CN114399888A - Mountain disaster early warning system - Google Patents
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- CN114399888A CN114399888A CN202210003006.9A CN202210003006A CN114399888A CN 114399888 A CN114399888 A CN 114399888A CN 202210003006 A CN202210003006 A CN 202210003006A CN 114399888 A CN114399888 A CN 114399888A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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Abstract
The invention discloses a mountain disaster early warning system, and relates to the technical field of mountain disaster early warning. The method comprises the following steps: the system comprises a monitoring device, a positioning device, a wireless communication module and a mobile terminal; the monitoring device is arranged at a monitoring position of a mountain body and used for acquiring geological information of a preset monitoring area; the positioning device is used for acquiring the position information of a preset monitoring area; the wireless communication module is used for sending the geological information and the position information to the mobile terminal; the mobile terminal predicts the probability of mountain disaster occurrence based on geological information; and generating first prompt information based on the probability of mountain disaster occurrence and the position information, wherein the first prompt information is used for prompting the probability of mountain disaster occurrence in the area corresponding to the position information. People who hold the mobile terminal can make emergency preparation according to the first prompt message, and life and property safety is guaranteed.
Description
Technical Field
The invention relates to the technical field of mountain disaster early warning, in particular to a mountain disaster early warning system.
Background
Landslide and debris flow are common mountain disasters, and landslide and debris flow disaster events occur all around the world every year. The land landslide and debris flow geological disasters can bring life and property threats to people living near or working in the mountain or inconvenience in production and life.
Therefore, how to effectively monitor landslide and debris flow, effectively early warning is carried out before a disaster happens, and early warning information is timely transmitted to people, so that the problem to be solved urgently is formed.
Disclosure of Invention
The invention aims to provide a mountain disaster early warning system, which is used for solving the problems that people living near or working in a mountain cannot predict mountain disasters and cannot prepare emergency and risk avoidance in advance to suffer life and property loss.
In order to achieve the above purpose, the invention provides the following technical scheme: a mountain disaster early warning system may include: the system comprises a monitoring device, a positioning device, a wireless communication module and a mobile terminal;
the monitoring device is arranged at a monitoring position of a mountain body and used for acquiring geological information of a preset monitoring area;
the positioning device is used for acquiring the position information of the preset monitoring area;
the wireless communication module is used for sending the geological information and the position information to the mobile terminal;
the mobile terminal predicts the probability of mountain disaster occurrence based on the geological information; and generating first prompt information based on the probability of the mountain disaster and the position information, wherein the first prompt information is used for prompting the probability of the mountain disaster in the area corresponding to the position information.
Optionally, the geological information may include infrasonic information, rainfall information, ground stress information, ground deformation information, water pressure information, and mountain inclination information;
the mobile terminal carries out wavelet decomposition on the infrasonic wave information and judges whether the infrasonic wave information is abnormal or not;
and inputting the rainfall information, the ground stress information, the ground deformation information, the water pressure information and the mountain inclination information into a neural network model when the infrasonic wave information is confirmed to be abnormal, so as to obtain the probability of mountain disaster.
Optionally, the mountain disaster early warning system may further include a cloud server, the wireless communication module sends the geological information and the location information to the cloud server, and the mobile terminal sends the probability of occurrence of the mountain disaster to the cloud server;
the cloud server stores the geological information and the probability of the mountain disaster.
Optionally, the cloud server performs big data analysis on the geological information, the probability of occurrence of the mountain disaster and the actual situation of occurrence of the mountain disaster to correct the neural network model.
Optionally, the wireless communication module may be configured as a 5g module.
Alternatively, the monitoring device may include a rainfall monitor that acquires rainfall information, a video monitoring device that acquires video information, a ground stress monitoring device that acquires ground stress information, an infrasonic monitoring device that acquires infrasonic information, a ground deformation monitoring device that acquires ground deformation information, a water pressure monitoring device that acquires water pressure information, and a mountain tilt monitoring device that acquires mountain tilt information.
Optionally, the wireless communication module may transmit the geological information and the location information at preset time intervals.
Optionally, the mobile terminal may adjust the preset time interval according to an abnormal condition of the infrasonic information, where the preset time interval when the infrasonic information is abnormal is smaller than the preset time interval when the infrasonic information is normal.
