An artificial intelligence-based mountain landslide risk intelligent monitoring system

Abstract

The application discloses a mountain landslide risk intelligent monitoring system based on artificial intelligence and relates to the technical field of mountain landslide monitoring.The technical problem that the mountain area cannot be macroscopically monitored and internally displaced, so that the mountain area cannot be risk monitored in the prior art, is solved.The mountain area risk assessment unit assesses the risk of the mountain area, obtains the risk assessment coefficient of the sub-area in the mountain area monitoring period, divides the sub-area into a high-risk area and a low-risk area according to the risk assessment coefficient comparison, and sets different data acquisition periods for different area types.The geological macroscopic monitoring unit performs geological macroscopic monitoring on each sub-area, and the real-time displacement monitoring unit performs real-time displacement monitoring on the sub-area.The influence monitoring and analysis unit performs influence monitoring and analysis on the sub-area, and the real-time image monitoring unit performs real-time monitoring on the mountain management and control of the sub-area.

Description

Technical Field

[0001] This invention relates to the field of landslide monitoring technology, specifically to an intelligent landslide risk monitoring system based on artificial intelligence. Background Technology

[0002] A landslide refers to the movement of a portion of rock and soil on a mountain slope downwards as a whole, under the influence of gravity (including the weight of the rock and soil itself and the dynamic and static pressure of groundwater) and shear displacement along a certain weak structural surface (zone).

[0003] However, in the existing technology, risk assessment of mountain areas cannot be carried out, resulting in a lack of targeted landslide monitoring. In addition, macroscopic monitoring and internal displacement monitoring of mountain areas are not possible, which makes risk monitoring of mountain areas impossible and reduces monitoring efficiency. Furthermore, the analysis cannot be combined with environmental impact and the mountain itself, resulting in low impact monitoring efficiency.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problems mentioned above by proposing an intelligent monitoring system for landslide risk based on artificial intelligence.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] An intelligent monitoring system for landslide risk based on artificial intelligence includes a monitoring platform, which is communicatively connected to a mountain area risk assessment unit, an impact monitoring and analysis unit, a body monitoring and analysis unit, and a real-time image monitoring unit.

[0008] The mountain area risk assessment unit conducts risk assessment on the mountain area, divides the mountain area into i sub-regions, where i is a natural number greater than 1, and each sub-region includes the top and bottom of the mountain. It obtains the risk assessment coefficient of the sub-regions during the monitoring period of the mountain area, and divides the sub-regions into high-risk areas and low-risk areas based on the comparison of the risk assessment coefficients. Different data collection cycles are set for different area types.

[0009] The body monitoring and analysis unit is connected to the geological macro monitoring unit and the real-time displacement monitoring unit. The geological macro monitoring unit performs geological macro monitoring of each sub-region, generates geological risk signals or geological safety signals through analysis, and sends them to the body monitoring and analysis unit, along with the current sub-region number, to the monitoring platform. The real-time displacement monitoring unit performs real-time displacement monitoring of the sub-region, generates displacement anomaly signals or normal displacement signals through real-time displacement monitoring, and sends them to the body monitoring and analysis unit, which then forwards them to the monitoring platform.

[0010] The impact monitoring and analysis unit performs impact monitoring and analysis on the sub-region, generates impact monitoring abnormal signals or impact monitoring normal signals through impact monitoring and analysis, and sends them to the monitoring platform. Upon receiving the impact monitoring abnormal signals, displacement abnormal signals, or geological risk signals, the monitoring platform will implement mountain control measures on the corresponding sub-region. After the mountain control measures are implemented, the real-time image monitoring unit will monitor the mountain control measures in the sub-region in real time.

[0011] As a preferred embodiment of the present invention, the operation process of the mountain area risk assessment unit is as follows:

[0012] When the furthest point of the sub-region corresponding to the top of the mountain exceeds the bottom of the mountain during the current monitoring period, obtain the rate of decrease of the tilt angle between the furthest point of the mountain top and the bottom of the mountain; obtain the span of decrease of the number of surviving trees in the extended mountain area corresponding to the top of the mountain exceeding the bottom of the mountain during the current monitoring period; obtain the duration of surface water flow connecting the top and bottom of the mountain in the sub-region during the current monitoring period.

[0013] The risk assessment coefficients of sub-regions within the monitoring period of the mountain area were obtained through analysis. The risk assessment coefficients of sub-regions within the monitoring period of the mountain area were compared with the risk assessment coefficient thresholds. If the risk assessment coefficient of a sub-region within the monitoring period of the mountain area exceeded the risk assessment coefficient threshold, the corresponding sub-region was marked as a high-risk area. If the risk assessment coefficient Di of a sub-region within the monitoring period of the mountain area did not exceed the risk assessment coefficient threshold, the corresponding sub-region was marked as a low-risk area.

