CN110650177A - Edge computing platform and method for servicing special hybrid vehicle - Google Patents
Edge computing platform and method for servicing special hybrid vehicle Download PDFInfo
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- CN110650177A CN110650177A CN201910731900.6A CN201910731900A CN110650177A CN 110650177 A CN110650177 A CN 110650177A CN 201910731900 A CN201910731900 A CN 201910731900A CN 110650177 A CN110650177 A CN 110650177A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- A—HUMAN NECESSITIES
- A62—LIFE-SAVING; FIRE-FIGHTING
- A62C—FIRE-FIGHTING
- A62C27/00—Fire-fighting land vehicles
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- A—HUMAN NECESSITIES
- A62—LIFE-SAVING; FIRE-FIGHTING
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- A62C3/00—Fire prevention, containment or extinguishing specially adapted for particular objects or places
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- A—HUMAN NECESSITIES
- A62—LIFE-SAVING; FIRE-FIGHTING
- A62C—FIRE-FIGHTING
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- G01—MEASURING; TESTING
- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P13/00—Indicating or recording presence, absence, or direction, of movement
- G01P13/02—Indicating direction only, e.g. by weather vane
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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- H—ELECTRICITY
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Abstract
The invention discloses an edge computing platform and a method for serving a special hybrid vehicle.A smart unmanned aerial vehicle exploration module is connected with a special hybrid vehicle server through short-distance communication, a fireman wears augmented reality equipment and is connected with the special hybrid vehicle server through short-distance communication, the special hybrid vehicle server is installed on the special hybrid vehicle and is connected with a first base station through wireless communication, the first base station is connected with a satellite through wireless communication, the satellite is connected with a second base station near a fire station through wireless communication, the second base station is connected with a fire monitoring server through wired communication, the fire monitoring server is connected with an edge computing workstation through wired communication, and a building information server is connected with the edge computing workstation through wired communication. The invention can effectively acquire the information of the fire scene in real time, plan the optimal emergency rescue route, improve the rescue efficiency of fire fighters, powerfully ensure the safety of the fire fighters, and has high intelligence and strong safety.
Description
Technical Field
The invention relates to the field of edge computing and intelligent fire rescue, in particular to an edge computing platform and method for serving a special hybrid vehicle.
Background
People are difficult to escape and rescue when a fire disaster happens due to complex terrain, high-rise buildings, public facilities, dense personnel, traffic jam and the like in modern cities, so that casualties and huge economic loss are caused. Because the fire disaster is unpredictable, the fire fighters are difficult to arrive at the scene at the first time and miss the best rescue opportunity; the complexity and the unknown of the fire scene situation cause fire fighters not to know the fire scene situation in detail in the first time in the rescue process, so that the fire situation and wounded persons are not put out and rescued in time; in the rescue process, due to the influence of fire, the building is possibly subjected to dangers such as structural deformation and house collapse, and the life safety of wounded personnel and firefighters is threatened.
Chinese patent (CN207898790U) discloses an intelligent fire truck and a remote fire control system, which can monitor the fire situation in time and send the fire situation to the fire fighters in time through an image acquisition device when a fire breaks out. However, the fire extinguishing system has the disadvantages that intuitive information such as the layout inside a building cannot be provided for fire fighters, the fire extinguishing progress of the fire fighters is seriously influenced, even the personal safety of the fire fighters is influenced, and serious consequences are caused.
Disclosure of Invention
In view of the above, the present invention aims to provide an edge computing platform and method for serving a special hybrid vehicle, which effectively acquire fire scene information in real time, provide visual information such as the layout of the interior of a building, perform quick interactive response by using an edge computing workstation and a cloud data center, plan an optimal emergency rescue route, improve the rescue efficiency of fire fighters, and powerfully ensure the personal safety of the fire fighters.
The invention is realized by adopting the following technical scheme:
the utility model provides a service special type hybrid vehicle's marginal computing platform, includes that unmanned aerial vehicle intelligence explores module, short distance communication, special type hybrid vehicle server, augmented reality equipment, a base station, satellite, No. two base stations, wired communication, fire monitoring server, building information server, marginal computing workstation.