Optionally, the mobile terminal may be further configured to receive disaster information input by a user, and generate second prompt information according to the disaster information.
Optionally, when the disaster information is disaster occurrence confirmation information, the mobile terminal analyzes the video information of the disaster occurrence area indicated by the disaster occurrence confirmation information to confirm whether a disaster occurs, and generates the second prompt information when the disaster occurs, where the second prompt information is used for prompting the disaster occurrence and the position of the disaster occurrence.
The invention has the following beneficial effects: the mountain disaster early warning system provided by the invention can monitor geological information of a mountain, transmit the geological information to the mobile terminal, process and analyze the geological information by the mobile terminal to obtain the probability of mountain disaster occurrence, and timely generate first prompt information by the mobile terminal based on the probability of mountain disaster occurrence, wherein the first prompt information is used for prompting the position and the probability of mountain disaster occurrence. People who hold the mobile terminal can make emergency preparation according to the first prompt message, and life and property safety is guaranteed.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic structural diagram of a mountain disaster warning system according to some embodiments of the present invention;
FIG. 2 is a flow chart illustrating the generation of a first reminder by a mobile terminal in some embodiments of the invention;
FIG. 3 is a schematic diagram of a mobile terminal and user interaction interface shown in some embodiments of the invention.
Detailed Description
In order to facilitate clear description of technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish the same items or similar items having substantially the same functions and actions. For example, the first threshold and the second threshold are only used for distinguishing different thresholds, and the sequence order of the thresholds is not limited. Those skilled in the art will appreciate that the terms "first," "second," etc. do not denote any order or quantity, nor do the terms "first," "second," etc. denote any order or importance.
It is to be understood that the terms "exemplary" or "such as" are used herein to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
Referring to fig. 1, a mountain disaster early warning system provided by the present invention is described. The mountain disaster early warning system is used for monitoring and early warning landslides and debris flows. The device comprises a monitoring device, a positioning device, a wireless communication module and a mobile terminal. The monitoring device and the wireless communication module can be connected through wired communication, the wireless communication module can be integrated on the monitoring device, the positioning device can be connected with the wireless communication module through wired communication, the positioning device can also be integrated on the monitoring device, and the wireless communication module is connected with the mobile terminal through wireless communication.
The monitoring device is arranged at the monitoring position of the mountain body and used for acquiring geological information of a preset monitoring area. The positioning device is used for acquiring the position information of a preset monitoring area. And the wireless communication module sends the geological information and the position information to the mobile terminal.
And the mobile terminal processes and analyzes the geological information and predicts the probability of mountain disaster. When the mountain disaster is predicted to occur with a certain probability, first prompt information is generated. The first prompt information is used for prompting the probability of mountain disaster occurrence in the area corresponding to the position information.
Therefore, people living near or working in the mountain can carry the mobile terminal with the mobile terminal, and the mobile terminal sends out first prompt information to warn people to prepare for emergency when the risk of mountain disasters is predicted. People can effectively avoid life and property loss caused by mountain disasters.
The mobile terminal can also be used for people to actively inquire the geological information of the mountain, and when the mobile terminal does not generate the first prompt information (the mobile terminal judges that no danger of mountain disasters occurs), people can also actively inquire the geological information of the mountain, make corresponding judgment through own analysis and processing, and guide own production and life.
A mobile terminal may also be referred to as a mobile communication terminal. May represent a computer device used in mobility, for example: the mobile terminal can be a mobile phone, a notebook, a tablet computer, a POS machine or a vehicle-mounted computer, and the like. Taking a mobile phone as an example, the mobile phone is provided with early warning software, the processing of geological information and position information is executed in the early warning software, and first prompt information is displayed in the early warning software.
For the system in fig. 1, the mobile terminal may perform the warning by using the following embodiments, which are described with reference to fig. 2:
the geological information comprises infrasonic wave information, rainfall information, ground stress information, ground deformation information, water pressure information and mountain inclination information.
The mobile terminal carries out wavelet decomposition on the infrasonic wave information and judges whether the infrasonic wave information is abnormal or not;
if the infrasonic wave signal is not abnormal, the operation is not carried out;
if the infrasonic wave information is abnormal, inputting rainfall information, ground stress information, ground deformation information, water pressure information and mountain inclination information into a neural network model to obtain the probability of mountain disaster occurrence;
judging whether the probability of mountain disaster occurrence is smaller than a preset threshold value or not;
if yes, no prompt message is generated;
and if not, generating first prompt information.
