Perimeter monitoring and intelligent early warning method and system based on environmental interference factors

Abstract

The present application relates to the technical field of intelligent equipment, and discloses a perimeter monitoring and intelligent early warning method and system based on environmental interference factors, comprising: determining a first required operating parameter according to real-time weather characteristics and seasonal characteristics of a monitoring and early warning area; determining a second required operating parameter according to vegetation and topography of the monitoring and early warning area; determining a current regular natural phenomenon according to the real-time weather characteristics, the seasonal characteristics, the vegetation and the topography; and controlling the perimeter monitoring and early warning equipment to perform monitoring analysis and early warning operation on the monitoring and early warning area according to the first required operating parameter, the second required operating parameter and the current regular natural phenomenon. It can be seen that the present application can improve the diversity, pertinence and flexibility of the parameters considered in perimeter monitoring and early warning, thereby improving the accuracy and reliability, efficiency, convenience and timeliness of perimeter monitoring and early warning, and thus improving the accuracy and timeliness, safety of perimeter anomaly response.

Description

Technical Field

[0001] This invention relates to the field of intelligent device technology, and in particular to a perimeter monitoring and intelligent early warning method and system based on environmental interference factors. Background Technology

[0002] With the increasing demand for public safety and the security challenges brought about by technological advancements, perimeter monitoring and early warning have become the focus of industry attention. As the first line of defense for preventing illegal intrusion and protecting the security of key areas, the importance of perimeter monitoring and early warning is self-evident.

[0003] Currently, perimeter monitoring and early warning methods primarily rely on operators at manual monitoring centers who observe the monitored area in real time on screens and decide whether to issue an early warning signal based on personal experience and subjective judgment. This subjective judgment is susceptible to various factors, leading to discrepancies even when assessing the same perimeter anomaly under identical conditions. Therefore, existing perimeter monitoring and early warning methods suffer from low accuracy and efficiency. Clearly, providing a perimeter monitoring and early warning method that improves both accuracy and efficiency is crucial. Summary of the Invention

[0004] This invention provides a perimeter monitoring and intelligent early warning method and system based on environmental interference factors, which can improve the monitoring and early warning accuracy and efficiency of perimeter monitoring and early warning equipment, thereby improving the timeliness and security of perimeter anomaly handling.

[0005] To address the aforementioned technical problems, the first aspect of this invention discloses a perimeter monitoring and intelligent early warning method based on environmental interference factors, the method comprising:

[0006] The system acquires real-time weather and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determines the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather and seasonal characteristics.

[0007] The vegetation and topography of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning device are obtained, and the second required operating parameters of the perimeter monitoring and early warning device are determined based on the vegetation and topography.

[0008] Based on the real-time weather characteristics, seasonal characteristics, vegetation conditions, and topographic features, the current routine natural phenomena in the monitoring and early warning area are determined.

[0009] According to the first demand operation parameter, the second demand operation parameter and the current regular natural phenomenon, the perimeter monitoring and early warning device is controlled to perform corresponding monitoring analysis and early warning operation on the monitoring and early warning area.

[0010] As an optional implementation, in the first aspect of the present application, according to the first demand operation parameter, the second demand operation parameter and the current regular natural phenomenon, the perimeter monitoring and early warning device is controlled to perform corresponding monitoring analysis and early warning operation on the monitoring and early warning area, including:

[0011] According to the vegetation condition, the current actual vegetation phenomenon of the monitoring and early warning area is determined, which includes one or more of current actual vegetation dense condition, current actual vegetation shaking and shaking sound condition, current actual vegetation growth and shape condition;

[0012] According to the current regular natural phenomenon and the current actual vegetation phenomenon, it is judged whether the perimeter monitoring and early warning device meets the preset abnormal early warning execution condition;

[0013] When it is judged that the perimeter monitoring and early warning device meets the abnormal early warning execution condition, according to the current regular natural phenomenon and the current actual vegetation phenomenon, the target early warning object and its related feature information are determined; according to the target early warning object and its related feature information, the first demand operation parameter and the second demand operation parameter, the specific early warning operation mode of the perimeter monitoring and early warning device is determined; according to the specific early warning operation mode, the perimeter monitoring and early warning device is controlled to perform corresponding early warning operation;

[0014] When it is judged that the perimeter monitoring and early warning device does not meet the abnormal early warning execution condition, according to the first demand operation parameter and the second demand operation parameter, the general early warning operation mode of the perimeter monitoring and early warning device is determined; according to the general early warning operation mode, the perimeter monitoring and early warning device is controlled to perform corresponding early warning operation.

[0015] As an optional implementation, in the first aspect of the present application, according to the current regular natural phenomenon and the current actual vegetation phenomenon, it is judged whether the perimeter monitoring and early warning device meets the preset abnormal early warning execution condition, including:

[0016] According to the current actual vegetation dense condition and the current actual vegetation growth and shape condition, the actual vegetation feature of the monitoring and early warning area is determined;

[0017] According to the actual vegetation feature and the current regular natural phenomenon, it is judged whether the monitoring and early warning area meets the preset irregular vegetation feature condition;

[0018] determining whether the monitoring and early warning region meets a preset rationality vegetation feature change condition;

[0019] when it is determined that the monitoring and early warning region meets the rationality vegetation feature change condition, determining that the perimeter monitoring and early warning device does not meet a preset abnormality early warning execution condition;

[0020] when it is determined that the monitoring and early warning region does not meet the rationality vegetation feature change condition, determining that the perimeter monitoring and early warning device meets the preset abnormality early warning execution condition.

[0021] As an optional implementation form, in the first aspect of the present application, the determination of whether the monitoring and early warning region meets the preset rationality vegetation feature change condition comprises:

[0022] determining a generation duration of the vegetation variation growth phenomenon in the monitoring and early warning region, and determining special vegetation planting record information of the monitoring and early warning region; determining whether the monitoring and early warning region meets a preset predictable vegetation feature abnormality condition according to the generation duration and the special vegetation planting record information; when it is determined that the monitoring and early warning region meets the predictable vegetation feature abnormality condition, determining that the monitoring and early warning region meets the preset rationality vegetation feature change condition; when it is determined that the monitoring and early warning region does not meet the predictable vegetation feature abnormality condition, determining that the monitoring and early warning region does not meet the preset rationality vegetation feature change condition; and / or,

[0023] determining first change information on the shaking and jarring levels caused by the natural wind blowing through the monitoring and early warning region according to the current regular natural phenomenon, and determining second change information on the shaking and jarring levels currently occurring in the monitoring and early warning region according to the current actual vegetation shaking and jarring situation; determining whether the monitoring and early warning region meets a preset vegetation unnatural shaking condition according to the first change information and the second change information; when it is determined that the monitoring and early warning region meets the vegetation unnatural shaking condition, determining that the monitoring and early warning region does not meet the preset rationality vegetation feature change condition; when it is determined that the monitoring and early warning region does not meet the vegetation unnatural shaking condition, determining that the monitoring and early warning region meets the preset rationality vegetation feature change condition; wherein the first change information and the second change information both include one or more of shaking amplitude information, shaking trajectory information, shaking frequency information, jarring volume information, jarring frequency information, jarring amplitude information, jarring duration information, and jarring tone information.