[0014] As a preferred embodiment of the present invention, the operation process of the geological macro-monitoring unit is as follows:

[0015] The system identifies areas where cracks appear in the mountain within the current monitoring period and marks them as crack areas. Based on these crack areas, the corresponding locations are divided into high and low regions. The system then obtains the increase in the deviation value of the mountain displacement velocity corresponding to the high and low regions within the monitoring period, as well as the rate of increase in the numerical value of the height difference between the high and low regions before and after the cracks appear. These values ​​are then compared with thresholds for the increase in deviation value and the rate of increase in numerical value.

[0016] If the increase in the deviation value of the mountain displacement velocity corresponding to the high and low areas exceeds the deviation value increase threshold during the monitoring period, or if the increase rate of the difference in the mountain position height between the high and low areas before and after the crack area is generated exceeds the value increase rate threshold, then the corresponding crack area will be marked as a danger area; if the increase in the deviation value of the mountain displacement velocity corresponding to the high and low areas does not exceed the deviation value increase threshold during the monitoring period, and the increase rate of the difference in the mountain position height between the high and low areas before and after the crack area is generated does not exceed the value increase rate threshold, then the corresponding crack area will be marked as a safe area.

[0017] As a preferred embodiment of the present invention, the frequency of successive occurrence of dangerous areas and the rate of increase in the number of safe areas within a sub-region during the monitoring period of the mountain area are obtained. If the frequency of successive occurrence of dangerous areas within a sub-region during the monitoring period of the mountain area exceeds the successive occurrence frequency threshold, or the rate of increase in the number of safe areas exceeds the rate of increase in the number threshold, a geological risk signal is generated and sent to the main body monitoring and analysis unit, and the current sub-region number is also transferred to the monitoring platform.

[0018] If the frequency of successive occurrences of dangerous areas within a sub-region during the monitoring period of the mountain area does not exceed the successive occurrence frequency threshold, and the rate of increase in the number of safe areas does not exceed the rate of increase threshold, then a geological safety signal is generated and sent to the main body monitoring and analysis unit, and the current sub-region number is also transferred to the monitoring platform.

[0019] In a preferred embodiment of the present invention, the operation process of the real-time displacement monitoring unit is as follows:

[0020] The instantaneous displacement fluctuation values ​​of slip zone soil at non-slope locations in adjacent sub-regions during the monitoring period of the mountain area are obtained, as well as the frequency of uniform displacement at any location of slip zone soil in non-adjacent sub-regions. These values ​​are then compared with the instantaneous displacement value threshold and the uniform displacement frequency threshold, respectively.

[0021] If, during the monitoring period of the mountain area, the instantaneous displacement value of the slip zone soil at the corresponding non-slope location in the adjacent sub-region exceeds the instantaneous displacement value threshold, or if the frequency of the slip zone soil at any location in the non-adjacent sub-region moving in the same direction exceeds the same direction displacement frequency threshold, a displacement anomaly signal is generated and sent together with the corresponding sub-region number to the main body monitoring and analysis unit, which then forwards it to the monitoring platform.

[0022] If, during the monitoring period of the mountain area, the instantaneous displacement fluctuation value of the slip zone soil at the corresponding non-slope location in the adjacent sub-region does not exceed the instantaneous displacement value threshold, and the frequency of the same-trend displacement of any location of the slip zone soil in the non-adjacent sub-region does not exceed the same-trend displacement frequency threshold, then a normal displacement signal is generated and sent together with the corresponding sub-region number to the main body monitoring and analysis unit, which then forwards it to the monitoring platform.

[0023] In a preferred embodiment of the present invention, the operation process of the impact monitoring and analysis unit is as follows:

[0024] The study obtains the excess of runoff velocity on the mountain slopes of sub-regions during the period of increased rainfall compared to the runoff velocity during the non-rainfall phase. It also obtains the rate of increase in sediment content in the runoff discharge water of sub-regions during the period of increased rainfall. The excess of runoff velocity on the mountain slopes of sub-regions compared to the runoff velocity during the non-rainfall phase, and the rate of increase in sediment content in the runoff discharge water of sub-regions are compared with the velocity excess threshold and the sediment content increase rate threshold, respectively.