The unmanned aerial vehicle intelligent detection module is connected with the special hybrid vehicle server through short-distance communication, the firefighter wearing the augmented reality device is connected with the special hybrid vehicle server through short-distance communication, the special hybrid vehicle server is arranged on the special hybrid vehicle, the fire monitoring system is characterized in that the fire monitoring system is connected with a first base station near a fire occurrence area through wireless communication, the first base station is connected with a satellite through wireless communication, the satellite is connected with a second base station near a fire station through wireless communication, the second base station is connected with a fire monitoring server through wired communication, the fire monitoring server is connected with an edge computing workstation through wired communication, a building information server is connected with the edge computing workstation through wired communication, and the fire monitoring server, the building information server and the edge computing workstation are arranged in the fire station.
Further, the module is exploreed to unmanned aerial vehicle intelligence includes that the module shell is exploreed to unmanned aerial vehicle intelligence, circuit board, image acquisition module, temperature acquisition module, smog concentration acquisition module, GPS, gyroscope, information storage module, information transceiver module. The circuit board is installed in unmanned aerial vehicle intelligence explores the module shell, and image acquisition module, temperature acquisition module, smog concentration acquisition module, GPS, gyroscope, information storage module and information transceiver module integrated mounting are carried out information transmission by the circuit on the circuit board. The information receiving and sending module is connected with the special hybrid vehicle server through short-distance communication.
Further, the image acquisition module can adopt, but is not limited to, a camera or a radar, and is used for acquiring the image information of the fire scene and transmitting the image information to the information storage module.
Furthermore, the augmented reality equipment comprises a GPS, a gyroscope, an information receiving and transmitting module, a display module and a circuit board. The GPS, the gyroscope, the information transceiving module and the display module are integrally installed on the circuit board, and information transmission is carried out through a circuit on the circuit board. The information receiving and sending module is connected with the special hybrid vehicle server through short-distance communication.
The edge computing platform for serving the special hybrid power vehicle performs unified management and dynamic allocation on the edge side rescue service platform according to the demand of fire rescue on computing resources, interacts with a plurality of cloud data centers according to real-time fire scene condition feedback, completes mass data storage and computation by using an edge computing workstation, finally obtains feedback to make a reasonable emergency rescue scheme, and realizes real-time sharing with fire rescue vehicles and fire fighters.
The invention discloses a control method for an edge computing platform for serving a special hybrid vehicle, which comprises the following steps:
step 1) after a fire disaster occurs, a fire department knows the place where the fire disaster occurs, immediately arranges a special hybrid vehicle to go to the place of the fire disaster at the first time, and carries out fire disaster rescue;
step 2) the unmanned aerial vehicle enters a fire scene, a GPS in an intelligent unmanned aerial vehicle exploration module determines position information and speed information acquired by the unmanned aerial vehicle, a gyroscope acquires angular velocity in three coordinates to judge the flight direction of the unmanned aerial vehicle, an image acquisition module acquires images of the fire scene, a temperature acquisition module acquires the temperature of the fire scene, and a smoke concentration acquisition module acquires the smoke concentration of the fire scene;
step 3) an information storage module in the intelligent unmanned aerial vehicle exploration module stores information, and meanwhile, an information transceiving module is connected with a special hybrid vehicle server through short-distance communication and transmits the fire scene internal information collected by the unmanned aerial vehicle to the special hybrid vehicle server;
step 4) the special hybrid vehicle server transmits the acquired fire scene information to a first base station near the fire scene, and transmits the fire scene information to an edge computing workstation in a fire station through a satellite, a second base station and a fire monitoring server;
step 5) calculating and predicting the fire condition and the damage condition in the building by the edge calculation workstation by combining a fire building structure transmitted by the cloud end of the building information server and the fire scene condition, the temperature smoke intensity and the like transmitted by the unmanned aerial vehicle, planning an optimal emergency rescue route according to a simulation result, and uploading the optimal emergency rescue route to the special hybrid vehicle server;
and 6) the firefighter wears the augmented reality equipment to enter a fire scene for rescue, the position of the firefighter is judged according to a GPS in the augmented reality equipment, the special hybrid vehicle server pushes current floor information and the optimal action path in the display module through short-distance communication to guide the firefighter to rapidly reach a target position, and the fact that the firefighter is collapsed and injured due to smoke diffusion, overlarge fire behavior and house collapse is prevented.