[0024] As an optional implementation, in the first aspect of the present invention, determining the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather characteristics and the seasonal characteristics includes:

[0025] Based on the real-time weather characteristics, determine the ambient brightness, ambient noise, ambient wind direction and force, and ambient medium density of the monitoring and early warning area;

[0026] Based on the seasonal characteristics, determine the environmental temperature, plant growth and animal activity, and astronomical and geographical conditions of the monitoring and early warning area;

[0027] Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the medium propagation stability requirements are determined according to the environmental wind direction and force, the astronomical and geographical conditions, and the environmental temperature. The medium penetration requirements are determined according to the environmental brightness, the environmental medium density, and the environmental noise. The medium ecological effect requirements are determined according to the plant growth and animal activity.

[0028] Based on the medium propagation stability requirements, the medium penetration requirements, and the medium ecological effect requirements, the first sensing medium type and its corresponding sensing parameter information are determined to obtain the first required operating parameters of the perimeter monitoring and early warning equipment.

[0029] And, determining the second required operating parameters of the perimeter monitoring and early warning equipment based on the vegetation and topographical conditions includes:

[0030] Based on the vegetation and topography, determine the distribution of obstructions, the nature of the obstructions, and the geographical conditions of the monitoring and early warning area.

[0031] Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, are determined according to the distribution of the obstructions, the nature of the obstructions, and the geographical conditions.

[0032] Based on the requirements for the dispersion and penetration of the medium and the requirements related to the propagation trajectory of the medium, the second sensing medium type and its corresponding sensing parameter information are determined to obtain the second required operating parameters of the perimeter monitoring and early warning equipment.

[0033] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0034] When an abnormal malfunction is detected in the perimeter monitoring and early warning device, the device operation data of the perimeter monitoring and early warning device in the historical time period before the abnormal malfunction occurred is obtained.

[0035] Based on the equipment operation data, determine whether the perimeter monitoring and early warning equipment meets the preset predictable fault conditions;

[0036] When it is determined that the perimeter monitoring and early warning device meets the predictable fault conditions, a first prompting instruction is generated to prompt maintenance personnel to handle the fault of the perimeter monitoring and early warning device.

[0037] When it is determined that the perimeter monitoring and early warning device does not meet the predictable fault conditions, the device monitoring data collected by the perimeter monitoring and early warning device and its surrounding devices in the historical time period before the occurrence of the abnormal fault phenomenon is obtained.

[0038] Based on the device monitoring data, determine whether the perimeter monitoring and early warning device meets the preset biological fault conditions;

[0039] When it is determined that the perimeter monitoring and early warning device meets the conditions for malfunction caused by the organism, a second prompt instruction is generated to prompt maintenance personnel to handle the malfunction of the perimeter monitoring and early warning device, and a third prompt instruction is generated to prompt security personnel to respond to the alarm for the organism that caused the malfunction.

[0040] As an optional implementation, in the first aspect of the present invention, determining whether the perimeter monitoring and early warning device meets preset predictable fault conditions based on the device operating data includes:

[0041] Based on the equipment operation data, determine the usage time of the perimeter monitoring and early warning equipment, and based on the usage time, determine whether the perimeter monitoring and early warning equipment meets the preset lifespan-induced failure conditions.

[0042] When it is determined that the perimeter monitoring and early warning device meets the lifespan-induced failure condition, it is determined that the perimeter monitoring and early warning device meets the preset predictable failure condition.

[0043] When it is determined that the perimeter monitoring and early warning device does not meet the lifespan-induced failure conditions, the operating effect of the perimeter monitoring and early warning device is determined based on the device operating data, and the operating effect is used to determine whether the perimeter monitoring and early warning device meets the preset intermittent failure conditions.

[0044] When it is determined that the perimeter monitoring and early warning device meets the intermittent failure condition, it is determined that the perimeter monitoring and early warning device meets the preset predictable failure condition.

[0045] When it is determined that the perimeter monitoring and early warning device does not meet the intermittent fault condition, it is determined that the perimeter monitoring and early warning device does not meet the preset predictable fault condition.

[0046] A second aspect of this invention discloses a perimeter monitoring and intelligent early warning system based on environmental interference factors, the system comprising:

[0047] The first parameter determination module is used to obtain the real-time weather characteristics and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determine the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather characteristics and seasonal characteristics.

[0048] The second parameter determination module is used to obtain the vegetation and topography of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning device, and determine the second required operating parameters of the perimeter monitoring and early warning device based on the vegetation and topography.

[0049] The routine phenomenon determination module is used to determine the current routine natural phenomena in the monitoring and early warning area based on the real-time weather characteristics, seasonal characteristics, vegetation conditions, and topography.

[0050] The monitoring and early warning module is used to control the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first required operating parameters, the second required operating parameters, and the current normal natural phenomena.

[0051] As an optional implementation, in a second aspect of the present invention, the monitoring and early warning module controls the perimeter monitoring and early warning device to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first required operating parameters, the second required operating parameters, and the current normal natural phenomenon. Specifically, this includes:

[0052] Based on the vegetation conditions, the current actual vegetation phenomena in the monitoring and early warning area are determined. The current actual vegetation phenomena include one or more of the following: current actual vegetation density, current actual vegetation swaying and rattling, and current actual vegetation growth and shape.

[0053] Based on the current normal natural phenomena and the current actual vegetation phenomena, determine whether the perimeter monitoring and early warning equipment meets the preset abnormal early warning execution conditions;

[0054] When it is determined that the perimeter monitoring and early warning device meets the abnormal early warning execution conditions, the target early warning object and its related characteristic information are determined based on the current normal natural phenomena and the current actual vegetation phenomena; based on the target early warning object and its related characteristic information, the first required operating parameters, and the second required operating parameters, the targeted early warning operation mode of the perimeter monitoring and early warning device is determined; based on the targeted early warning operation mode, the perimeter monitoring and early warning device is controlled to perform corresponding early warning operations;

[0055] When it is determined that the perimeter monitoring and early warning device does not meet the abnormal early warning execution conditions, the normal early warning operation mode of the perimeter monitoring and early warning device is determined according to the first required operation parameters and the second required operation parameters; according to the normal early warning operation mode, the perimeter monitoring and early warning device is controlled to perform the corresponding early warning operation.

[0056] As an optional implementation, in the second aspect of the present invention, the monitoring and early warning module determines whether the perimeter monitoring and early warning device meets the preset abnormal early warning execution conditions based on the current normal natural phenomena and the current actual vegetation phenomena. Specifically, this includes:

[0057] Based on the current actual vegetation density, the current actual vegetation growth and shape, the actual vegetation characteristics of the monitoring and early warning area are determined;

[0058] Based on the actual vegetation characteristics and the current conventional natural phenomena, determine whether the monitoring and early warning area meets the preset unconventional vegetation characteristic conditions;

[0059] When it is determined that the monitoring and early warning area meets the unconventional vegetation characteristic conditions, it is determined whether the monitoring and early warning area meets the preset reasonable vegetation characteristic change conditions.

[0060] When it is determined that the monitoring and early warning area meets the reasonable vegetation characteristic change conditions, it is determined that the perimeter monitoring and early warning device does not meet the preset abnormal early warning execution conditions.

[0061] When it is determined that the monitoring and early warning area does not meet the reasonable vegetation characteristic change conditions, the perimeter monitoring and early warning device is determined to meet the preset abnormal early warning execution conditions.

