Solving problems such as information asymmetry, delays, and communication barriers among participants in emergency management and rescue, improving the efficiency of multi-party and multi-level coordinated command, and gaining more time for rescue efforts.
The existing emergency management command system has a mismatch between information and space, and cannot provide remote understanding of disaster development trends and losses. At the same time, due to the asymmetry of information among multiple departments, it is not possible to prepare rescue materials and formulate rescue plans in advance, which may lead to delays in rescue time.
The collaborative command and rescue platforms based on digital twins, mechanism models, and AI algorithms are used to display real -time disaster conditions and predictions for different participation in emergency command and rescue units, and provide rescue solutions for command and rescue personnel.
The application of this technology can enable the commanders to understand the situation and trend of the disaster from multiple dimensions in the overall situation, and give the deduction results for different rescue measures to help the commander make the correct decision; Understand the scene of the disaster in advance, and give relevant suggestions to fight for more time to rescue.