183 results about "Post disaster" patented technology

A disaster assessment system is presented. The disaster assessment system generates one or more impact reports detailing the nature of how a disaster has impacted a building site based on sensor data associated with the building site that is collected after the disaster. According to one aspect of the inventive subject matter, the disaster assessment system includes a sensor platform, a pre-disaster database, a historic disaster database, and an impact assessment engine. The sensor platform obtains sensor data reflecting a building site before, during, and/or after an event. The impact assessment engine derives a pre-event 3D model based on sensor data collected by the sensor platform before the event, and derives a post-event 3D model based on sensor data collected by the sensor platform after the event. The impact assessment engine then generates the impact reports based on a difference between the pre-event 3D model and the post-event 3D model.

The invention discloses a method for post-disaster damage assessment of buildings by using unmanned aerial vehicles, and relates to the field of disaster assessment. Multiple unmanned aerial vehicles(UAVs) are used to shoot the images of the disaster area, and then TIFF format remote sensing images of the disaster area are quickly constructed on a GPU server by using the photographed high-definition images transmitted from the UAVs. the neural network image segmentation model is used to extract the intact houses from the remote sensing images and compare them with the remote sensing images before the disaster, the block is taken as the unit to record the damaged data and corresponding GPS coordinates, and the geographic coordinates polar spherical projection is used to draw the distribution map of the damaged houses on the map of the disaster area. The invention can quickly evaluate the disaster situation, and the detection result has high credibility.

The invention relates to a country prefabricated steel structure residence system and a construction method of the country prefabricated steel structure residence system. The country prefabricated steel structure residence system comprises plane assembling units, stereoscopic assembling units, stair assembling units and independent component units. The plane assembling units comprise steel pipe concrete columns and H-steel beams forming rectangular frames, each stereoscopic assembling unit is defined by four plane assembling units, a herringbone support is arranged in at least one plane assembling unit in each stereoscopic assembling unit, and a light structure triangular roof truss is arranged on the top layer. Sleeves are welded to vertical connecting column joints at the lower ends of the steel pipe concrete columns, the sleeves are welded to the H-steel beams, and reinforcing plates are further arranged at the joint points where the steel pipe concrete columns and the H-steel beams are connected. Reinforced concrete foundation columns are connected to the bottoms of the steel pipe concrete columns on the first layer, and independent reinforced concrete foundations are further arranged at the bottoms of the reinforced concrete foundation columns. The system is convenient to assemble, short in using time and capable of being widely applied to rural residences and post-disaster reconstruction projects.

The invention discloses a construction method of a road blocking image semantic segmentation sample library for full convolutional neural network training. The construction method comprises the steps of performing vectorization, enhancement and standardization on samples; secondly, introducing a classical convolutional neural network type and a network structure improvement method, and explaining a network realization method and a training process; then, using the full convolutional neural network obtained through training for conducting remote sensing image road surface semantic segmentation, and on the basis that the road surface which is not damaged after disaster is extracted, judging the road integrity through the length proportion of the road which is not damaged before disaster and after disaster. The precision evaluation indexes of the improved full convolutional neural network model are superior to those of an original full convolutional neural network model. The improved model is more suitable for specific problems of post-disaster undamaged pavement detection and road integrity judgment, and the adverse effects of tree and shadow shielding on road blocking information extraction can be effectively overcome.

The invention provides a mobile terminal, a life detection instrument, a post-disaster search and rescue system and a post-disaster search and rescue method. The mobile terminal can be switched to an emergency control mode by an active and/or passive mode(s) and positioned by the life detection instrument by a three-point or multi-point positioning mode. The method comprises the following steps of: establishing an emergency link connection between the mobile terminal and the life detection instrument and switching the mobile terminal to the emergency control mode; generating a distress signal by the mobile terminal according to a preset rule, spreading a spectrum by using a spectrum spreading code and transmitting the signal to the life detection instrument, wherein the distress signal at least comprises a unique identifier of the mobile terminal; transmitting a positioning control signal to the mobile terminal after the life detection instrument receives the distress signal; transmitting a positioning signal by the mobile terminal; and calculating the position of the mobile terminal according to time delay of the positioning signals received by three or more life detection instruments arranged around the mobile terminal. The embodiment of the invention can also realize accurate positioning to improve the search and rescue efficiency.

The invention discloses a landslide extraction method based on a large-range remote-sensing image and altitude data. According to the method, on the basis of a remote-sensing image of a study area and corresponding altitude data, a bare soil region in the image is enhanced by using a significance concept to obtain a significance probability graph, wherein each pixel belongs to a probability graph of a landslide. On the basis of an expansion operation in a morphological algorithm, little large-plaque bare soil in the image is communicated to form a large area and thus the difference with a small landslide area is enhanced, so that the non-landslide bare soil area can be rejected to obtain a landslide potential region. On the basis of the characteristic of frequent occurrence of the landslide at a mountainous area, the potential landslide region at the mountain slope is kept by combining the altitude data to obtain a final landslide extraction result. With the method disclosed by the invention, problems of small research range and simple situation for the existing landslide extraction example can be solved; a technological base is provided for large-range practical rapid landslide extraction; and thus the method plays an important role in post-disaster emergency response and rapid landslide area positioning.