[0025] As a preferred embodiment of the present invention, if the excess of the runoff velocity on the slope of the mountain in the sub-region compared with the runoff velocity during the non-rainfall period exceeds the velocity excess threshold, or if the rate of increase of sediment content in the runoff water discharged from the slope of the mountain in the sub-region exceeds the sediment content increase rate threshold, then the sub-region is determined to be abnormal in the impact monitoring analysis, an impact monitoring abnormal signal is generated, and the impact monitoring abnormal signal and the corresponding sub-region number are sent to the monitoring platform together.

[0026] If the excess of the runoff velocity on the mountain slope during the non-rainfall period in the sub-region does not exceed the velocity excess threshold, and the rate of increase of sediment content in the runoff discharge water in the sub-region does not exceed the sediment content increase rate threshold, then the sub-region impact monitoring analysis is determined to be normal, an impact monitoring normal signal is generated, and the impact monitoring normal signal and the corresponding sub-region number are sent to the monitoring platform together.

[0027] In a preferred embodiment of the present invention, the operation process of the real-time image monitoring unit is as follows:

[0028] Using the mountain control location as the image acquisition center point, the initial image of the current mountain control location is acquired at the moment of mountain control implementation. After the implementation of mountain control, images of the mountain control location are acquired at set intervals, and the images are sorted according to the acquisition order to build an image library. The increase rate of the numerical interval difference of the mountain displacement at the mountain control location in the image library of adjacent acquired images during the mountain control period, as well as the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of mountain control, are obtained. The increase rate of the numerical interval difference of the mountain displacement at the mountain control location in the image library of adjacent acquired images during the mountain control period, as well as the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of mountain control, are compared with the threshold of the increase rate of the interval difference and the threshold of the decrease in the displacement velocity, respectively.

[0029] In a preferred embodiment of the present invention, if the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period exceeds the threshold for the rate of increase of the interval difference, or if the reduction in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared to the mountain displacement velocity before the implementation of the mountain control exceeds the threshold for the reduction in displacement velocity, then a control and rectification signal is generated and sent to the monitoring platform. After receiving the signal, the monitoring platform increases the type of control measures implemented in the mountain control area. If the control efficiency remains unchanged, a landslide warning is issued.

[0030] If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period exceeds the threshold for the rate of increase of the interval difference, and the reduction of the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of the mountain control exceeds the threshold for the reduction of the displacement velocity, then a landslide warning signal is generated and sent to the monitoring platform.

[0031] If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period does not exceed the threshold for the rate of increase of the interval difference, and the reduction of the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of the mountain control does not exceed the threshold for the reduction of displacement velocity, then a continuous control signal is generated and sent to the monitoring platform.

[0032] Compared with the prior art, the beneficial effects of the present invention are:

[0033] 1. In this invention, risk assessment is conducted on mountain areas based on topography or topographic composition analysis, thereby improving the accuracy of landslide monitoring, ensuring the targeted nature of data collection and monitoring in mountain areas, and increasing the efficiency of landslide monitoring. Furthermore, geological macro-monitoring is performed on each sub-region to determine the safety of macro-monitoring at the top and bottom of the mountain within the current sub-region, preventing geological changes within the sub-region from affecting the mountain structure and increasing the probability of landslides. Therefore, real-time geological macro-monitoring enables surface-based prediction of mountain formations, further improving the efficiency of landslide monitoring.

[0034] 2. In this invention, real-time displacement monitoring of sub-regions is performed to determine whether there is a risk of landslides in the real-time mountain displacement within each sub-region. In-depth location monitoring of sub-regions improves the accuracy of landslide monitoring in sub-regions and avoids the sudden increase in landslides caused by abnormal displacement within sub-regions, which would prevent timely prediction and prevention and control, thus ensuring that the impact of landslides cannot be minimized. Impact monitoring and analysis of sub-regions are also performed to determine whether the environmental impact of the current sub-region is normal, thus preventing environmental anomalies in sub-regions from causing changes in the mountain structure within the sub-region, increasing the risk of landslides, and affecting the safety efficiency of the sub-region.

[0035] 3. In this invention, the mountain control of sub-regions is monitored in real time, and landslide warnings are issued through monitoring the efficiency of mountain control. The real-time monitoring of mountain control can also provide early warnings of landslides, thereby improving the efficiency of landslide risk monitoring. Attached Figure Description

[0036] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0037] Figure 1 This is a schematic diagram of the overall principle of the present invention;

[0038] Figure 2 This is a schematic diagram of the body monitoring and analysis unit of the present invention. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0041] Please see Figure 1 As shown, an intelligent monitoring system for landslide risk based on artificial intelligence includes a monitoring platform. The monitoring platform is connected to a mountain area risk assessment unit, an impact monitoring and analysis unit, a body monitoring and analysis unit, and a real-time image monitoring unit. The monitoring platform has bidirectional communication connections with the mountain area risk assessment unit, the impact monitoring and analysis unit, the body monitoring and analysis unit, and the real-time image monitoring unit.

