Algorithm for the use of intelligent drone ports in emergency situations in the Republic of Kazakhstan

Abstract

A structured algorithm has been developed in this study for the application of intelligent drone ports during emergency situations in the Republic of Kazakhstan. Primary considerations for the employment of drones during emergency situations in Kazakhstan include vast territorial areas, given the geography and extreme climate conditions. Initially, comprehensive performance criteria and indicators are established to cover operational performance, cost-effectiveness, safety, social and regional dimensions for the effective employment of drones during disasters/emergencies, facilitating subsequent response management. Various available drone ports were analyzed, which include universal, user-defined, and mobile stations. Following this, an analysis and classification of drones were carried out based on their functional roles in emergency management. Based on these criteria and classification, a five-stage operational algorithm was proposed. These stages are emergency detection and notification, task planning, task execution, maintenance, data collection and analysis. The integration of artificial intelligence (AI), including machine learning (ML) and computer vision, is recommended for improving automation, responsiveness, and decision-making efficiency, thereby enhancing the effective employment of drones in disaster response management. A scalable and adaptable framework was proposed to increase the overall capacity of emergency response management in Kazakhstan, thereby reducing risk and optimizing resource utilization. This research provides not only a theoretical foundation for performance assessment but also a practical roadmap for future implementation, testing, and policy development for the employment of intelligent drones in general elsewhere in the world and in particular for Kazakhstan.