The first prompt information is described by taking an area a of a mountain as an example, the preset threshold is set to 20%, and if the probability of mountain disaster occurrence is predicted by the mobile terminal to be 20% -30%, the first prompt information generates and sends an area a green alarm, and the position of the area a can be marked in the form of characters and a map. When the probability is 30% -60%, the first prompt message is a yellow alarm; when the probability is 60% -80%, the first prompt message is a red alarm; when the probability is 80% -100%, the first prompt message is a whistling alarm.
The infrasonic wave information received by the mobile terminal can be generated by landslide (debris flow) and also can be generated by artificial activities, waterfall, wind, rain, thunder and lightning and the like. Since wavelet decomposition has good localization properties in both frequency and time domains, and has the advantage of adaptive resolution analysis, lower time resolution and higher frequency resolution are used for the low frequency part, and progressively finer frequency and time domain sampling steps are used in the high frequency part, so that every detail of the infrasonic signal can be found. Because the noise generated by artificial activities, waterfall, wind, rain, thunder, lightning and the like and the infrasonic wave signal generated by landslide have obviously different characteristics after wavelet decomposition, the noise part can be effectively removed by utilizing the wavelet decomposition, so that the judgment on the infrasonic wave signal is more accurate.
After the infrasonic signal is judged to be abnormal (namely, the infrasonic signal is judged to be generated by landslide (debris flow)), rainfall information, ground stress information, ground deformation information, pore water pressure information and mountain inclination information are input into a neural network model as characteristics, the neural network model trains and determines a threshold value and a weight through an error inverse propagation algorithm so that the output of the neural network model is closest to the actual expected effect, and the neural network model outputs the probability of occurrence of the mountain disaster (the landslide or the debris flow) through a probability type transformation function on the basis of the mapping relation of input and output.
Because the infrasonic wave information is the final index for predicting whether the mountain disaster occurs or not, after the infrasonic wave information is judged to be abnormal, the probability of the mountain disaster is greater than 0, and at the moment, the rainfall information, the ground stress information, the ground deformation information, the pore water pressure information and the mountain inclination information are analyzed by adopting a neural network algorithm, so that the obtained prediction probability is more accurate.
The mountain disaster early warning system can further comprise a cloud server, the wireless communication module sends geological information and position information to the cloud server, and the mobile terminal sends the probability of mountain disaster occurrence to the cloud server; the cloud server stores geological information and probability of mountain disaster occurrence.
And the cloud server stores the geological information and the mountain disaster occurrence probability predicted by the mobile terminal so as to facilitate the tracing of the historical data by the staff.
The cloud server can also perform big data analysis on geological information, the probability of mountain disaster occurrence and the actual situation of mountain disaster occurrence so as to correct the neural network model. For example, after confirming that the mountain disaster occurs, the cloud server performs big data analysis on geological information, the mountain disaster occurrence probability predicted by the mobile terminal and the actual situation of whether the mountain disaster occurs or not, corrects each data threshold of the neural network model based on statistical distribution or density clustering, and then predicts the network model corrected according to the data threshold by the mobile terminal, so that the early warning accuracy of the mobile terminal can be further improved.
The wireless communication module is preferably provided as a 5g module, which 5g module can be integrated into the respective monitoring device.
The 5g module has high data transmission speed, can transmit geological information to the mobile terminal in time for the mobile terminal to process and analyze, and improves the timeliness of early warning.
The monitoring device comprises a rainfall monitor for acquiring rainfall information, a video monitoring device for acquiring video information, a ground stress monitoring device for acquiring ground stress information, an infrasonic wave monitoring device for acquiring infrasonic wave information, a ground deformation monitoring device for acquiring ground deformation information, a water pressure monitoring device for acquiring water pressure information and a mountain inclination monitoring device for acquiring mountain inclination information.
