoring During Rescue Operations, International Journal of Computers Communications & Control, Vol. 16, No. 5

[22] M. Pakanen, L. Arhippainen, S. Hickey, A. Karhu (2013). Visual Indication of Interactive 3D Elements in 3D Virtual Environments. Proceedings of International Conference on Making Sense of Converging Media, Tampere Finland

[23] Y. Wu, Y.Sui, G. Wang (2017). Vision-based Real-Time Aerial Object Localization and Tracking for UAV Sensing System. IEEE Access, Vol. 5.

[24] J. Zhang, S. Sclaroff, Z. Lin, X. Shen, B. Price, R. Mech (2015). Minimum barrier salient object detection at 80 fps. Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 1404-1412.

[25] 25. S. Kontogiannis, G. Kokkonis (2020). Proposed Fuzzy Real-Time HaPticS Protocol Carrying Haptic Data and Multisensory Streams. International Journal of Computers Communications & Control, Vol. 15, No. 4.

[26] 26. R. Haina, G. Mianjun, Z. Gexiang, Z. Ming (2018). An Approach for Detecting Fault Lines in a Small Current Grounding System using Fuzzy Reasoning Spiking Neural P Systems. International Journal of Computers Communications & Control, Vol. 13, No. 4.

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