[0062] As an optional implementation, in the second aspect of the present invention, the method by which the monitoring and early warning module determines whether the monitoring and early warning area meets the preset reasonable vegetation characteristic change conditions specifically includes:

[0063] The duration of vegetation mutation in the monitored and early warning area is determined, and special vegetation planting records for the monitored and early warning area are identified. Based on the duration of the mutation and the special vegetation planting records, it is determined whether the monitored and early warning area meets preset predictable vegetation characteristic anomaly conditions. When it is determined that the monitored and early warning area meets the predictable vegetation characteristic anomaly conditions, it is determined that the monitored and early warning area meets preset reasonable vegetation characteristic change conditions. When it is determined that the monitored and early warning area does not meet the predictable vegetation characteristic anomaly conditions, it is determined that the monitored and early warning area does not meet preset reasonable vegetation characteristic change conditions; and / or,

[0064] Based on the current normal natural phenomena, the first change information regarding the swaying and swaying sound caused by natural wind blowing through the monitoring and warning area is determined. Based on the current actual vegetation swaying and swaying sound, the second change information regarding the swaying and swaying sound currently occurring in the monitoring and warning area is determined. Based on the first and second change information, it is determined whether the monitoring and warning area meets the preset conditions for unnatural vegetation swaying. When it is determined that the monitoring and warning area meets the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area does not meet the preset conditions for reasonable vegetation characteristic changes. When it is determined that the monitoring and warning area does not meet the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area meets the preset conditions for reasonable vegetation characteristic changes. Wherein, the first and second change information each include one or more of the following: swaying amplitude information, swaying trajectory information, swaying frequency information, swaying sound volume information, swaying sound frequency information, swaying sound amplitude information, swaying sound duration information, and swaying sound timbre information.

[0065] As an optional implementation, in a second aspect of the present invention, the method by which the first parameter determining module determines the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather characteristics and the seasonal characteristics specifically includes:

[0066] Based on the real-time weather characteristics, determine the ambient brightness, ambient noise, ambient wind direction and force, and ambient medium density of the monitoring and early warning area;

[0067] Based on the seasonal characteristics, determine the environmental temperature, plant growth and animal activity, and astronomical and geographical conditions of the monitoring and early warning area;

[0068] Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the medium propagation stability requirements are determined according to the environmental wind direction and force, the astronomical and geographical conditions, and the environmental temperature. The medium penetration requirements are determined according to the environmental brightness, the environmental medium density, and the environmental noise. The medium ecological effect requirements are determined according to the plant growth and animal activity.

[0069] Based on the medium propagation stability requirements, the medium penetration requirements, and the medium ecological effect requirements, the first sensing medium type and its corresponding sensing parameter information are determined to obtain the first required operating parameters of the perimeter monitoring and early warning equipment.

[0070] Furthermore, the method by which the second parameter determining module determines the second required operating parameters of the perimeter monitoring and early warning equipment based on the vegetation and topographical conditions specifically includes:

[0071] Based on the vegetation and topography, determine the distribution of obstructions, the nature of the obstructions, and the geographical conditions of the monitoring and early warning area.

[0072] Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, are determined according to the distribution of the obstructions, the nature of the obstructions, and the geographical conditions.

[0073] Based on the requirements for the dispersion and penetration of the medium and the requirements related to the propagation trajectory of the medium, the second sensing medium type and its corresponding sensing parameter information are determined to obtain the second required operating parameters of the perimeter monitoring and early warning equipment.

[0074] As an optional implementation, in a second aspect of the invention, the system further includes:

[0075] The fault handling module is used to, when an abnormal fault is detected in the perimeter monitoring and early warning device, acquire the device's operating data for the historical period preceding the occurrence of the abnormal fault; based on the operating data, determine whether the perimeter monitoring and early warning device meets preset predictable fault conditions; when the perimeter monitoring and early warning device meets the predictable fault conditions, generate a first prompt instruction to prompt maintenance personnel to handle the fault; when the perimeter monitoring and early warning device does not meet the predictable fault conditions, acquire the device monitoring data collected by the perimeter monitoring and early warning device and its surrounding devices during the historical period preceding the occurrence of the abnormal fault; based on the device monitoring data, determine whether the perimeter monitoring and early warning device meets preset biologically caused fault conditions; when the perimeter monitoring and early warning device meets the biologically caused fault conditions, generate a second prompt instruction to prompt maintenance personnel to handle the fault, and generate a third prompt instruction to prompt security personnel to take alarm action against the biological object causing the fault.

[0076] As an optional implementation, in the second aspect of the present invention, the method by which the fault handling module determines whether the perimeter monitoring and early warning device meets the preset predictable fault conditions based on the device operating data specifically includes:

[0077] Based on the equipment operation data, determine the usage time of the perimeter monitoring and early warning equipment, and based on the usage time, determine whether the perimeter monitoring and early warning equipment meets the preset lifespan-induced failure conditions.

[0078] When it is determined that the perimeter monitoring and early warning device meets the lifespan-induced failure condition, it is determined that the perimeter monitoring and early warning device meets the preset predictable failure condition.

[0079] When it is determined that the perimeter monitoring and early warning device does not meet the lifespan-induced failure conditions, the operating effect of the perimeter monitoring and early warning device is determined based on the device operating data, and the operating effect is used to determine whether the perimeter monitoring and early warning device meets the preset intermittent failure conditions.

[0080] When it is determined that the perimeter monitoring and early warning device meets the intermittent failure condition, it is determined that the perimeter monitoring and early warning device meets the preset predictable failure condition.

[0081] When it is determined that the perimeter monitoring and early warning device does not meet the intermittent fault condition, it is determined that the perimeter monitoring and early warning device does not meet the preset predictable fault condition.

[0082] A third aspect of this invention discloses another perimeter monitoring and intelligent early warning system based on environmental interference factors, the system comprising:

[0083] Memory containing executable program code;

[0084] A processor coupled to the memory;

[0085] The processor calls the executable program code stored in the memory to execute the perimeter monitoring and intelligent early warning method based on environmental interference factors disclosed in the first aspect of the present invention.

[0086] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the perimeter monitoring and intelligent early warning method based on environmental interference factors disclosed in the first aspect of the present invention.

[0087] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0088] In this embodiment of the invention, real-time weather and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning device are acquired, and a first required operating parameter for the perimeter monitoring and early warning device is determined based on the weather and seasonal characteristics; vegetation and topography of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning device are acquired, and a second required operating parameter for the perimeter monitoring and early warning device is determined based on the vegetation and topography; current common natural phenomena in the monitoring and early warning area are determined based on the real-time weather, seasonal, vegetation, and topography; and the perimeter monitoring and early warning device is controlled to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first required operating parameter, the second required operating parameter, and the current common natural phenomena. As can be seen, this invention can determine the first required operating parameters based on weather and seasonal characteristics, the second required operating parameters based on vegetation and topography, and the current routine natural phenomena in the monitoring and early warning area. Furthermore, based on the first and second required operating parameters and the current routine natural phenomena, it controls the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area. This is beneficial for improving the comprehensiveness and rationality of perimeter monitoring and intelligent early warning methods, for increasing the diversity, specificity, and flexibility of the parameters considered for perimeter monitoring and early warning, and thus for improving the accuracy and reliability of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area. It is also beneficial for improving the efficiency, convenience, and timeliness of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area, thereby improving the accuracy and timeliness of responding to perimeter anomalies and enhancing perimeter security. Attached Figure Description

[0089] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0090] Figure 1 This is a flowchart illustrating a perimeter monitoring and intelligent early warning method based on environmental interference factors disclosed in an embodiment of the present invention.

