<![CDATA[Conventional emergency response strategies are often constrained by limited operational coverage, slow resource mobilization, and fragmented data acquisition, hindering coordination effectiveness during critical phases. This research proposes the design of an autonomous drone swarm system to support innovative disaster management and rescue operations. A coordinated multi-agent based system is designed to perform real-time monitoring, structured search and rescue, and post-disaster infrastructure evaluation. Rule-based behavioral modeling is used in complex emergency scenarios. Initial simulation results show greater area coverage, accelerated response times, and increased mission adaptability under dynamic conditions. The system is also designed to deliver logistical assistance such as food and medicine to hard to reach areas, such as ravines or steep mountains. The integration of artificial intelligence algorithms improves target identification precision as well as adaptive swarm response. This model is considered to have transformational potential to be the foundation for the development of future rapid-response autonomous rescue systems. ]]>
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