The invention discloses a road blocking information extraction based on deep learning image classification, and the method comprises the steps: building a road blocking image classification sample library through employing a disaster typical case image, carrying out the training of a convolutional neural network, and obtaining an initial convolutional neural network model CNNmodel0; obtaining a post-disaster image I (x) and a road vector R (x) of the research area x, and detecting road blocking to obtain a to-be-detected sample Dn (x); using the trained network CNNmodel0 to perform multi-pointroad blocking detection of adding detection points in the vertical normal direction of the road vector direction on the sample Dn (x) to be detected: selecting a small number of road segments to generate new training sample data S1, and performing network fine tuning on the existing network; and repeating the road blocking classification detection work until the detection result meets the precision requirement. Various precision evaluation indexes of the improved convolutional neural network model are superior to those of an original model, and the improved convolutional neural network modelis more suitable for specific problems of disaster area road blocking image classification and detection.

The invention discloses a mobile gas monitoring system and a method based on accurate positioning in underground coal mine. The system comprises: a mobile gas detector brought by people who enters a mine and used to detect gas concentration; a radio communication base station arranged in the mine and for determining a position of the mobile gas detector and receiving information about sensed gas concentration by carrying out radio communication with the mobile gas detector; a monitoring center server used to receive the information of the sensed gas concentration and information of the position of the mobile gas detector from the radio communication base station to carry out information management. The system and the method provided in the invention can be used for safety monitoring management of daily production in the coal mine to guarantee safe production in the coal mine, and also can provide basis for decision of coal mine cataclysm rescue, with the system and the method, rescue progress can be accelerated and post-disaster casualties can be minimized.

The invention relates to a high resolution optical remote sensing image post-disaster water body information extracting method and system. The method comprises the steps that a post-disaster water body region is selected as a target post-disaster water body research region; the high-resolution optical remote sensing image is acquired; radiation calibration, atmospheric correction, geometric correction and noise removing are carried out on the acquired remote sensing image to acquire a preprocessed image; the preprocessed image is enhanced based on a generalized fuzzy operator method to acquire the enhanced image of the target post-disaster water body research region; an object-oriented method is used to segment the enhanced image; a method based on spectral information is used to carry out coarse extracting on water body information in the segmented image to acquire coarse-extracted post-disaster water body information; according to a water body information extraction feature knowledge judgment method, refined extracting is carried out on the coarse-extracted post-disaster water body information to acquire refined-extracted post-disaster water body information; and a regional mark method is used to carry out hole filling on the water body region to acquire final post-disaster water body information.

The present invention relates to a rescue path planning method based on multiple starting points, multiple to-be-rescued points, and multiple destinations. Three components: a wireless sensor, a mobile terminal and a remote server end which are pre-deployed inside the building are involved in the method. The rescue path planning method comprises the following steps: obtaining environment information through a wireless sensor network deployed inside the building, and establishing an environment model by using a grid method; and according to the environment model established by using the grid method, establishing a combined optimization model by improving the ant colony algorithm, thereby finding the shortest rescue route. According to the combined emergency rescue real-time path planning method for multiple starting points, multiple to-be-rescued points, and multiple exits provided by the present invention, a multi-objective combination optimization model for the post-disaster emergencyrescue is established, an improved ant colony algorithm is designed, model solving is performed, requirements for rapid decision-making in the post-disaster emergency rescue route planning can be better satisfied, a safe and fast rescue route can be found, and the efficiency of disaster rescue can be improved.

The invention discloses a post-disaster unmanned aerial vehicle base station deployment method and system based on an artificial bee colony algorithm. The method comprises the steps of constructing an unmanned aerial vehicle base station three-dimensional scene with a preset size and distributed with a plurality of terminal users; calculating the network throughput of each terminal user in the scene area, and calculating the overall network throughput according to the capacity constraint of the unmanned aerial vehicle base station; calculating the maximum overall network throughput and the optimal flight position of the corresponding unmanned aerial vehicle base station in the air by adopting an artificial bee colony algorithm, and deploying the unmanned aerial vehicle base station.