Wherein, the monitoring devices can be arranged in multiple layers according to the size and type of the mountain; the method comprises the steps of arranging monitoring devices in a stepped mode for a low mountain and a middle mountain, installing a mountain inclination monitoring device and an infrasonic wave monitoring device at a steep slope, installing a ground deformation monitoring device at a flat area, installing a pore water pressure monitoring device at a gully, and installing a ground stress monitoring device at the root of the mountain. Monitoring devices can be respectively arranged in four directions for the mountains to carry out comprehensive monitoring; the mountain can be divided into ridges and arranged layer by layer.
The wireless communication module sends geological information and position information according to a preset time interval.
The wireless communication module has larger power consumption, sends geological information and position information according to a preset time interval, can reduce the consumption of the power and reduce the times of replacing a power supply. The preset time interval may be 15 minutes, or other duration.
The mobile terminal adjusts the preset time interval according to the abnormal condition of the infrasonic wave information, and the preset time interval when the infrasonic wave information is abnormal is smaller than the preset time interval when the infrasonic wave information is normal.
And when the mobile terminal judges that the infrasonic wave information is abnormal, reducing the time interval of information transmission of the wireless communication module, and recovering the preset time interval of information transmission of the wireless communication module when the infrasonic wave signal is normal. Therefore, the power consumption of the wireless communication module can be reduced, the wireless communication module can be guaranteed to transmit the geological information to the mobile terminal in time when the geological information is abnormal, and the mobile terminal can process and analyze in time and make early warning.
The mobile terminal is further used for receiving disaster information input by the user and generating second prompt information according to the disaster information.
Fig. 3 is a schematic diagram of an interactive interface of a mobile terminal, and people can click "disaster information input" on the mobile terminal to input disaster information. And clicking 'geological information query' to query geological information. When the prompt message is generated, the prompt message appears in a prompt message column.
The mobile terminal analyzes video information of a disaster occurrence area indicated by the disaster occurrence confirmation information to confirm whether a disaster occurs, and generates second prompt information when the disaster occurs, wherein the second prompt information is used for prompting that the disaster has occurred and the position of the disaster.
Therefore, when mountain disasters are found, people can input disaster situation confirmation information on the mobile terminal in time, the mobile terminal can call video information of a disaster situation occurrence area indicated by the disaster situation confirmation information after receiving the disaster situation confirmation information, and second prompt information is generated when the disaster situation is confirmed. Such as landslide or debris flow in area a. After receiving the second prompt message, the user can take corresponding measures or eliminate the dangerous case; or to replace the travel route in advance due to a road blockage caused by a disaster. As most people hold the mobile terminal, the mobile terminal is added with the disaster information receiving function, and the timeliness of finding dangerous cases can be properly increased.
The disaster information can also be early warning information of the user, if the user sees that cracks appear in the area A on a mountain and the risk of falling rocks exist, the information can be input into the mobile terminal, the mobile terminal can call video information of the area, and second prompt information is generated after judging that the risk of falling rocks exists really, and the second prompt information is used for prompting early warning content, if the risk of falling rocks exists in the area A.
The disaster information can also be prediction information of the user, the user can check geological information through the mobile terminal, the conclusion that mountain disasters are about to occur is obtained through analysis of the geological information, and then the conclusion is input into the mobile terminal. The mobile terminal sends the prediction information of the user to the cloud server. And the cloud server stores the prediction information, compares the prediction information with the actual situation of whether the disaster happens or not, and judges the accuracy of the prediction information. The cloud server counts the prediction times and the accuracy of the user, and when the prediction times and the accuracy of the user reach preset thresholds, the user is marked as an expert user, and if one user predicts that mountain disasters occur for 100 times, the mountain disasters occur for 95 times. When the mobile terminal receives the prediction information of the expert user and the mobile terminal predicts through the neural network model and judges that the mountain disaster probability is less than 20% and the first information is not generated, the mobile terminal generates second prompt information which is used for prompting the expert user to perform early warning and informing people of preparing emergency. The mobile terminal is added with the function of receiving the prediction information of the user, the attention degree of the user to geological information and an early warning system can be increased, and the disaster prevention consciousness is improved.
