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The number of emergency call received history by Kobe firefighters during Kobe earthquake 1995 (Source: [3]).
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The efficient allocation of resources in the aftermath of an earthquake in an affected area largely depends on the identification of post-earthquake critical rescue area. This paper is the second part of the companion paper on the integration of smart watch and geographic information system (GIS) to identify post-earthquake critical rescue area. In...
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Context 1
... from emergency call and is shown in Eq. (8). In Japan, one of the main sources of information collection about damage and causalities immediately after the earthquake is the emergency calls (dialled at 119). Thus, Eq. (8) is developed based on the Kobe earthquake emergency call data received by Kobe Fire Department during emergency period (Fig. 3) and the assumption that, if information providers are the public then it will follow exponential type ...
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To address the shortcomings of single-step decision making in the existing deep reinforcement learning based unmanned aerial vehicle (UAV) real-time path planning problem, a real-time UAV path planning algorithm based on long short-term memory (RPP-LSTM) network is proposed, which combines the memory characteristics of recurrent neural network (RNN) and the deep reinforcement learning algorithm. LSTM networks are used in this algorithm as Q-value networks for the deep Q network (DQN) algorithm, which makes the decision of the Q-value network has some memory. Thanks to LSTM network, the Q-value network can use the previous environmental information and action information which effectively avoids the problem of single-step decision considering only the current environment. Besides, the algorithm proposes a hierarchical reward and punishment function for the specific problem of UAV real-time path planning, so that the UAV can more reasonably perform path planning. Simulation verification shows that compared with the traditional feed-forward neural network (FNN) based UAV autonomous path planning algorithm, the RPP-LSTM proposed in this paper can adapt to more complex environments and has significantly improved robustness and accuracy when performing UAV real-time path planning.
With the continuous development of geographic information surveying and mapping technology, emergency surveying and mapping puts forward higher requirements for surveying and mapping work. Whenever an emergency occurs, emergency investigation and geographic mapping provide effective and reliable information for the emergency situation. In addition, emergency surveying puts forward higher requirements for mapping geographic information. Analyzing the application of surveying and mapping geographic information technology in emergency surveying and mapping, such as the application of data collection technology and virtual reality technology, can effectively enhance the role of geographic information technology in emergency surveying and mapping, and improve the ability of emergency response. This paper mainly analyzes the application of geographic information in emergency surveying and mapping and related technical fields, and explores the main application trends of emergency surveying and mapping.
