<![CDATA[Fire-related emergencies inside buildings expose first responders to severe risks caused by limited visibility, high temperatures, toxic gases, and rapidly changing structural conditions. Immediate entry without adequate situational awareness increases the probability of injury and operational failure. Autonomous robotic systems provide a promising approach to reduce human exposure by performing preliminary hazard assessment and environmental monitoring. This study presents the design and experimental evaluation of EVACo-Aid, an IoT-enabled autonomous robotic platform developed to support indoor fire rescue operations. The system integrates fire detection, obstacle avoidance, victim identification, and real-time data transmission within a compact mobile platform. An experimental prototyping methodology was employed, covering system design, hardware integration, control programming, and functional testing under controlled indoor conditions. Experimental results demonstrate that the proposed system can reliably detect fire sources, navigate autonomously around obstacles, and transmit operational data in real time. Although limitations remain regarding mobility on uneven terrain and sensor performance in extreme environments, the findings indicate that low-cost autonomous robots can enhance situational awareness and improve responder safety during indoor fire emergencies.]]>
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