[0042] The monitoring platform generates a risk assessment signal for the mountain area and sends it to the risk assessment unit. After receiving the risk assessment signal, the risk assessment unit conducts a risk assessment of the mountain area based on the topography or topographic composition analysis, thereby improving the accuracy of landslide monitoring, ensuring the targeted nature of data collection and monitoring in the mountain area, and improving the efficiency of landslide monitoring.

[0043] The mountain region is divided into i sub-regions, where i is a natural number greater than 1, and each sub-region includes the top and bottom of the mountain. During the current monitoring period, when the furthest point of the mountain top in a sub-region extends beyond the bottom, the rate of decrease in the angle of inclination between the furthest point of the mountain top and the bottom is obtained and denoted as SDi. The reduction span of the number of surviving trees extending from the mountain top to the bottom in a sub-region during the current monitoring period is obtained and denoted as KDi. The duration of surface water flow connecting the mountain top and the bottom of the mountain peak in a sub-region during the current monitoring period is obtained and denoted as STi.

[0044] Obtain the risk assessment coefficient Di for the sub-region within the monitoring period of the mountain area;

[0045] Compare the risk assessment coefficient Di of the sub-region with the risk assessment coefficient threshold within the monitoring period of the mountain area:

[0046] If the risk assessment coefficient Di of a sub-region exceeds the risk assessment coefficient threshold during the monitoring period of the mountain area, the corresponding sub-region will be marked as a high-risk area; if the risk assessment coefficient Di of a sub-region does not exceed the risk assessment coefficient threshold during the monitoring period of the mountain area, the corresponding sub-region will be marked as a low-risk area.

[0047] The corresponding numbers of high-risk and low-risk areas are sent to the monitoring platform together. After receiving the data, the monitoring platform sets different data collection cycles for different area types.

[0048] The monitoring platform generates body monitoring and analysis signals and sends these signals to the body monitoring and analysis unit. Please refer to [link / reference]. Figure 2 As shown, the body monitoring and analysis unit is connected to the geological macro-monitoring unit and the real-time displacement monitoring unit.

[0049] After receiving the body monitoring and analysis signal, the body monitoring and analysis unit generates a geological macro-monitoring signal and a real-time displacement monitoring signal and sends them to the geological macro-monitoring unit and the real-time displacement monitoring unit, respectively.

[0050] After receiving the geological macro-monitoring signal, the geological macro-monitoring unit conducts geological macro-monitoring of each sub-region to determine whether the macro-monitoring of the top and bottom of the mountain in the current sub-region is safe, so as to avoid geological changes in the sub-region affecting the mountain structure and increasing the probability of landslides. Therefore, real-time geological macro-monitoring can predict the mountain from the surface, further improving the monitoring efficiency of landslides.

[0051] The system identifies and marks areas where cracks appear in the mountain within the current monitoring period. Based on these crack areas, the corresponding locations are divided into high and low regions. The system then obtains the increase in the deviation value of the mountain displacement velocity corresponding to the high and low regions within the monitoring period, as well as the rate of increase in the difference in mountain height between the high and low regions before and after the crack formation. These values ​​are then compared with threshold values ​​for the increase in deviation value and the rate of increase in the rate of increase, respectively.

[0052] If the increase in the deviation value of the displacement velocity of the corresponding high and low areas of the mountain exceeds the deviation value increase threshold during the monitoring period, or if the increase rate of the difference in the height of the mountain position between the high and low areas before and after the crack area is formed exceeds the value increase rate threshold, then the corresponding crack area will be marked as a danger area; if the increase in the deviation value of the displacement velocity of the corresponding high and low areas of the mountain does not exceed the deviation value increase threshold during the monitoring period, and the increase rate of the difference in the height of the mountain position between the high and low areas before and after the crack area is formed does not exceed the value increase rate threshold, then the corresponding crack area will be marked as a safe area.