[0091] Figure 2 This is a flowchart illustrating another perimeter monitoring and intelligent early warning method based on environmental interference factors disclosed in an embodiment of the present invention.

[0092] Figure 3 This is a schematic diagram of the structure of a perimeter monitoring and intelligent early warning system based on environmental interference factors disclosed in an embodiment of the present invention;

[0093] Figure 4 This is a schematic diagram of another perimeter monitoring and intelligent early warning system based on environmental interference factors disclosed in an embodiment of the present invention;

[0094] Figure 5 This is a schematic diagram of another perimeter monitoring and intelligent early warning system based on environmental interference factors disclosed in an embodiment of the present invention. Detailed Implementation

[0095] 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.

[0096] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0097] 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.

[0098] This invention discloses a perimeter monitoring and intelligent early warning method and system based on environmental interference factors. It can determine first required operating parameters based on weather and seasonal characteristics, second required operating parameters based on vegetation and topography, and current common natural phenomena in the monitoring and early warning area. Furthermore, based on the first and second required operating parameters and the current common natural phenomena, it controls the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area. This improves the comprehensiveness and rationality of the perimeter monitoring and intelligent early warning method, enhances the diversity, relevance, and flexibility of the parameters considered for perimeter monitoring and early warning, and consequently improves the accuracy and reliability of monitoring and early warning for the equipment and area. It also improves the efficiency, convenience, and timeliness of monitoring and early warning for the equipment and area, thereby enhancing the accuracy and timeliness of responding to perimeter anomalies and improving perimeter security. Detailed descriptions follow.

[0099] Example 1

[0100] Please see Figure 1 , Figure 1 This is a flowchart illustrating a perimeter monitoring and intelligent early warning method based on environmental interference factors disclosed in an embodiment of the present invention. Figure 1 The described method can be applied to perimeter monitoring and intelligent early warning systems based on environmental interference factors. This system may include a server, which may be a local server or a cloud server; this embodiment of the invention does not limit the scope. Figure 1 As shown, this perimeter monitoring and intelligent early warning method based on environmental interference factors includes the following operations:

[0101] 101. Obtain real-time weather and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determine the first required operating parameters of the perimeter monitoring and early warning equipment based on the weather and seasonal characteristics.

[0102] Optionally, real-time weather characteristics may include, but are not limited to, temperature (e.g., air temperature, perceived temperature, landmark temperature), precipitation (e.g., precipitation type, precipitation amount, precipitation intensity, precipitation probability), wind (e.g., wind direction, wind speed, gusts, wind force level), humidity (e.g., relative humidity, absolute humidity, dew point temperature), air pressure (e.g., sea level air pressure, air pressure change, air pressure gradient), cloud and visibility (e.g., cloud cover, cloud height, visibility), weather system (e.g., fronts, cyclones and anticyclones, typhoons / hurricanes), and extreme weather (e.g., heat waves, cold waves, droughts, severe convective weather), etc., and the embodiments of the present invention are not limited to one or more of these.

[0103] Optionally, seasonal characteristics may include, but are not limited to, one or more of the following: temperature changes (such as seasonal average temperature, diurnal temperature range, extreme temperature events, accumulated temperature information), precipitation patterns (such as seasonal precipitation, precipitation type, plum rain / monsoon, dry season), sunshine and solar radiation (such as sunshine duration, solar altitude angle, ultraviolet intensity), wind and air pressure systems (such as monsoon, typhoon / hurricane season, high pressure / low pressure control), etc. The embodiments of the present invention are not limited to these.

[0104] 102. Obtain the vegetation and topography of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determine the second required operating parameters of the perimeter monitoring and early warning equipment based on the vegetation and topography.

[0105] Optionally, the topographic and geomorphological information may include, but is not limited to, one or more of the following: topographic and geomorphological type, altitude and elevation difference information, slope and aspect information, typical characteristics information, morphological characteristics information, ecological characteristics information, climate characteristics information, and human activity characteristics information. This embodiment of the invention does not limit the information.

[0106] Optionally, the first and second required operating parameters can be used to represent different sensing medium types, intensities, divergences, propagations, penetrations, and other parameters corresponding to different operating modes. This embodiment of the invention does not limit these parameters.

[0107] 103. Based on real-time weather characteristics, seasonal characteristics, vegetation conditions, and topography, determine the current routine natural phenomena in the monitoring and early warning area.

[0108] Optionally, the current routine natural phenomena in the monitoring and early warning area can be understood as the routine and normal natural phenomena that will occur in the monitoring and early warning area under the current weather and season. This embodiment of the invention does not limit this.

[0109] 104. Based on the first requirement operating parameters, the second requirement operating parameters, and current normal natural phenomena, control the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitored and early warning area.

[0110] As can be seen, the perimeter monitoring and intelligent early warning method based on environmental interference factors described in the embodiments of the present invention can determine the first required operating parameters for weather and seasonal characteristics, the second required operating parameters for vegetation and topography, and the current normal natural phenomena in the monitoring and early warning area. Furthermore, based on the first required operating parameters, the second required operating parameters, and the current normal natural phenomena, the perimeter monitoring and early warning equipment is controlled to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area. This is beneficial to improving the comprehensiveness and rationality of the perimeter monitoring and intelligent early warning method, and to improving the diversity, specificity, and flexibility of the parameters considered for perimeter monitoring and early warning. Consequently, it is beneficial to improving the accuracy and reliability of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area, and to improving the efficiency, convenience, and timeliness of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area. Therefore, it is beneficial to improve the accuracy and timeliness of responding to perimeter anomalies and to improve perimeter security.

[0111] In an optional embodiment, the above-mentioned control of the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first required operating parameters, the second required operating parameters, and current normal natural phenomena may include:

[0112] Based on the vegetation conditions, determine the current actual vegetation phenomena in the monitoring and early warning area. The current actual vegetation phenomena include one or more of the following: current actual vegetation density, current actual vegetation swaying and sounding, and current actual vegetation growth and shape.

[0113] Based on current normal natural phenomena and current actual vegetation conditions, determine whether the perimeter monitoring and early warning equipment meets the preset abnormal early warning execution conditions;

[0114] When it is determined that the perimeter monitoring and early warning equipment meets the conditions for abnormal early warning execution, the target early warning object and its related characteristic information are determined based on the current normal natural phenomena and the current actual vegetation phenomena; based on the target early warning object and its related characteristic information, the first required operating parameters, and the second required operating parameters, the targeted early warning operation mode of the perimeter monitoring and early warning equipment is determined; based on the targeted early warning operation mode, the perimeter monitoring and early warning equipment is controlled to execute the corresponding early warning operation.

[0115] When it is determined that the perimeter monitoring and early warning equipment does not meet the abnormal early warning execution conditions, the normal early warning operation mode of the perimeter monitoring and early warning equipment is determined according to the first requirement operation parameter and the second requirement operation parameter; according to the normal early warning operation mode, the perimeter monitoring and early warning equipment is controlled to perform the corresponding early warning operation.

[0116] Optionally, the target warning object can be determined based on the current normal natural phenomena and the current actual vegetation phenomena. For example, the shape of normally growing vegetation / the shape of vegetation caused by wind is different from the shape of vegetation caused by organisms hiding / passing by. Also, the swaying of vegetation caused by wind is different from the swaying of vegetation caused by organisms passing by. Therefore, the target warning object can be determined based on the specific location and specific difference between the current actual vegetation phenomena and the current normal natural phenomena. This embodiment of the invention does not limit this.