The invention has the beneficial effects that:
before the firefighter arrives at the scene, the unmanned aerial vehicle enters the fire scene firstly to acquire fire information, collect fire source information, wounded information, information of inflammable and explosive materials on the scene and the like. If inflammable and explosive materials exist, whether secondary fire is possibly caused is confirmed. The edge calculates the site conditions that the workstation collected building structure information and unmanned aerial vehicle and transmitted back, use cloud computing prediction condition of a fire and house damage condition, carry out analog simulation, plan best emergency rescue route, wear augmented reality equipment by the fire fighter and get into the scene of a fire rescue, judge the position that the fire fighter was located according to the GPS in the augmented reality equipment, with current floor information and best action route propelling movement in display module, guide the fire fighter to reach the target location rapidly, and prevent because smog is diffuse, the intensity of a fire is too big, the house collapses and injures the fire fighter by a crashing object.
Drawings
FIG. 1 is a schematic diagram of an edge computing platform and method for servicing a special hybrid vehicle;
fig. 2 is a schematic diagram of an unmanned aerial vehicle intelligent probe module;
FIG. 3 is a circuit board structure diagram of an intelligent unmanned aerial vehicle exploration module;
FIG. 4 is a diagram of an augmented reality device circuit board configuration;
fig. 5 is a schematic view of a fire scene.
Wherein: 1-unmanned aerial vehicle intelligent exploration module, 2-short distance communication, 3-special hybrid vehicle, 4-special hybrid vehicle server, 5-augmented reality equipment, 6-base station, 7-satellite, 8-base station, 9-wire communication, 10-fire monitoring server, 11-building information server, 12-edge computing workstation, 13-unmanned aerial vehicle intelligent exploration module shell, 14-circuit board A, 15-image acquisition module, 16-temperature acquisition module, 17-smoke acquisition module, 18-GPS A, 19-gyroscope A, 20-information storage module, 21-information transceiver module A, 22-circuit board B, 23-GPS B, 24-gyroscope B, 25-information transceiver module B, 23-information transceiver module B, and, 26-display module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and the detailed description. The specific embodiments described herein are merely illustrative of the invention and do not delimit the invention.
As shown in fig. 1, an edge computing platform for servicing a special hybrid vehicle of the present invention comprises: the intelligent unmanned aerial vehicle detection system comprises an unmanned aerial vehicle intelligent detection module 1, short-distance communication 2, a special hybrid vehicle 3, a special hybrid vehicle server 4, augmented reality equipment 5, a first base station 6, a satellite 7, a second base station 8, wired communication 9, a fire monitoring server 10, a building information server 11 and an edge computing workstation 12.
The unmanned aerial vehicle intelligent exploration module 1 is connected with a special hybrid vehicle server 4 through short-distance communication 2, a fireman wears an augmented reality device 5 and is connected with the special hybrid vehicle server 4 through the short-distance communication 2, the special hybrid vehicle server 4 is installed on the special hybrid vehicle 3 and is connected with a first base station 6 near a fire occurrence area through wireless communication, the first base station 6 is connected with a satellite 7 through wireless communication, the satellite 7 is connected with a second base station 8 near a fire station through wireless communication, the second base station 8 is connected with a fire monitoring server 10 through wired communication 9, the fire monitoring server 10 is connected with an edge computing workstation 12 through wired communication 9, a building information server 11 is connected with the edge computing workstation 12 through wired communication 9, the fire monitoring server 10, the building information server 11, The edge computing workstation 12 is disposed within a fire station.