[0053] The system acquires the frequency of successive occurrences of dangerous areas and the rate of increase in the number of safe areas within a sub-region during a monitoring period of the mountain area. If the frequency of successive occurrences of dangerous areas within a sub-region during the monitoring period exceeds a successive occurrence frequency threshold, or the rate of increase in the number of safe areas exceeds a rate of increase threshold, a geological risk signal is generated and sent to the main monitoring and analysis unit, along with the current sub-region number, which is also transferred to the monitoring platform. If the frequency of successive occurrences of dangerous areas within a sub-region during the monitoring period does not exceed the successive occurrence frequency threshold, and the rate of increase in the number of safe areas does not exceed the rate of increase threshold, a geological safety signal is generated and sent to the main monitoring and analysis unit, along with the current sub-region number, which is also transferred to the monitoring platform. Successive occurrences indicate that dangerous areas appear in adjacent positions and in sequential order.

[0054] After receiving the real-time displacement monitoring signal, the real-time displacement monitoring unit performs real-time displacement monitoring on the sub-regions, determines whether there is a risk of landslide in the real-time mountain displacement in each sub-region, and performs in-depth location monitoring on the sub-regions, which improves the accuracy of landslide monitoring in the sub-regions and avoids the sudden increase of landslides caused by abnormal displacement within the sub-regions, which would make it impossible to predict and prevent in time, and thus prevent the impact of landslides from being minimized.

[0055] The instantaneous displacement fluctuation values ​​of the slip zone soil at non-slope locations in adjacent sub-regions during the monitoring period of the mountain area are obtained, as well as the frequency of uniform displacement at any location of the slip zone soil in non-adjacent sub-regions. The instantaneous displacement fluctuation values ​​of the slip zone soil at non-slope locations in adjacent sub-regions and the frequency of uniform displacement at any location of the slip zone soil in non-adjacent sub-regions during the monitoring period of the mountain area are compared with the instantaneous displacement value threshold and the uniform displacement frequency threshold, respectively: non-slope location is defined as a location where the slope of the mountain between the top and bottom of the mountain does not exceed the set threshold; uniform displacement is defined as displacement in the same direction.

[0056] If the instantaneous displacement value of the slip zone soil at the corresponding non-slope location in the adjacent sub-region exceeds the instantaneous displacement value threshold during the monitoring period of the mountain area, or if the frequency of the slip zone soil at any location in the non-adjacent sub-region moving in the same direction exceeds the same direction displacement frequency threshold, then the sub-region displacement is determined to be abnormal during the monitoring period of the mountain area, a displacement anomaly signal is generated, and the displacement anomaly signal and the corresponding sub-region number are sent to the main body monitoring and analysis unit, which then forwards it to the monitoring platform.

[0057] If the instantaneous displacement value of the slip zone soil at the corresponding non-slope location in the adjacent sub-region does not exceed the instantaneous displacement value threshold during the monitoring period of the mountain area, and the frequency of the same trend displacement of any location of the slip zone soil in the non-adjacent sub-region does not exceed the same trend displacement frequency threshold, then the sub-region displacement is determined to be normal during the monitoring period of the mountain area, a normal displacement signal is generated, and the normal displacement signal and the corresponding sub-region number are sent to the main body monitoring and analysis unit, which then forwards it to the monitoring platform.

[0058] The monitoring platform generates an impact monitoring and analysis signal and sends it to the impact monitoring and analysis unit. After receiving the impact monitoring and analysis signal, the impact monitoring and analysis unit performs impact monitoring and analysis on the sub-region to determine whether the environmental impact of the current sub-region is normal. This is to prevent environmental anomalies in the sub-region from causing changes in the mountain structure within the sub-region, increasing the risk of landslides, and affecting the safety efficiency of the sub-region.

[0059] The study obtains the excess of runoff velocity on the mountain slopes of sub-regions during the rainfall increase period compared to the runoff velocity during the non-rainfall phase. It also obtains the rate of increase in sediment content in the runoff discharge water of sub-regions during the rainfall increase period. The excess of runoff velocity on the mountain slopes of sub-regions compared to the non-rainfall phase, and the rate of increase in sediment content in the runoff discharge water of sub-regions are compared with thresholds for velocity excess and sediment content increase rate, respectively.

[0060] If the difference between the runoff velocity on the mountain slope in the sub-region and the runoff velocity during the non-rainfall period exceeds the velocity difference threshold, or if the rate of increase in sediment content in the runoff water discharged from the mountain slope in the sub-region exceeds the sediment content increase rate threshold, then the sub-region is determined to be abnormal in the impact monitoring analysis, an impact monitoring abnormality signal is generated, and the impact monitoring abnormality signal and the corresponding sub-region number are sent to the monitoring platform together.