While the invention has been described in connection with various embodiments, other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a review of the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other elements or steps, and the word "a" or "an" does not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
While the invention has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the invention. Accordingly, the specification and figures are merely exemplary of the invention as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the invention. It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A mountain disaster early warning system, comprising: the system comprises a monitoring device, a positioning device, a wireless communication module and a mobile terminal;
the monitoring device is arranged at a monitoring position of a mountain body and used for acquiring geological information of a preset monitoring area;
the positioning device is used for acquiring the position information of the preset monitoring area;
the wireless communication module is used for sending the geological information and the position information to the mobile terminal;
the mobile terminal predicts the probability of mountain disaster occurrence based on the geological information; and generating first prompt information based on the probability of the mountain disaster and the position information, wherein the first prompt information is used for prompting the probability of the mountain disaster in the area corresponding to the position information.
2. The mountain disaster early warning system of claim 1, wherein the geological information comprises infrasonic information, rainfall information, ground stress information, ground deformation information, water pressure information and mountain inclination information;
the mobile terminal carries out wavelet decomposition on the infrasonic wave information and judges whether the infrasonic wave information is abnormal or not;
and when the infrasonic wave information is confirmed to be abnormal, inputting the rainfall information, the ground stress information, the ground deformation information, the water pressure information and the mountain inclination information into a neural network model to obtain the probability of mountain disaster.
3. The mountain disaster early warning system according to claim 2, further comprising a cloud server, wherein the wireless communication module transmits the geological information and the location information to the cloud server, and the mobile terminal transmits the probability of occurrence of the mountain disaster to the cloud server;
the cloud server stores the geological information and the probability of the mountain disaster.
4. The mountain disaster early warning system according to claim 3, wherein the cloud server performs big data analysis on the geological information, the probability of occurrence of the mountain disaster and the actual situation of occurrence of the mountain disaster to modify the neural network model.
5. The mountain disaster early warning system of claim 1, wherein the wireless communication module is configured as a 5g module.
6. The mountain disaster early warning system according to claim 2, wherein the monitoring devices comprise a rainfall monitor for acquiring rainfall information, a video monitoring device for acquiring video information, a ground stress monitoring device for acquiring ground stress information, an infrasonic monitoring device for acquiring infrasonic information, a ground deformation monitoring device for acquiring ground deformation information, a water pressure monitoring device for acquiring water pressure information, and a mountain inclination monitoring device for acquiring mountain inclination information.
7. The mountain disaster early warning system of claim 2, wherein the wireless communication module transmits the geological information and the location information at preset time intervals.
8. The mountain disaster early warning system according to claim 7, wherein the mobile terminal adjusts the preset time interval according to an abnormal condition of the infrasonic information, and the preset time interval when the infrasonic information is abnormal is smaller than the preset time interval when the infrasonic information is normal.
9. The mountain disaster early warning system of claim 6, wherein the mobile terminal is further configured to receive disaster information input by a user, and generate second prompt information according to the disaster information.
