Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 171–177, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-171-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 171–177, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-171-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  18 Oct 2019

18 Oct 2019

DESIGNING A CONTEXT-AWARE RECOMMENDER SYSTEM IN THE OPTIMIZATION OF THE RELIEF AND RESCUE

N. Bahrami1, M. Argany1, N. N. Samani1, and A. R. Vafaeinejad2 N. Bahrami et al.
  • 1Department of RS & GIS, Factually of Geography, University of Tehran, Tehran, Iran
  • 2Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University , Tehran, Iran

Keywords: Context-aware, Optimization, Relief & Rescue, Particle Swarm Optimization, Geospatial Information System, Earthquake

Abstract. The context-aware is the knowledge that leads to better cognition and recognition of the environment, objects and factors, and the way of communication and interactions between them. As a result, it can have a great impact in providing appropriate solutions to various problems. It is possible to integrate consciousness into relief and rescue discussions and to take steps to improve and make realistic solutions. In this study, this issue was addressed in the earthquake crisis, due to a large number of seismic faults in Iran, is one of the major crises in Iran and many parts of the world. Hence, the contexts of rescuers, teams, and environment as the main textures in the above-mentioned issue are investigated and their relationship with each other and the priorities of activities and locations by identifying specialties and the physical and situational conditions of the relief workers, and an algorithm was designed and optimized to optimize the allocation of the relief workers to the affected areas and the necessary activities. Finally, the improvement of the 2.4 fold results of the algorithm and the proposed structure of this research resulted in the ratio of non-use of this algorithm.