[0061] If the excess of the runoff velocity on the mountain slope during the non-rainfall period in the sub-region does not exceed the velocity excess threshold, and the rate of increase of sediment content in the runoff discharge water in the sub-region does not exceed the sediment content increase rate threshold, then the sub-region is determined to be normal in the impact monitoring analysis, an impact monitoring normal signal is generated, and the impact monitoring normal signal and the corresponding sub-region number are sent to the monitoring platform together.

[0062] When the monitoring platform receives abnormal signals affecting monitoring, abnormal displacement signals, or geological risk signals, it will implement mountain control measures for the corresponding sub-area. After the mountain control measures are implemented, the monitoring platform will generate real-time image monitoring signals and send them to the real-time image monitoring unit. Mountain control measures are the existing measures for controlling mountain displacement and movement.

[0063] After receiving the real-time image monitoring signal, the real-time image monitoring unit monitors the mountain control in the sub-area in real time. It provides early warning of landslides by monitoring the efficiency of mountain control. It can provide early warning of landslides while monitoring mountain control in real time, thus improving the efficiency of landslide risk monitoring.

[0064] Using the mountain control location as the image acquisition center point, the initial image of the current mountain control location is acquired at the moment of mountain control implementation. After mountain control implementation, images of the mountain control location are acquired at set intervals, and an image library is constructed by sorting the images according to the acquisition order. The rate of increase of the numerical interval difference of mountain displacement at the mountain control location in adjacent acquired images in the image library during the mountain control period, as well as the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared to the mountain displacement velocity before mountain control implementation, are obtained. The rate of increase of the numerical interval difference of mountain displacement at the mountain control location in adjacent acquired images in the image library during the mountain control period, and the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared to the mountain displacement velocity before mountain control implementation, are compared with the thresholds for the rate of increase of the interval difference and the thresholds for the decrease in the displacement velocity, respectively.

[0065] If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period exceeds the threshold for the rate of increase of the interval difference, or if the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared to the mountain displacement velocity before the implementation of the mountain control exceeds the threshold for the decrease in displacement velocity, then the current mountain control efficiency is determined to be low. A control rectification signal is generated and sent to the monitoring platform. After receiving the signal, the monitoring platform increases the type of control measures to be implemented in the mountain control area. If the control efficiency does not change, a landslide warning is issued.

[0066] If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period exceeds the threshold for the rate of increase of the interval difference, and the reduction of the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of the mountain control exceeds the threshold for the reduction of the displacement velocity, then the current mountain control efficiency is determined to be abnormal, a landslide warning signal is generated and sent to the monitoring platform;

[0067] If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in the image library of adjacent acquired images during the mountain control period does not exceed the threshold of the rate of increase of the interval difference, and the reduction of the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the reduction of the mountain displacement velocity before the implementation of the mountain control does not exceed the threshold of the reduction of the displacement velocity, then the current mountain control efficiency is determined to be normal, a continuous control signal is generated and sent to the monitoring platform;

[0068] In use, this invention involves a mountain area risk assessment unit that assesses the risk of a mountain area, dividing it into i sub-regions, obtaining risk assessment coefficients for each sub-region during the monitoring period, and classifying the sub-regions into high-risk and low-risk areas based on these coefficients. Different data collection cycles are set for different region types. The body monitoring and analysis unit is connected to a geological macro-monitoring unit and a real-time displacement monitoring unit. The geological macro-monitoring unit performs geological macro-monitoring of each sub-region, while the real-time displacement monitoring unit performs real-time displacement monitoring of the sub-regions. The impact monitoring and analysis unit performs impact monitoring and analysis on the sub-regions, and the real-time image monitoring unit performs real-time monitoring of the mountain control in the sub-regions.