The invention discloses a post-disaster life tracking unmanned aerial vehicle system. The post-disaster life tracking unmanned aerial vehicle system comprises an unmanned aerial vehicle system body, a control station system and a communication link system. The unmanned aerial vehicle system body comprises at least one unmanned aerial vehicle which obtains the position of the unmanned aerial vehicle in real time through a navigational satellite and flies in the sky above a post-disaster search-rescue region to collect an image, the spectrum and infrared rays of the ground in real time. In addition, the position, the image, the spectrum and the infrared rays are sent to a control station after being integrated, classified and analyzed. The control station system comprises at least one control station which is used for recognizing a vital sign signal according to the image, the spectrum and the infrared rays collected through the unmanned aerial vehicle and drawing a map presenting a life position in combination with the position. The communication link system is used for providing communication links between the unmanned aerial vehicle and the navigational satellite, between the unmanned aerial vehicle and the control station, and between the control station and a disaster relief command center. The post-disaster life tracking unmanned aerial vehicle system can overcome the influence of severe environment and collect data continuously, and has the advantages of being high in search-rescue efficiency and accurate in life locating.

The invention discloses a high-resolution image house information rapid supervision and identification method based on a BFD-IGA-SVM model. The method is characterized by on the basis of a house building target feature system, constructing an object of a high-resolution remote sensing image through multi-scale segmentation, wherein the image object is a carrier of the feature and knowledge expression, and the accurate construction of the image object is the basis of the subsequent target recognition; extracting the feature variables, and optimizing the features by combining a ReliefF algorithm, a genetic algorithm and a support vector machine model to form a house optimal feature subset; carrying out house information extraction and identification on the optimal feature subset of the house, and comparing the sensitivity of the optimal feature subset of the house with that of a related method. The method is higher in precision and very good in robustness, greatly improves the house extraction efficiency, achieves the quick extraction of the post-disaster onsite house information, is very good in application value, and achieves the important information support for the post-disasterreconstruction and quick rescue.

The invention discloses an automatic matching-based power transmission line fault cause identification method. According to the method, line tripping and log book information is connected into and matched in a lightning locating system, so that the location of a lightning strike fault is judged; and the shielding failure and back striking lightning withstand levels of towers at each stage of a power transmission line are compared with the amplitude of lightning current, so that the nature of the lightning strike fault can be determined. With the method of the invention adopted, the tripping lightning fault of the power transmission line can be automatically identified, a technical basis is provided for the auxiliary decision-making of the post-disaster rapid processing of the lightning strike tripping fault, the application limitations of a method according to which the type of a fault can be diagnosed and the location of the fault can be determined only after line inspection is performed to search a fault point after a lightning strike fault occurs can be eliminated, the repair time and power resuming time of the power transmission line can be greatly shortened, and a large quantity of labor, material and time costs for detecting the fault can be saved.

The invention relates to a radio frequency identification real-time positioning tracking management system and a real-time positioning tracking method thereof. The system comprises a plurality of labels, a plurality of readers, at least one switch, a server, a database and at least one display, wherein the server controls the reader to read data in the labels through the switch, and resolves the read data, and transmits the resolved data to the display; and an interface of the display is operated so as to search required information. The system and the method not only can quickly search accurate position of a specific person or equipment, but also can quickly understand distribution conditions of staff or equipment in different types, and are convenient for distributing the staff in time.The system and the method are applicable in the fields of staff attendance checking, tracking positioning, post-disaster emergency treatment, daily management and the like.

The invention relates to a landslide and debris flow geological disaster monitoring and emergency response method. The landslide and debris flow geological disaster monitoring and emergency service system according to the method is composed of a ground online monitoring and early warning subsystem, an emergency and command subsystem, a disaster information extraction subsystem, a post-disaster damage assessment subsystem and an emergency consultation service subsystem. Pre-disaster early warning and post-disaster emergency disposal are integrated to provide a full-process and systematic solution. The monitoring and early warning difficulties and the outbreak characteristics of the landslide and debris flow geological disaster are fully considered, the pre-disaster monitoring and early warning are organically combined with the post-disaster emergency rescue, and the emergency disposal integration is performed based on the space-air-ground integrated remote sensing monitoring and emergency response technological means to form the systematic geological disaster emergency disposal scheme of landslide and debris flow. Multiple monitoring techniques are complementary to each other, the manual patrol mode is replaced, a great deal of manpower and material resources are saved, the decision-making time of disaster emergency is shortened and the collaborative emergency response efficiency of all the departments is effectively improved.

The invention discloses a method for detecting life information and belongs to the field of post-disaster life information detection, search and rescue. The method comprises following steps: step 1: multiple geophone sensors are used for collecting signals which are knocking signals sent by trapped people in an area to be searched and rescued; step 2: a STA/LTA algorithm is used for recognizing collected signals to obtain pulse frequency and time interval of the knocking signals; step 3: the recognized signals are interpreted according to a pre-determined knocking rule constituted by pulse frequency and time interval to obtain distress information corresponding to the knocking signals; and step 4: the distress information is displayed on a display screen. By use of the method, life status of trapped people is determined through picking up knocking signals of the trapped people, distress information of the trapped people is determined through signal interpretation, and the life information detection of trapped people can be effectively realized.

