## 5 Discussion  
The intelligent emergency management model based on digital technology has facilitated the digital integration of disaster elements, thereby enhancing the efficiency of emergency management and fostering sustainable development in rural economies within China's rural areas. In the subsequent discussion and conclusions, we will delve into the advantages brought forth by this model, as well as the challenges and opportunities encountered during its implementation. Based on the scientific literature, government documents, field research, and analysis, this paper proposes a rural intelligent emergency management model guided by the principle of \"intelligent perception and intelligent emergency\". Firstly, to enhance the information level in rural areas, it is crucial to leverage new-generation information technology. By establishing a comprehensive intelligent perception system (i.e., integrating aerial and ground monitoring), round-the-clock monitoring and perception of rural areas can be achieved, effectively improving their information collection and processing capabilities. Simultaneously, developing a diversified communication network command and scheduling system enables the rapid and accurate transmission of information as well as efficient command and coordination during various emergencies. Secondly, to improve the efficiency and accuracy of emergency response efforts, an emergency supplies scheduling system based on machine learning can predict the required supplies for different types of disasters using real-time information for effective scheduling. Additionally, a dynamic deductive transportation scheduling system can perform optimal path planning and scheduling based on real-time road conditions and material needs to significantly enhance material transportation efficiency while ensuring timely delivery. Finally, in enhancing rescue capacity, a multi-dimensional resource fusion rescue team scheduling system can be employed to coordinate and optimize the allocation of various rescue forces. The objective of this model is to establish a diversified technology chain for addressing emergency rescue by integrating multi-dimensional data on rural natural disasters and the latest generation of information technology. In order to enhance the efficiency of dealing with rural natural disasters, this model employs satellite remote-sensing technology and big data analysis methods to assess the disaster situation, ensuring the real-time comprehension of dynamic disaster events. Simultaneously, it optimizes command and scheduling through artificial intelligence technology in order to achieve the comprehensive monitoring and cross-regional coordination of emergency personnel, equipment, and material resources within the affected area. Furthermore, it utilizes machine-learning algorithms for material allocation in response to real-time changes in the disaster situation, thereby improving resource optimization for rescue teams. This approach not only enables swift responses to rural natural disasters but also enhances rescue efficiency while minimizing the losses incurred. Consequently, this model will contribute towards enhancing rural areas' capacity for preventing natural disasters, safeguarding citizens' lives and property safety as well as providing robust support for sustainable development efforts. Additionally, it will facilitate widespread adoption of cutting-edge information technologies while promoting economic society transformation and upgrading. The promotion of rural intelligent emergency management mode is confronted with a series of formidable challenges. Firstly, there exists a substantial disparity between rural infrastructure construction and the requirements of this mode, which proves arduous to bridge within a limited timeframe. This discrepancy encompasses not only hardware facilities such as communication networks and intelligent devices but also software conditions like technical personnel and data resources.