[0117] Optionally, the target warning object and its related characteristic information can be understood as the target warning object's movement behavior characteristics, age and physical characteristics, surrounding environmental characteristics, etc. Different objects and related characteristics require different warning execution parameters. Furthermore, for example, when the targeted warning operation mode is used to represent laser repulsion, the laser intensity and laser type used for young people / old people are different. For example, the purpose of the laser is also different based on the different behavioral dangers and the different urgency of the repulsion. For example, the laser parameters corresponding to simply repelling the target warning object are different from those corresponding to making the target warning object stand still and wait to be captured. For example, if it is necessary to minimize the impact on the surrounding organisms of the target warning object or not consider it at all, then the accuracy and diffusion requirements of the repulsion medium will also be different. The same applies to other cases. This embodiment of the invention does not limit the scope of the invention.

[0118] Optionally, the warning operation in the targeted warning operation mode can be understood as targeting and driving away a specific warning object, such as using laser strikes to drive it away; the warning operation in the routine warning operation mode can be understood as routine patrol monitoring to see if there is a target warning object, such as playing routine warning voice messages, etc. This embodiment of the invention does not limit the scope of the warning operation.

[0119] As can be seen, this optional embodiment can determine the result of meeting the abnormal early warning execution conditions based on the current normal natural phenomena and the current actual vegetation phenomena. For those that meet the abnormal early warning execution conditions and those that do not, it matches the corresponding perimeter monitoring and early warning equipment operation mode and early warning operation. This is beneficial to improving the comprehensiveness and rationality of the method for determining the early warning operation mode of the perimeter monitoring and early warning equipment, and to improving the diversity, flexibility and pertinence of the method for determining the early warning operation mode. In turn, it is beneficial to improve the accuracy and reliability of the determined early warning operation mode, thereby improving the early warning accuracy and reliability of the perimeter monitoring and early warning equipment.

[0120] In another optional embodiment, the above-mentioned determination of whether the perimeter monitoring and early warning device meets the preset abnormal early warning execution conditions based on the current normal natural phenomena and the current actual vegetation phenomena may include:

[0121] Based on the current actual vegetation density, current actual vegetation growth and shape, determine the actual vegetation characteristics of the monitoring and early warning area;

[0122] Based on the actual vegetation characteristics and current common natural phenomena, determine whether the monitoring and early warning area meets the preset unconventional vegetation characteristic conditions;

[0123] When it is determined that the monitoring and early warning area meets the unconventional vegetation characteristic conditions, it is then determined whether the monitoring and early warning area meets the preset reasonable vegetation characteristic change conditions.

[0124] When it is determined that the monitoring and early warning area meets the conditions for reasonable vegetation characteristic changes, it is determined that the perimeter monitoring and early warning equipment does not meet the preset abnormal early warning execution conditions.

[0125] When it is determined that the monitoring and early warning area does not meet the conditions for reasonable vegetation characteristic changes, the perimeter monitoring and early warning equipment is determined to meet the preset abnormal early warning execution conditions.

[0126] Further optionally, the above-mentioned determination of whether the monitoring and early warning area meets the preset unconventional vegetation characteristic conditions based on actual vegetation characteristics and current conventional natural phenomena may include:

[0127] Determine the conventional vegetation characteristics corresponding to the current conventional natural phenomenon, and judge whether the actual vegetation characteristics match the conventional vegetation characteristics; when the judgment result is no, determine that the monitoring and early warning area meets the preset unconventional vegetation characteristic conditions; when the judgment result is yes, determine that the monitoring and early warning area does not meet the preset unconventional vegetation characteristic conditions.

[0128] Alternatively, the method may further include the following steps:

[0129] When it is determined that the monitoring and early warning area does not meet the characteristics of unconventional vegetation, it is determined that the perimeter monitoring and early warning equipment does not meet the preset abnormal early warning execution conditions.

[0130] Optionally, for example: the appearance of vegetation without external influence is different from the appearance of vegetation with organisms hiding in it. That is, the dense distribution of vegetation under normal growth is different from the dense distribution of vegetation when someone is pressing down on it. When the actual characteristics of the vegetation are consistent with the normal characteristics without external influence, it can be determined that there are no intruders at the current perimeter and no specific warning is needed. When the actual characteristics of the vegetation are inconsistent with the normal characteristics without external influence, further, it can be determined whether the difference in vegetation characteristics is a normal or abnormal phenomenon by whether the vegetation is continuously growing differently / the difference in characteristics caused by special planting by staff, or by whether there is a difference between the actual shaking sound of the vegetation and the shaking sound caused by normal wind. If the difference in vegetation characteristics is a normal phenomenon, no abnormal warning is needed. If the difference in vegetation characteristics is an abnormal phenomenon, an abnormal warning is needed. This embodiment of the invention does not limit this.

[0131] As can be seen, this optional embodiment can determine the rationality of the monitoring and early warning area based on the actual vegetation characteristics and current normal natural phenomena, and further determine the result of the abnormal early warning execution condition being met. This is conducive to improving the comprehensiveness, rationality and pertinence of the method for determining the result of the abnormal early warning execution condition being met, and thus conducive to improving the accuracy and reliability of the determined result of the abnormal early warning execution condition being met. In this way, it is conducive to improving the accuracy and timeliness of the early warning operation triggered by the result of the abnormal early warning execution condition being met.

[0132] In another optional embodiment, the above-mentioned determination of whether the monitoring and early warning area meets the preset reasonable vegetation characteristic change conditions may include:

[0133] Determine the duration of vegetation variation in the monitoring and early warning area, and identify specific vegetation planting records for the area. Based on the duration and the specific vegetation planting records, determine whether the monitoring and early warning area meets preset predictable vegetation characteristic anomaly conditions. If the monitoring and early warning area meets the predictable vegetation characteristic anomaly conditions, determine that it meets preset reasonable vegetation characteristic change conditions. If the monitoring and early warning area does not meet the predictable vegetation characteristic anomaly conditions, determine that it does not meet preset reasonable vegetation characteristic change conditions. And / or,

[0134] Based on current natural phenomena, the system determines the first change information regarding swaying and swaying caused by natural wind blowing through the monitoring and warning area. Based on the current actual vegetation swaying and swaying situation, it determines the second change information regarding swaying and swaying in the monitoring and warning area. Based on the first and second change information, it determines whether the monitoring and warning area meets the preset conditions for unnatural vegetation swaying. If the monitoring and warning area meets the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area does not meet the preset conditions for reasonable vegetation characteristic changes. If the monitoring and warning area does not meet the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area meets the preset conditions for reasonable vegetation characteristic changes. The first and second change information each include one or more of the following: swaying amplitude information, swaying trajectory information, swaying frequency information, swaying sound volume information, swaying frequency information, swaying amplitude information, swaying duration information, and swaying timbre information.

