Abstract
Fires pose grave threats to lives, properties, and natural resources, necessitating effective fire suppression and rescue efforts. This paper proposes a solution to enhance firefighter safety and efficiency by integrating Unmanned Aerial Vehicles (UAVs) with Artificial Intelligence (AI)-based human motion recognition. The proposed system employs supervised machine learning algorithms trained on firefighting video datasets to recognize six crucial firefighter actions: ‘advance’, ‘climb’, ‘connect’, ‘fetchwater’, ‘hoselaying’, and ‘watersupply’. The trained model demonstrates 74.8% accuracy in identifying these actions during fire suppression activities. By utilizing UAVs and AI, this system offers extended detection range, deployment flexibility, and live, high-resolution image capture without risking pilots’ lives. The integration of UAVs and AI holds great promise in mitigating the devastating impact of fires and safeguarding the lives of firefighters
