## 1 Introduction
Departments report incrementally following a process of reporting-request-approval-issuance-execution. In many regions, there is a lack of synchronization among multi-level government functional institutions which leads to the dispersion of information after disasters occur. This hinders quick sharing and collection of crucial information such as disaster situations, availability of emergency supplies, the status of rescue team deployment, or expert support availability. Additionally, although some emergency management institutions have gradually been established in rural areas, they often operate jointly with government offices where personnel hold multiple positions resulting in insufficient expertise in emergency response knowledge or the adoption of advanced information technology, thereby limiting innovation capabilities. These aspects collectively highlight the deficiencies within the current mode of rural emergency management. Based on the above problems, this paper explores the optimization of rural intelligent emergency management by integrating five modes under the backdrop of the new generation of information technology. These modes encompass utilizing satellite remote sensing, unmanned aerial vehicle reconnaissance, and ground sensors to achieve comprehensive, multi-level, and high-precision disaster monitoring; establishing a high-speed, stable, and secure communication network for real-time transmission and sharing of disaster information while leveraging big data and cloud computing technologies for intelligent analysis; incorporating machine-learning algorithms to automatically adjust emergency supply scheduling strategies in order to enhance efficiency and ensure accurate and timely delivery to affected areas; comprehensively considering the advantages and limitations of various transportation resources to dynamically deduce hybrid transportation scheduling strategies in complex environments for swift and safe rescue operations; and emphasizing integration and collaboration among diverse rescue resources while optimizing resource allocation through multidimensional fusion to improve effectiveness. The aforementioned five modes converge into a comprehensive, efficient, and intelligent rural intelligent emergency man agement system that can provide robust support for rural areas including real-time disaster monitoring with early warning capabilities, rapid response measures along with post-processing work procedures, and effective material allocation coupled with optimized transportation resource utilization, as well as the optimal deployment of rescue teams. In summary, the research hypothesis of this paper is that we try to prove or deny that the construction of rural intelligent emergency management mode realizes the digital integration of disaster elements, improves the efficiency of emergency management, and promotes economic sustainable development. A fundamental objective in achieving the rural intelligent emergency management mode is to digitally integrate disaster elements, thereby providing robust data support. Through digital integration, disasters can be comprehended with greater accuracy, early warning and response capabilities can be enhanced, disaster losses can be effectively mitigated, and rural social stability and security can be ensured. Disaster elements encompass various factors that may contribute to disasters, including natural elements such as weather conditions, geology, and the environment, as well as social elements such as population dynamics, the economy, and infrastructure. Digitally integrating these elements entails their conversion into digital formats and employing information technology means for unified management and analysis purposes encompassing data collection, standardization, integration, analysis, and sharing. The enhancement of the intelligent emergency management mode in rural areas lies in leveraging modern information network technology to achieve the real-time collection, transmission, and processing of disaster information.