[0135] Further optionally, the above-mentioned determination of whether the monitoring and early warning area meets the preset predictable vegetation characteristic anomaly conditions based on the generated duration and special vegetation planting record information may include:

[0136] Determine whether the growth duration is greater than or equal to a preset growth duration threshold; if the determination result is yes, determine that the monitoring and warning area meets the preset predictable vegetation characteristic anomaly conditions; if the determination result is no, determine that the monitoring and warning area does not meet the preset predictable vegetation characteristic anomaly conditions; and / or,

[0137] Determine whether the special vegetation planting record information indicates that the monitoring and early warning area has been specially planted with vegetation; if the determination result is yes, determine that the monitoring and early warning area meets the preset predictable vegetation characteristic anomaly conditions; if the determination result is no, determine that the monitoring and early warning area does not meet the preset predictable vegetation characteristic anomaly conditions.

[0138] Optionally, for predictable vegetation feature anomalies, examples can be given: for instance, vegetation will not suddenly and drastically deform without reason. If historical monitoring shows that vegetation has been growing abnormally and gradually deviating from the norm for a period of time, then the abnormal vegetation features are traceable and predictable, which means they meet the preset reasonable vegetation feature change conditions. Another example is that information from special vegetation planting records shows that the vegetation in the monitoring and warning area was planted specifically for research and development, resulting in abnormal vegetation features. In other words, the fixed setting of the monitoring and warning area leads to abnormal vegetation features. In this case, the abnormal vegetation features are traceable and predictable, which means they meet the preset reasonable vegetation feature change conditions. Other situations can be understood in the same way. This embodiment of the invention does not limit the scope of the invention.

[0139] Further optionally, the determination of whether the monitoring and early warning area meets the preset conditions for non-natural vegetation shaking based on the first change information and the second change information may include:

[0140] Determine whether the first change information matches the second change information; if the determination result is yes, determine that the monitoring and warning area does not meet the preset non-natural vegetation shaking conditions; if the determination result is no, determine that the monitoring and warning area meets the preset non-natural vegetation shaking conditions.

[0141] Optionally, for non-natural vegetation shaking conditions, for example: the shaking and sound caused by wind blowing vegetation is different from the shaking and sound caused by human intrusion. For example, the shaking and sound caused by wind blowing may be continuous, while the shaking and sound caused by human intrusion may be intermittent and rustling. Therefore, if the actual shaking and sound is inconsistent with the natural shaking and sound (such as the shaking and sound caused by wind blowing), it can be considered that an external organism has intruded, further confirming that the non-natural vegetation shaking condition is met; if the actual shaking and sound is consistent with the natural shaking and sound, it can be considered that it is just wind blowing and not the intrusion of an external organism, further confirming that the non-natural vegetation shaking condition is not met. Other situations can be obtained in the same way, and the embodiments of the present invention are not limited.

[0142] As can be seen, this optional embodiment can determine the results of predictable vegetation characteristic abnormality conditions based on the duration of vegetation variation growth phenomena and special vegetation planting record information, and / or determine the results of vegetation non-natural shaking conditions based on current normal natural phenomena and current actual vegetation shaking and swaying conditions, and further determine the results of reasonable vegetation characteristic change conditions. This is conducive to improving the comprehensiveness and rationality of the method for determining the results of reasonable vegetation characteristic change conditions, and to improving the diversity, flexibility and pertinence of the method for determining the results of reasonable vegetation characteristic change conditions, thereby improving the accuracy and reliability of the determined results of reasonable vegetation characteristic change conditions.

[0143] In another optional embodiment, determining the first required operating parameters of the perimeter monitoring and early warning equipment based on weather and seasonal characteristics may include:

[0144] Based on weather characteristics, determine the ambient light level, ambient noise level, ambient wind direction and force, and ambient medium density of the monitoring and early warning area;

[0145] Based on seasonal characteristics, determine the environmental temperature, plant growth and animal activity, and astronomical and geographical conditions of the monitoring and early warning area;

[0146] Based on the monitoring and early warning area and perimeter monitoring and early warning equipment, the media propagation stability requirements are determined according to the environmental wind direction and force, astronomical and geographical conditions and environmental temperature. The media penetration requirements are determined according to the environmental brightness, environmental media density and environmental noise. The media ecological effect requirements are determined according to the plant growth and animal activity.

[0147] Based on the requirements for media propagation stability, media penetration, and media ecological effects, the first sensing medium type and its corresponding sensing parameter information are determined to obtain the first required operating parameters for the perimeter monitoring and early warning equipment.

[0148] Optionally, for example: the repelling effect of using the same laser medium is different when it is very bright during the day and very dark at night / dark during a rainstorm; the volume of the repelling is also different depending on the noise level during rain / sunny day; the required penetration is also different depending on the degree of obstruction during rain / sunny day. The embodiments of the present invention are not limited.

[0149] Optionally, for environmental wind direction and force conditions, astronomical and geographical conditions, environmental temperature conditions, and medium propagation stability requirements, examples can be given: for instance, environmental wind direction and force conditions are used to indicate that the stronger the wind force and the more mismatched the wind direction with the medium propagation direction; astronomical and geographical conditions are used to indicate that the more mismatched the Earth's rotation direction with the actual medium propagation direction; and environmental temperature conditions are used to indicate that the more extreme the temperature, the stronger the medium propagation stability is required. The same logic applies to other cases, and the embodiments of the present invention are not limited.

[0150] Optionally, for different environmental conditions such as brightness, density, noise, and penetrability, examples can be given: when brightness is used to indicate darkness, density is used to indicate particle density, and noise is used to indicate noise, then stronger penetrability is required. The same applies to other conditions. This invention does not impose any limitations.

[0151] Optionally, based on the plant growth and animal activity conditions and the requirements of the media ecological effect, for example: the required media ecological effect varies depending on the rarity of different plants and animals and their ability to withstand external disturbances. When the rarity is higher and the ability to withstand external disturbances is weaker, the corresponding media ecological effect is lower. The same applies to other situations. The embodiments of the present invention are not limited.

[0152] Optionally, the first sensing medium type may include, but is not limited to, one or more of the following: sound medium type, ultrasonic medium type, radiation medium type, light medium type, laser medium type, electromagnetic wave medium type, object medium type (such as using a spherical object as a medium), liquid medium type, solid medium type, gas medium type, molecular medium type, etc., and the embodiments of the present invention do not limit it.

[0153] As can be seen, this optional embodiment can provide a specific method for determining the first required operating parameters. Based on weather and seasonal characteristics, it determines the medium propagation stability requirements, medium penetration requirements, and medium ecological effect requirements, and further determines the first sensing medium type and its corresponding sensing parameter information. This is beneficial to improving the comprehensiveness and rationality of the method for determining the first required operating parameters, as well as the diversity, flexibility, and pertinence of the parameters considered in determining the first required operating parameters. In turn, it is beneficial to improve the accuracy and reliability of the determined first required operating parameters, thereby optimizing the monitoring and early warning effect of the subsequent perimeter monitoring and early warning equipment based on the first required operating parameters.

[0154] In another optional embodiment, determining the second required operating parameters for the perimeter monitoring and early warning equipment based on vegetation and topography may include:

[0155] Based on vegetation and topography, determine the distribution of obstructions, the nature of the obstructions, and geographical conditions in the monitoring and early warning area;

[0156] Based on the monitoring and early warning area and perimeter monitoring and early warning equipment, and according to the distribution of obstructions, the nature of obstructions, and geographical conditions, the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, are determined.

[0157] Based on the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, the type of the second sensing medium and its corresponding sensing parameter information are determined in order to obtain the second required operating parameters for the perimeter monitoring and early warning equipment.