[0069] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent monitoring system for landslide risk based on artificial intelligence, characterized in that, This includes a monitoring platform, which is connected to a mountain area risk assessment unit, an impact monitoring and analysis unit, a body monitoring and analysis unit, and a real-time image monitoring unit. The mountain area risk assessment unit conducts risk assessments on mountain areas, dividing them into i sub-regions, where i is a natural number greater than 1. Each sub-region includes both the top and bottom of the mountain. Risk assessment coefficients for each sub-region are obtained during the monitoring period. Based on these coefficients, the sub-regions are classified as high-risk or low-risk areas. Different data collection cycles are set for different region types. The operation process of the mountain area risk assessment unit is as follows: When the furthest point of the mountain top position in the sub-region exceeds the bottom position during the current monitoring period of the mountain area, the rate of decrease of the tilt angle corresponding to the furthest point of the mountain top position and the bottom position is obtained. Obtain the reduction span of the number of surviving trees on the extended mountainside beyond the base of the mountain in the sub-region corresponding to the current monitoring period of the mountain area; Obtain the duration of surface water flow connecting the top and bottom of the mountain in the corresponding sub-region within the current monitoring period of the mountain area; Risk assessment coefficients for sub-regions within the monitoring period of the mountainous area were obtained through analysis; The risk assessment coefficient of a sub-region within the monitoring period of the mountain area is compared with the risk assessment coefficient threshold: if the risk assessment coefficient of a sub-region within the monitoring period of the mountain area exceeds the risk assessment coefficient threshold, the corresponding sub-region is marked as a high-risk area. If the risk assessment coefficient Di of a sub-region does not exceed the risk assessment coefficient threshold during the monitoring period of the mountain area, the corresponding sub-region will be marked as a low-risk area. The body monitoring and analysis unit is connected to the geological macro-monitoring unit and the real-time displacement monitoring unit. The geological macro-monitoring unit performs geological macro-monitoring of each sub-region, generates geological risk signals or geological safety signals through analysis, and sends them to the body monitoring and analysis unit, along with the current sub-region number to the monitoring platform. The operation process of the geological macro-monitoring unit is as follows: The system identifies areas where cracks appear in the mountain within the current monitoring period and marks them as crack areas. Based on these crack areas, the corresponding locations are divided into high and low regions. The system then obtains the increase in the deviation value of the mountain displacement velocity corresponding to the high and low regions within the monitoring period, as well as the rate of increase in the numerical value of the height difference between the high and low regions before and after the cracks appear. These values ​​are then compared with thresholds for the increase in deviation value and the rate of increase in numerical value. If the increase in the deviation value of the displacement velocity of the mountain in the high and low areas exceeds the threshold value of the deviation value increase during the monitoring period, or if the increase rate of the value of the height difference between the high and low areas before and after the crack area is generated exceeds the threshold value of the value increase rate, then the corresponding crack area will be marked as a dangerous area. If the increase in the deviation value of the displacement velocity of the mountain corresponding to the high and low areas during the monitoring period does not exceed the threshold for the increase in deviation value, and the rate of increase in the value of the height difference between the high and low areas before and after the crack area is generated does not exceed the threshold for the rate of increase in value, then the corresponding crack area will be marked as a safe area. The real-time displacement monitoring unit performs real-time displacement monitoring of the sub-region, generates abnormal displacement signals or normal displacement signals through real-time displacement monitoring, and sends them to the body monitoring and analysis unit, which then forwards them to the monitoring platform. The impact monitoring and analysis unit performs impact monitoring and analysis on the sub-region, generates impact monitoring abnormal signals or impact monitoring normal signals through impact monitoring and analysis, and sends them to the monitoring platform. Upon receiving the impact monitoring abnormal signals, displacement abnormal signals, or geological risk signals, the monitoring platform will implement mountain control measures on the corresponding sub-region. After the mountain control measures are implemented, the real-time image monitoring unit will monitor the mountain control measures in the sub-region in real time.

2. The intelligent monitoring system for landslide risk based on artificial intelligence according to claim 1, characterized in that, The frequency of successive occurrences of dangerous areas and the rate of increase in the number of safe areas within a sub-region during the monitoring period of the mountain area are obtained. If the frequency of successive occurrences of dangerous areas within a sub-region during the monitoring period of the mountain area exceeds the successive occurrence frequency threshold, or the rate of increase in the number of safe areas exceeds the rate of increase threshold, a geological risk signal is generated and sent to the main monitoring and analysis unit, and the current sub-region number is also transferred to the monitoring platform. If the frequency of successive occurrences of dangerous areas within a sub-region during the monitoring period of the mountain area does not exceed the successive occurrence frequency threshold, and the rate of increase in the number of safe areas does not exceed the rate of increase threshold, then a geological safety signal is generated and sent to the main body monitoring and analysis unit, and the current sub-region number is also transferred to the monitoring platform.

