Artificial Intelligence Technique Based Effective Disaster Recovery Framework to Provide Longer Time Connectivity in Mobile Ad-hoc Networks

Authors

  • Nismon Rio Robert Robert
  • A. Cecil Donald
  • K. Suresh

DOI:

https://doi.org/10.22399/ijcesen.713

Keywords:

Artificial Intelligence, Neural Network, Geographical Information System, Greedy Randomized Adaptive, Search Procedure

Abstract

Communication plays a vital role for effective management and for the execution of disaster response and emergency recovery efforts must be able to exchange information with each other from anywhere, at any time to successfully fulfill their missions. Therefore, it is important to configure emergency communications networks in disaster conditions using ad-hoc networks. This proposed framework collects the information and communication before or after a disaster. The aim of this research work is to propose a possible practical communication model by using ad-hoc network configuration technologies using Greedy Randomized Adaptive Search Procedure (GRASP) with the proposed algorithm. The development of this research work is to improve information exchange and facilitate coordination among emergency services and disaster field offices, state/level entities and private industry. This is accomplished by the integration of existing information systems, implementation of new efficient technologies and interconnection of established networks with artificial based techniques

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Published

2025-01-04

How to Cite

Robert, N. R., A. Cecil Donald, & K. Suresh. (2025). Artificial Intelligence Technique Based Effective Disaster Recovery Framework to Provide Longer Time Connectivity in Mobile Ad-hoc Networks. International Journal of Computational and Experimental Science and Engineering, 11(1). https://doi.org/10.22399/ijcesen.713

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Research Article