The present invention discloses a system for map construction aiming at a communication failure area of an earthquake area, belonging to the post-disaster reconstruction device field. The device comprises an air detection device and a land detection device; the air detection device comprises an aircraft, a binocular visual sense module, a map revision module and an air navigation module; the land detection device comprises a carrier, a land sensing module, a map construction module and a ground navigation module, wherein the air detection device is in communication connection with the land detection device through a zig bee communication module. The air detection device and the land detection device are interconnected through autonomous communication to rapidly obtain a post-disaster map and information required rescuing so as to effectively save manpower, shorten the detection time and substantially improve the rescue efficiency.

The invention discloses a geological-disaster emergency commanding system based on a GIS. The geological-disaster emergency commanding system comprises a data collecting module, a disaster-situation early warning module, a disaster point numbering module, an attribute database, a GIS database, a data fusion module, a map management module, a positioning navigation module, a disaster point management module, a disaster-situation evaluation module, a disaster-situation grading standard library, an emergency treatment module, an emergency plan library and a real-time communication module. Geological-disaster control departments of all regions can query detailed information of geologic attributes of all disaster points, and therefore comprehensive management of disaster points is achieved; meanwhile, emergency plans when disasters occur can be directly and rapidly displayed, and a direct and rapid solution is provided for pre-disaster early warning, disaster commanding and post-disaster rescuing.

The invention discloses an emergency material reserve optimization system, which comprises an emergency material module, an emergency event module, an emergency material demand model, an emergency material demand estimation, an emergency material reserve optimization and a front-end display control module. The present invention optimizes and calculates the resource requirements required for emergency events with multiple response levels; at the same time, it provides an optimization strategy for the distributed federation storage mechanism to guide the coordinated transfer of material supply between post-disaster regional warehouses (first-level warehouses, second-level warehouses) and first-aid kits , can output accurate and efficient emergency material reserve plan (including warehouse and first aid kit reserve plan), to ensure that the materials stored in the warehouse and first aid kit meet the emergency needs, so that the emergency material reserve management level has been significantly improved. Avoid repeated reserves and insufficient reserves in emergency material reserves, and improve the efficiency and effect of emergency resource protection.

The invention discloses a method for evaluating the importance of a power system element based on restoring force. The method comprises the following steps: 1) determining the type and occurrence property of a disaster; 2) obtaining vulnerable element types and related fault probabilities under disasters; 3) acquiring fault configuration conditions of elements in the system after disasters occur by utilizing non-sequential Monte Carlo simulation; 4) establishing a post-disaster optimal recovery strategy model, and proposing an objective function and constraint conditions; and 5) simulating thepost-disaster recovery process for multiple times to obtain the repair time of each element, and performing sorting by using a Koplan sorting method to obtain the importance sorting of the elements.By utilizing the method, the element importance of the power system under various natural disasters and man-made disasters can be solved, and the disaster type and characteristics are considered in the solving process. The element importance result obtained by the method can provide reference for making a post-disaster recovery strategy and determining a pre-disaster element reinforcement scheme.

A tethered aerial system includes an on-board fuel cell for powering on-board electronics and a tether cable is less conductive than air. The tether cable includes a pipe for carrying a flow of gas to the fuel cell and/or maintain the gas level in a lighter-than-air platform, so that the tethered aerial system can remain operational for an extended period of time. The system is particularly applicable for maintaining communication links in remote areas, agriculture and applications in the IoT (Internet of Things), event coverage, interactive marketing, for post-disaster situations in rural areas and at mining sites or construction sites in remote environments. The present invention also is immune to rays.

The invention discloses a meizoseismal area debris flow hidden risk point quick recognizing method. According to the method, drainage basins are divided according to a meizoseismal area vector topographic map to obtain areas of the drainage basins, the total area and the total volume of critical loose material sources which are needed by debris flows of each drainage basin are obtained through calculation, then the total area and the total volume of new loose material sources in drainage basins to be recognized are obtained through remote-sensing images and calculation, and finally the total area and the total volume of the new loose material sources in the drainage basins to be recognized are compared with the total area and the total volume of the critical loose material sources which are needed by the debris flows of the drainage basins so as to judge whether the drainage basins to be recognized are new debris flow hidden risk points or not after earthquakes. Compared with the prior art, the method enables the new loose solid material sources after the earthquakes to serve as the only debris flow recognition indicator, it is distinguished that a judging threshold value is a variable related to the areas of the drainage basins, supporting data are easy to obtain, the recognition precision is high, the debris flow hidden risk points of the meizoseismal area can be recognized reasonably and quickly, and reference is provided for site selection of post-disaster reconstruction in the meizoseismal area.