As shown in fig. 2 and fig. 3, the intelligent unmanned aerial vehicle exploration module 1 includes an intelligent unmanned aerial vehicle exploration module housing 13, a circuit board a 14, an image acquisition module 15, a temperature acquisition module 16, a smoke concentration acquisition module 17, a GPS a 18, a gyroscope a 19, an information storage module 20, and an information transceiver module a 21. The circuit board A is installed in unmanned aerial vehicle intelligence explores module shell 13, and image acquisition module 15, temperature acquisition module 16, smog concentration acquisition module 17, GPSA 18, gyroscope A19, information storage module 20 and information transceiver module A21 integration are installed on the circuit board, are carried out information transmission by the circuit on the circuit board A14. The information transceiver module a 21 is connected to the special hybrid vehicle server 4 through short-range communication 2.
As shown in fig. 4, the augmented reality device 5 includes a circuit board B22, a GPS B23, a gyroscope B24, an information transceiver module B25, and a display module 26. The GPS B23, the gyroscope B24, the information transceiving module B25 and the display module 26 are integrally installed on the circuit board B22, and information transmission is carried out by a circuit on the circuit board B22. The information transceiver module B25 is connected to the special hybrid vehicle server 4 via short-range communication 2.
The edge computing platform for serving the special hybrid power vehicle performs unified management and dynamic allocation on the edge side rescue service platform according to the demand of fire rescue on computing resources, interacts with a plurality of cloud data centers according to real-time fire scene condition feedback, completes mass data storage and computation by using an edge computing workstation, finally obtains feedback to make a reasonable emergency rescue scheme, and realizes real-time sharing with fire rescue vehicles and fire fighters.
The invention discloses a control method for an edge computing platform for serving a special hybrid vehicle, which comprises the following steps:
step 1) after a fire disaster occurs, a fire department knows the place where the fire disaster occurs, immediately arranges a special hybrid vehicle 3 to go to the place of the fire disaster for the first time, and carries out fire disaster rescue;
step 2) the unmanned aerial vehicle enters a fire scene, a GPS A18 in the unmanned aerial vehicle intelligent exploration module 1 determines position information and speed information acquired by the unmanned aerial vehicle, a gyroscope A19 acquires angular velocity in three coordinates to judge the flight direction of the unmanned aerial vehicle, an image acquisition module 15 acquires images of the fire scene, a temperature acquisition module 16 acquires the temperature of the fire scene, and a smoke concentration acquisition module 17 acquires the smoke concentration of the fire scene;
step 3) an information storage module 20 in the unmanned aerial vehicle intelligent detection module 1 stores information, and meanwhile, an information transceiver module A21 is connected with a special hybrid vehicle server 4 through short-distance communication 2 and transmits fire scene internal information collected by the unmanned aerial vehicle to the special hybrid vehicle server 4;
step 4), the special hybrid vehicle server 4 transmits the acquired fire scene information to a first base station 6 near the fire scene, and transmits the information to an edge computing workstation 12 in a fire station through a satellite 7, a second base station 8 and a fire monitoring server 10;
step 5), the edge computing workstation 12 calculates and predicts the fire condition and the damage condition in the building by using a cloud platform in combination with the fire building structure transmitted by the cloud of the building information server 11 and the fire scene condition, the temperature smoke intensity and the like transmitted by the unmanned aerial vehicle, plans an optimal emergency rescue route according to a simulation result, and uploads the optimal emergency rescue route to the special hybrid vehicle server 4;
and 6) the firefighter wears the augmented reality device 5 to enter a fire scene for rescue, the position of the firefighter is judged according to the GPS B in the augmented reality device 5, the special hybrid vehicle server 4 pushes the current floor information and the optimal action path in the display module 26 through the short-distance communication 2, the firefighter is guided to rapidly reach a target position, and the firefighter is prevented from being injured by collapse due to smoke diffusion, overlarge fire behavior and collapse of a house.
