article · Electronics
Natural disasters and crisis events present complex environments where independent communication networks are vital for victims and first responders. Developing exploratory paths for unmanned aerial vehicle networks in these settings remains a major challenge. A crisis and disaster management system uses a swarm optimisation algorithm combined with a delay tolerant network strategy to support search and rescue operations. The system is designed to identify global optimum solutions across the search space rather than settling for suboptimal paths. Operationally, the method pursues two core objectives: exploring potential disaster zones and navigating unmanned aerial vehicles towards identified groups of victims. System performance evaluated through metrics including communication delay, throughput, performance rate, and path loss demonstrates superior results when compared against existing operational techniques.
During catastrophic events, conventional communication infrastructure frequently fails, leaving emergency responders and victims disconnected. Deploying autonomous aerial networks capable of navigating complex disaster zones helps locate survivors more effectively. Improved data throughput, lower communication delay, and robust route optimisation allow rescue teams to coordinate resources rapidly when time is critical for saving lives.
The system could enable software solutions for emergency response agencies, civil protection bodies, and smart city operators coordinating autonomous aerial rescue fleets. Because the findings reflect algorithmic modelling evaluated on communication metrics like throughput and path loss rather than physical field deployments, the technology appears to be at an early stage of applied research requiring real-world prototyping before deployment.
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Over the course of the last decade, the unmanned aerial vehicle (UAV) research community has received a significant amount of attention. Emergency response operations, such as those that follow a natural disaster, are one of the civil applications that could benefit from the use of UAVs in disaster and crisis management. In the event of a catastrophic event, it would be extremely beneficial for both victims and first responders to have access to a UAV network that is capable of deploying independently and offering communication services. However, when working with complicated situations, one of the most difficult things is coming up with exploratory paths for the networks involved. A crisis and disaster management system using a swarm optimization algorithm (SOA) is proposed to assist in disaster and crisis management. In this system, the UAV search and rescue team follows the strategy called the delay tolerant network, which has the ability to explore. The proposed approach is able to find the global maximum in the search space without ever settling for a suboptimal solution. This work has two primary objectives: the first is to investigate a potential disaster zone, and the second is to direct the UAV to a number of victim groups that were found during the investigation phase. For the purpose of performing a characterization, performance metrics such as delay, throughput, performance rate, and path loss have been analyzed. The results show the superiority of the performance over the existing work.
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DOI: 10.3390/electronics12041051
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