[0158] Optionally, for the distribution of obstructions, the properties of obstructions, geographical conditions, the requirements for the dispersion and penetration of the medium, and the requirements related to the propagation trajectory of the medium, for example: when the distribution of obstructions is used to indicate that the wider the distribution, the stronger the dispersion of the medium is required; when the properties of obstructions are used to indicate that the thicker and denser the obstructions, the stronger the penetration of the medium is required; different properties of obstructions match different media with different penetration requirements; when geographical conditions are used to indicate that the more undulating and winding the geographical conditions, the stronger the ability of the medium to change its propagation trajectory is required; other cases can be obtained in the same way, and the embodiments of the present invention are not limited.

[0159] Optionally, the second sensing medium type may include, but is not limited to, one or more of the following: sound medium type, ultrasonic medium type, radiation medium type, light medium type, laser medium type, electromagnetic wave medium type, object medium type (such as using a spherical object as a medium), liquid medium type, solid medium type, gas medium type, molecular medium type, etc., and the embodiments of the present invention are not limited thereto.

[0160] As can be seen, this optional embodiment can provide a specific method for determining the second required operating parameters. By determining the requirements for the dispersion and penetration of the medium and the related requirements for the propagation trajectory of the medium based on vegetation and topography, it further determines the type of the second sensing medium and its corresponding sensing parameter information. This is beneficial to improving the comprehensiveness and rationality of the method for determining the second required operating parameters, as well as to improving the diversity, flexibility, and pertinence of the parameters considered in determining the second required operating parameters. In turn, it is beneficial to improve the accuracy and reliability of the determined second required operating parameters, thereby optimizing the monitoring and early warning effect of the subsequent perimeter monitoring and early warning equipment based on the second required operating parameters.

[0161] Example 2

[0162] Please see Figure 2 , Figure 2 This is a flowchart illustrating another perimeter monitoring and intelligent early warning method based on environmental interference factors disclosed in an embodiment of the present invention. Figure 2 The described method can be applied to perimeter monitoring and intelligent early warning systems based on environmental interference factors. This system may include a server, which may be a local server or a cloud server; this embodiment of the invention does not limit the scope. Figure 2 As shown, this perimeter monitoring and intelligent early warning method based on environmental interference factors includes the following operations:

[0163] 201. Obtain real-time weather and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determine the first required operating parameters of the perimeter monitoring and early warning equipment based on the weather and seasonal characteristics.

[0164] 202. Obtain the vegetation and topography of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determine the second required operating parameters of the perimeter monitoring and early warning equipment based on the vegetation and topography.

[0165] 203. Based on real-time weather characteristics, seasonal characteristics, vegetation conditions, and topography, determine the current routine natural phenomena in the monitoring and early warning area.

[0166] 204. Based on the first requirement operating parameters, the second requirement operating parameters, and current normal natural phenomena, control the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area.

[0167] 205. When an abnormal fault is detected in the perimeter monitoring and early warning equipment, obtain the equipment operation data of the perimeter monitoring and early warning equipment in the historical time period before the abnormal fault occurred.

[0168] 206. Based on the equipment operation data, determine whether the perimeter monitoring and early warning equipment meets the preset predictable fault conditions. If the determination result is yes, proceed to step 207; if the determination result is no, proceed to step 208.

[0169] Optionally, for predictable failure conditions, for example: if the perimeter monitoring and early warning equipment has been used for too long and the equipment / component has been previously detected to be operating intermittently / unstable, then the predictable failure condition is determined to be met; if the perimeter monitoring and early warning equipment has been used for a short time and the previously monitored equipment / component is operating well, then the predictable failure condition is determined not to be met. This embodiment of the invention does not impose any limitations.

[0170] 207. Generate a first prompt command to alert maintenance personnel to handle the fault of the perimeter monitoring and early warning equipment.

[0171] 208. Obtain equipment monitoring data collected by the perimeter monitoring and early warning equipment and its surrounding equipment in the historical period preceding the occurrence of the abnormal fault.

[0172] Optionally, the device monitoring data may include, but is not limited to, one or more of camera data, video data, voice data, and other types of monitoring data, and this embodiment of the invention does not impose any limitations.

[0173] 209. Based on the equipment monitoring data, determine whether the perimeter monitoring and early warning equipment meets the preset conditions for biological malfunction.

[0174] Optionally, for the condition of biological malfunction, for example: when the perimeter monitoring and early warning equipment malfunctions due to intentional damage by an intruder or intentional or unintentional entry by a living organism, the condition of biological malfunction is determined to be met. This embodiment of the invention does not limit this.

[0175] 210. When it is determined that the perimeter monitoring and early warning equipment meets the conditions for biological malfunction, a second prompt instruction is generated to prompt maintenance personnel to handle the malfunction of the perimeter monitoring and early warning equipment, and a third prompt instruction is generated to prompt security personnel to respond to the alarm caused by the biological object.

[0176] Optionally, in addition to performing equipment maintenance on the perimeter monitoring and early warning equipment, when the equipment malfunctions due to intentional damage by intruders or unintentional intrusion by living beings, it is necessary to dispatch an emergency response to prevent further danger. This embodiment of the invention does not limit the scope of the invention.

[0177] In this embodiment of the invention, for other descriptions of steps 201-210, please refer to the other detailed descriptions of steps 101-104 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0178] As can be seen, the embodiments of the present invention can determine the first required operating parameters based on weather and seasonal characteristics, the second required operating parameters based on vegetation and topography, and the current routine natural phenomena in the monitoring and early warning area. Furthermore, based on the first and second required operating parameters and the current routine natural phenomena, the perimeter monitoring and early warning equipment is controlled to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area. This is beneficial for improving the comprehensiveness and rationality of perimeter monitoring and intelligent early warning methods, for increasing the diversity, specificity, and flexibility of the parameters considered for perimeter monitoring and early warning, and thus for improving the accuracy and reliability of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area. It also helps to improve the efficiency, convenience, and timeliness of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area, thereby improving the perimeter... This system improves the accuracy and timeliness of responses to anomalies and enhances perimeter security. Furthermore, it provides fault analysis and response methods for perimeter monitoring and early warning equipment. Based on determined equipment operating data, it identifies predictable fault conditions and biologically induced fault conditions. Corresponding fault response prompts are generated based on these conditions, improving the comprehensiveness, rationality, and progressive nature of fault analysis and response methods. This, in turn, enhances the diversity, flexibility, and relevance of fault response prompt generation methods, thereby improving the accuracy and reliability of the identified fault response prompts. Ultimately, this improves the accuracy and reliability of fault response for perimeter monitoring and early warning equipment, and helps address situations where equipment malfunctions due to malicious damage.

[0179] In an optional embodiment, the above-mentioned determination of whether the perimeter monitoring and early warning device meets the preset predictable fault conditions based on device operating data may include:

[0180] Based on the equipment operation data, determine the usage time of the perimeter monitoring and early warning equipment, and based on the usage time, determine whether the perimeter monitoring and early warning equipment meets the preset lifespan-induced failure conditions.

[0181] When it is determined that the perimeter monitoring and early warning equipment meets the life-related failure conditions, it is determined that the perimeter monitoring and early warning equipment meets the preset predictable failure conditions.

[0182] When it is determined that the perimeter monitoring and early warning equipment does not meet the conditions for failure due to its lifespan, the operating effect of the perimeter monitoring and early warning equipment is determined based on the equipment operation data, and based on the operating effect, it is determined whether the perimeter monitoring and early warning equipment meets the preset intermittent failure conditions.