The working method of the invention is explained with reference to fig. 5:
as shown in fig. 5, one wounded person and one inflammable substance exist in the room, the right room beam may collapse due to the overhigh flame temperature, the door 1 and the door 3 cannot be opened due to the structural deformation caused by the overhigh temperature, and the door 2 and the window can pass through the fire source at a certain distance. According to the above information, the edge computing station 12 plans a rescue route: enters the room through the window, bypasses the barrier, first handles the combustibles to prevent secondary damage, then bypasses the possibly collapsed beam for rescue of the wounded, and then leaves the room through the door 2. The position is positioned according to the unmanned aerial vehicle, the optimal spraying angle and pressure of the fire-fighting lance are obtained through simulation, and the fire-fighting lance can be directly sprayed to a fire source, so that the purpose of rapidly controlling the fire condition is achieved.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention, and they are not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention should be included in the scope of the present invention.
Claims (9)
1. An edge computing platform for serving special hybrid vehicles is characterized by comprising an unmanned aerial vehicle intelligent exploration module (1), a special hybrid vehicle (3), a special hybrid vehicle server (4), augmented reality equipment (5), a first base station (6), a satellite (7), a second base station (8), a fire monitoring server (10), a building information server (11) and an edge computing workstation (12); the intelligent unmanned aerial vehicle exploration module (1) is connected with a special hybrid vehicle server (4) through short-distance communication (2), a firefighter wears an augmented reality device (5) and is connected with the special hybrid vehicle server (4) through the short-distance communication (2), the special hybrid vehicle server (4) is connected with a base station (6) through wireless communication, the base station (6) is connected with a satellite (7) through wireless communication, the satellite (7) is connected with a second base station (8) nearby the fire station through wireless communication, the second base station (8) is connected with a fire monitoring server (10) through wired communication (9), the fire monitoring server (10) is connected with an edge computing workstation (12) through wired communication (9), and a building information server (11) is connected with the edge computing workstation (12) through wired communication (9).
2. An edge computing platform serving a special hybrid vehicle as claimed in claim 1, wherein the unmanned aerial vehicle intelligent exploration module (1) comprises an unmanned aerial vehicle intelligent exploration module housing (13), a circuit board A (14), an image acquisition module (15), a temperature acquisition module (16), a smoke concentration acquisition module (17), a GPS A (18), a gyroscope A (19), an information storage module (20) and an information transceiving module A (21).
3. An edge computing platform serving a special hybrid vehicle according to claim 2, characterized in that the circuit board a (14) is mounted inside the unmanned aerial vehicle intelligent probe module housing (13); the image acquisition module (15), the temperature acquisition module (16), the smoke concentration acquisition module (17), the GPS A (18), the gyroscope A (19), the information storage module (20) and the information transceiving module A (21) are integrally installed on the circuit board, and information transmission is carried out by a circuit on the circuit board A (14); the information transceiver module A (21) is connected with the special hybrid vehicle server (4) through short-distance communication (2).
4. An edge computing platform for servicing a special hybrid vehicle as claimed in claim 2, characterised in that the image acquisition module (15) employs a camera or radar for acquiring fire scene image information and passing it to the information storage module (20).
5. An edge computing platform serving a special hybrid vehicle as claimed in claim 1, characterised in that the augmented reality device (5) comprises a circuit board B (22), a GPS B (23), a gyroscope B (24), an information transceiver module B (25), a display module (26).
6. The edge computing platform for servicing special type hybrid vehicles as claimed in claim 5, wherein the GPS B (23), the gyroscope B (24), the information transceiver module B (25) and the display module (26) are integrally installed on the circuit board B (22), and information transmission is carried out through a circuit on the circuit board B (22); the information transceiver module B (25) is connected with the special hybrid vehicle server (4) through short-distance communication (2).