3. The intelligent monitoring system for landslide risk based on artificial intelligence according to claim 1, characterized in that, The operation process of the real-time displacement monitoring unit is as follows: The instantaneous displacement fluctuation values ​​of slip zone soil at non-slope locations in adjacent sub-regions during the monitoring period of the mountain area are obtained, as well as the frequency of uniform displacement at any location of slip zone soil in non-adjacent sub-regions. These values ​​are then compared with the instantaneous displacement value threshold and the uniform displacement frequency threshold, respectively. If, during the monitoring period of the mountain area, the instantaneous displacement value of the slip zone soil at the corresponding non-slope location in the adjacent sub-region exceeds the instantaneous displacement value threshold, or if the frequency of the slip zone soil at any location in the non-adjacent sub-region moving in the same direction exceeds the same direction displacement frequency threshold, a displacement anomaly signal is generated and sent together with the corresponding sub-region number to the main body monitoring and analysis unit, which then forwards it to the monitoring platform. If, during the monitoring period of the mountain area, the instantaneous displacement fluctuation value of the slip zone soil at the corresponding non-slope location in the adjacent sub-region does not exceed the instantaneous displacement value threshold, and the frequency of the same-trend displacement of any location of the slip zone soil in the non-adjacent sub-region does not exceed the same-trend displacement frequency threshold, then a normal displacement signal is generated and sent together with the corresponding sub-region number to the main body monitoring and analysis unit, which then forwards it to the monitoring platform.

4. The intelligent monitoring system for landslide risk based on artificial intelligence according to claim 1, characterized in that, The operation process of the impact monitoring and analysis unit is as follows: The study obtains the excess of runoff velocity on the mountain slopes of sub-regions during the period of increased rainfall compared to the runoff velocity during the non-rainfall phase. It also obtains the rate of increase in sediment content in the runoff discharge water of sub-regions during the period of increased rainfall. The excess of runoff velocity on the mountain slopes of sub-regions compared to the runoff velocity during the non-rainfall phase, and the rate of increase in sediment content in the runoff discharge water of sub-regions are compared with the velocity excess threshold and the sediment content increase rate threshold, respectively.

5. The intelligent monitoring system for landslide risk based on artificial intelligence according to claim 4, characterized in that, If the difference between the runoff velocity on the mountain slope in the sub-region and the runoff velocity during the non-rainfall period exceeds the velocity difference threshold, or if the rate of increase in sediment content in the runoff water discharged from the mountain slope in the sub-region exceeds the sediment content increase rate threshold, then the sub-region is determined to be abnormal in the impact monitoring analysis, an impact monitoring abnormality signal is generated, and the impact monitoring abnormality signal and the corresponding sub-region number are sent to the monitoring platform together. If the excess of the runoff velocity on the mountain slope during the non-rainfall period in the sub-region does not exceed the velocity excess threshold, and the rate of increase of sediment content in the runoff discharge water in the sub-region does not exceed the sediment content increase rate threshold, then the sub-region impact monitoring analysis is determined to be normal, an impact monitoring normal signal is generated, and the impact monitoring normal signal and the corresponding sub-region number are sent to the monitoring platform together.

6. The intelligent monitoring system for landslide risk based on artificial intelligence according to claim 1, characterized in that, The operation process of the real-time image monitoring unit is as follows: Using the mountain control location as the image acquisition center point, the initial image of the current mountain control location is acquired at the moment of mountain control implementation. After the implementation of mountain control, images of the mountain control location are acquired at set intervals, and the images are sorted according to the acquisition order to build an image library. The increase rate of the numerical interval difference of the mountain displacement at the mountain control location in the image library of adjacent acquired images during the mountain control period, as well as the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of mountain control, are obtained. The increase rate of the numerical interval difference of the mountain displacement at the mountain control location in the image library of adjacent acquired images during the mountain control period, as well as the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of mountain control, are compared with the threshold of the increase rate of the interval difference and the threshold of the decrease in the displacement velocity, respectively.

7. The intelligent monitoring system for landslide risk based on artificial intelligence according to claim 6, characterized in that, If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period exceeds the threshold for the rate of increase of the interval difference, or if the decrease in the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared to the mountain displacement velocity before the implementation of the mountain control exceeds the threshold for the decrease in displacement velocity, then a control and rectification signal is generated and sent to the monitoring platform. After receiving the signal, the monitoring platform will increase the type of control measures implemented in the mountain control area. If there is no change in control efficiency, a landslide warning will be issued. If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period exceeds the threshold for the rate of increase of the interval difference, and the reduction of the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of the mountain control exceeds the threshold for the reduction of the displacement velocity, then a landslide warning signal is generated and sent to the monitoring platform. If the rate of increase of the numerical interval difference of the mountain displacement at the mountain control location in adjacent images in the image library during the mountain control period does not exceed the threshold for the rate of increase of the interval difference, and the reduction of the mountain displacement velocity at the mountain control location in the image library during the mountain control period compared with the mountain displacement velocity before the implementation of the mountain control does not exceed the threshold for the reduction of displacement velocity, then a continuous control signal is generated and sent to the monitoring platform.

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