10. The mountain disaster early warning system of claim 9, wherein when the disaster information is disaster occurrence confirmation information, the mobile terminal analyzes video information of a disaster occurrence area indicated by the disaster occurrence confirmation information to confirm whether a disaster occurs, and generates the second prompt information when the disaster occurs, and the second prompt information is used for prompting the occurrence of the disaster and a location where the disaster occurs.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115546613A (en) * | 2022-12-01 | 2022-12-30 | 成都理工大学 | Debris flow identification method and device based on infrasonic waves |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184619A (en) * | 2011-04-27 | 2011-09-14 | 中科恒源科技股份有限公司 | System and method for monitoring, preventing and treating geologic disasters |
| CN202887397U (en) * | 2012-11-13 | 2013-04-17 | 四川大学 | Geological environment disaster video monitor |
| CN103729969A (en) * | 2014-01-09 | 2014-04-16 | 四川大学 | System and method for embedded type geological disaster video monitoring early warning |
| CN103743441A (en) * | 2014-01-20 | 2014-04-23 | 马鞍山南山开发公司 | Multi-factor coupling on-line monitoring system and multi-factor coupling on-line monitoring system method for slope safety |
| CN104598737A (en) * | 2015-01-23 | 2015-05-06 | 水利部南京水利水文自动化研究所 | Method and system for forecasting debris flow |
| CN106128035A (en) * | 2016-06-30 | 2016-11-16 | 西安工程大学 | The geological disaster forecasting method merged based on neutral net and multi-parameter information |
| CN106803221A (en) * | 2015-11-26 | 2017-06-06 | 中国电力科学研究院 | A kind of geological disaster mass presdiction and disaster prevention method |
| CN107705515A (en) * | 2017-11-30 | 2018-02-16 | 四川领创者科技有限公司 | A kind of geological disaster monitoring system based on big data |
| CN108898800A (en) * | 2018-09-07 | 2018-11-27 | 中国地质调查局西安地质调查中心 | A kind of geo-hazard early-warning method adding technology based on internet |
| CN208363068U (en) * | 2018-05-28 | 2019-01-11 | 西南交通大学 | A kind of high precipitous rock slope monitoring system |
| CN208568762U (en) * | 2018-04-08 | 2019-03-01 | 福建师范大学 | Landslide state monitor |
| CN109872509A (en) * | 2019-04-02 | 2019-06-11 | 西安邮电大学 | Massif Geological Hazards Monitoring and early warning system and method based on the twin driving of number |
| CN110264672A (en) * | 2019-06-25 | 2019-09-20 | 广州市城市规划勘测设计研究院 | A kind of early warning system of geological disaster |
| CN113034017A (en) * | 2021-03-31 | 2021-06-25 | 重庆城市管理职业学院 | Application security service platform based on cloud computing |
| CN113592451A (en) * | 2021-07-30 | 2021-11-02 | 四川省建筑科学研究院有限公司 | Civil engineering accidental state monitoring data acquisition method, storage medium, gateway and system |
-
2022
- 2022-01-04 CN CN202210003006.9A patent/CN114399888A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184619A (en) * | 2011-04-27 | 2011-09-14 | 中科恒源科技股份有限公司 | System and method for monitoring, preventing and treating geologic disasters |
| CN202887397U (en) * | 2012-11-13 | 2013-04-17 | 四川大学 | Geological environment disaster video monitor |
| CN103729969A (en) * | 2014-01-09 | 2014-04-16 | 四川大学 | System and method for embedded type geological disaster video monitoring early warning |
| CN103743441A (en) * | 2014-01-20 | 2014-04-23 | 马鞍山南山开发公司 | Multi-factor coupling on-line monitoring system and multi-factor coupling on-line monitoring system method for slope safety |
| CN104598737A (en) * | 2015-01-23 | 2015-05-06 | 水利部南京水利水文自动化研究所 | Method and system for forecasting debris flow |
| CN106803221A (en) * | 2015-11-26 | 2017-06-06 | 中国电力科学研究院 | A kind of geological disaster mass presdiction and disaster prevention method |
| CN106128035A (en) * | 2016-06-30 | 2016-11-16 | 西安工程大学 | The geological disaster forecasting method merged based on neutral net and multi-parameter information |
| CN107705515A (en) * | 2017-11-30 | 2018-02-16 | 四川领创者科技有限公司 | A kind of geological disaster monitoring system based on big data |
| CN208568762U (en) * | 2018-04-08 | 2019-03-01 | 福建师范大学 | Landslide state monitor |
| CN208363068U (en) * | 2018-05-28 | 2019-01-11 | 西南交通大学 | A kind of high precipitous rock slope monitoring system |
| CN108898800A (en) * | 2018-09-07 | 2018-11-27 | 中国地质调查局西安地质调查中心 | A kind of geo-hazard early-warning method adding technology based on internet |
| CN109872509A (en) * | 2019-04-02 | 2019-06-11 | 西安邮电大学 | Massif Geological Hazards Monitoring and early warning system and method based on the twin driving of number |
| CN110264672A (en) * | 2019-06-25 | 2019-09-20 | 广州市城市规划勘测设计研究院 | A kind of early warning system of geological disaster |
| CN113034017A (en) * | 2021-03-31 | 2021-06-25 | 重庆城市管理职业学院 | Application security service platform based on cloud computing |
| CN113592451A (en) * | 2021-07-30 | 2021-11-02 | 四川省建筑科学研究院有限公司 | Civil engineering accidental state monitoring data acquisition method, storage medium, gateway and system |
Non-Patent Citations (2)
| Title |
|---|
| 欧文浩: "基于云环境的地质灾害移动服务系统研究", pages 5 * |
| 河南省地质环境监测院: "《河南省地质灾害及防治研究（上卷）》", 黄河水利出版社 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115546613A (en) * | 2022-12-01 | 2022-12-30 | 成都理工大学 | Debris flow identification method and device based on infrasonic waves |
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