7. An edge computing platform to serve a special hybrid vehicle as claimed in claim 1, characterized in that the special hybrid vehicle server (4) is installed on the special hybrid vehicle (3), the fire monitoring server (10), the building information server (11), the edge computing workstation (12) being arranged in a fire station.
8. The method for controlling the edge computing platform for serving a special hybrid vehicle according to any one of claims 1 to 7, wherein unified management and dynamic allocation are performed on the edge-side rescue service platform according to the demand of fire rescue on computing resources, interaction is performed with a plurality of cloud data centers according to real-time fire scene condition feedback, the edge computing workstation completes massive data storage and computation, finally obtains feedback to make a reasonable emergency rescue scheme, and realizes real-time sharing with fire rescue vehicles and firefighters.
9. A control method for serving an edge computing platform of a special hybrid vehicle according to claim 8, characterized in that the implementation of the control method comprises the following steps:
step 1) after a fire disaster occurs, a fire department knows the place where the fire disaster occurs, immediately arranges a special hybrid vehicle 3 to go to the place of the fire disaster for the first time, and carries out fire disaster rescue;
step 2) the unmanned aerial vehicle enters a fire scene, a GPS A (18) in an intelligent unmanned aerial vehicle exploration module 1 determines position information and speed information acquired by the unmanned aerial vehicle, a gyroscope A (19) acquires angular velocity in three coordinates to judge the flight direction of the unmanned aerial vehicle, an image acquisition module (15) acquires images of the fire scene, a temperature acquisition module (16) acquires the temperature of the fire scene, and a smoke concentration acquisition module (17) acquires the smoke concentration of the fire scene;
step 3), an information storage module (20) in the intelligent unmanned aerial vehicle exploration module 1 stores information, and meanwhile, an information transceiving module A (21) is connected with a special hybrid vehicle server (4) through short-distance communication (2) and transmits the fire scene internal information collected by the unmanned aerial vehicle to the special hybrid vehicle server (4);
step 4), the special hybrid vehicle server 4 transmits the acquired fire scene information to a first base station (6) near the fire scene, and transmits the information to an edge computing workstation (12) in a fire station through a satellite (7), a second base station (8) and a fire monitoring server (10);
step 5), the edge computing workstation (12) combines a fire building structure transmitted by the cloud of the building information server (11) and a fire scene condition, temperature smoke intensity and the like transmitted by the unmanned aerial vehicle, utilizes the cloud platform to compute and predict the fire condition and the damage condition in the building, plans an optimal emergency rescue route according to a simulation result, and uploads the optimal emergency rescue route to the special hybrid vehicle server (4);
and step 6) the firefighter wears the augmented reality device (5) to enter a fire scene for rescue, the position of the firefighter is judged according to the GPS B in the augmented reality device (5), the special hybrid vehicle server (4) pushes the current floor information and the optimal action path in the display module (26) through short-distance communication (2), the firefighter is guided to rapidly reach a target position, and the firefighter is prevented from being injured by collapse of a house due to diffusion of smoke and overlarge fire.
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| CN108737510A (en) * | 2018-04-28 | 2018-11-02 | 深圳万发创新进出口贸易有限公司 | Intelligent fire monitoring system based on augmented reality |
| CN108734356A (en) * | 2018-05-25 | 2018-11-02 | 中国电子科技集团公司第二十八研究所 | A kind of indoor positioning in the case of fire fighting and rescue and paths planning method |
| CN109323694A (en) * | 2018-08-27 | 2019-02-12 | 广东容祺智能科技有限公司 | A kind of indoor positioning and search and rescue system based on unmanned plane |
| US10262437B1 (en) * | 2018-10-31 | 2019-04-16 | Booz Allen Hamilton Inc. | Decentralized position and navigation method, device, and system leveraging augmented reality, computer vision, machine learning, and distributed ledger technologies |
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| CN115146933A (en) * | 2022-06-20 | 2022-10-04 | 深圳市城市公共安全技术研究院有限公司 | Processing method, system, equipment and storage medium for dangerous source explosion accident |
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