[0183] When it is determined that the perimeter monitoring and early warning equipment meets the intermittent failure condition, it is determined that the perimeter monitoring and early warning equipment meets the preset predictable failure condition.

[0184] When it is determined that the perimeter monitoring and early warning equipment does not meet the intermittent failure conditions, it is determined that the perimeter monitoring and early warning equipment does not meet the preset predictable failure conditions.

[0185] Further optionally, the above-mentioned determination of whether the perimeter monitoring and early warning equipment meets the preset lifespan-induced failure conditions based on the duration of use may include:

[0186] Determine whether the usage time is greater than or equal to the preset usage time threshold; if the determination result is yes, determine that the perimeter monitoring and early warning equipment meets the preset lifespan-induced failure conditions; if the determination result is no, determine that the perimeter monitoring and early warning equipment does not meet the preset lifespan-induced failure conditions.

[0187] Optionally, the above-mentioned intermittent failure conditions can be illustrated as follows: if the perimeter monitoring and early warning equipment has been operating intermittently or unstable, then the intermittent failure conditions are determined to be met; if the perimeter monitoring and early warning equipment is operating well, then the perimeter is determined not to meet the intermittent failure conditions. This embodiment of the invention does not impose any limitations.

[0188] As can be seen, this optional embodiment can determine the failure condition fulfillment results caused by lifetime and the failure condition fulfillment results of intermittent failure, and thus determine the predictable failure condition fulfillment results. This is beneficial to improving the comprehensiveness, rationality, and progressiveness of the predictable failure condition fulfillment results, and to improving the diversity and flexibility of the parameters considered in determining the predictable failure condition fulfillment results. This, in turn, is beneficial to improving the accuracy and reliability of the determined predictable failure condition fulfillment results, thereby improving the accuracy and timeliness of subsequent failure response operations triggered by the predictable failure condition fulfillment results.

[0189] Example 3

[0190] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a perimeter monitoring and intelligent early warning system based on environmental interference factors, as disclosed in an embodiment of the present invention. Figure 3 The described system may include a server, which may be a local server or a cloud server; this embodiment of the invention does not limit the scope. Figure 3 As shown, the perimeter monitoring and intelligent early warning system based on environmental interference factors may include:

[0191] The first parameter determination module 301 is used to obtain the real-time weather characteristics and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determine the first required operating parameters of the perimeter monitoring and early warning equipment based on the weather characteristics and seasonal characteristics.

[0192] The second parameter determination module 302 is used to obtain the vegetation and topographic conditions of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and to determine the second required operating parameters of the perimeter monitoring and early warning equipment based on the vegetation and topographic conditions.

[0193] The routine phenomenon determination module 303 is used to determine the current routine natural phenomena in the monitoring and early warning area based on real-time weather characteristics, seasonal characteristics, vegetation conditions and topography.

[0194] The monitoring and early warning module 304 is used to control the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first requirement operating parameters, the second requirement operating parameters, and the current normal natural phenomena.

[0195] It is evident that implementation Figure 3 The described perimeter monitoring and intelligent early warning system based on environmental interference factors can determine the first required operating parameters based on weather and seasonal characteristics, the second required operating parameters based on vegetation and topography, and the current routine natural phenomena in the monitoring and early warning area. Furthermore, based on the first and second required operating parameters and the current routine natural phenomena, the system controls the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations in the monitoring and early warning area. This improves the comprehensiveness and rationality of perimeter monitoring and intelligent early warning methods, enhances the diversity, specificity, and flexibility of the parameters considered for perimeter monitoring and early warning, and consequently improves the accuracy and reliability of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area. It also improves the efficiency, convenience, and timeliness of monitoring and early warning for the perimeter monitoring and early warning equipment and the monitoring and early warning area, thereby improving the accuracy and timeliness of responding to perimeter anomalies and enhancing perimeter security.

[0196] In an optional embodiment, the monitoring and early warning module 304 controls the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first required operating parameters, the second required operating parameters, and current normal natural phenomena. Specifically, this includes:

[0197] Based on the vegetation conditions, determine the current actual vegetation phenomena in the monitoring and early warning area. The current actual vegetation phenomena include one or more of the following: current actual vegetation density, current actual vegetation swaying and sounding, and current actual vegetation growth and shape.

[0198] Based on current normal natural phenomena and current actual vegetation conditions, determine whether the perimeter monitoring and early warning equipment meets the preset abnormal early warning execution conditions;

[0199] When it is determined that the perimeter monitoring and early warning equipment meets the conditions for abnormal early warning execution, the target early warning object and its related characteristic information are determined based on the current normal natural phenomena and the current actual vegetation phenomena; based on the target early warning object and its related characteristic information, the first required operating parameters, and the second required operating parameters, the targeted early warning operation mode of the perimeter monitoring and early warning equipment is determined; based on the targeted early warning operation mode, the perimeter monitoring and early warning equipment is controlled to execute the corresponding early warning operation.

[0200] When it is determined that the perimeter monitoring and early warning equipment does not meet the abnormal early warning execution conditions, the normal early warning operation mode of the perimeter monitoring and early warning equipment is determined according to the first requirement operation parameter and the second requirement operation parameter; according to the normal early warning operation mode, the perimeter monitoring and early warning equipment is controlled to perform the corresponding early warning operation.

[0201] It is evident that implementation Figure 4 The described system can determine the fulfillment of abnormal early warning execution conditions based on current normal natural phenomena and actual vegetation conditions. It matches corresponding perimeter monitoring and early warning equipment operation modes and early warning operations to those that meet and do not meet the abnormal early warning execution conditions. This improves the comprehensiveness and rationality of the determination method for the early warning operation mode of the perimeter monitoring and early warning equipment, enhances the diversity, flexibility, and relevance of the determination method, and consequently improves the accuracy and reliability of the determined early warning operation mode, thereby improving the early warning accuracy and reliability of the perimeter monitoring and early warning equipment.

[0202] In another optional embodiment, the monitoring and early warning module 304 determines whether the perimeter monitoring and early warning device meets the preset abnormal early warning execution conditions based on current normal natural phenomena and current actual vegetation conditions. The specific methods include:

[0203] Based on the current actual vegetation density, current actual vegetation growth and shape, determine the actual vegetation characteristics of the monitoring and early warning area;

[0204] Based on the actual vegetation characteristics and current common natural phenomena, determine whether the monitoring and early warning area meets the preset unconventional vegetation characteristic conditions;

[0205] When it is determined that the monitoring and early warning area meets the unconventional vegetation characteristic conditions, it is then determined whether the monitoring and early warning area meets the preset reasonable vegetation characteristic change conditions.

[0206] When it is determined that the monitoring and early warning area meets the conditions for reasonable vegetation characteristic changes, it is determined that the perimeter monitoring and early warning equipment does not meet the preset abnormal early warning execution conditions.

[0207] When it is determined that the monitoring and early warning area does not meet the conditions for reasonable vegetation characteristic changes, the perimeter monitoring and early warning equipment is determined to meet the preset abnormal early warning execution conditions.

[0208] It is evident that implementation Figure 4 The described system can also determine the rationality of the monitoring and early warning area based on the actual vegetation characteristics and current normal natural phenomena. The vegetation characteristic change conditions are met, and the abnormal early warning execution conditions are met. This helps to improve the comprehensiveness, rationality and pertinence of the method for determining the abnormal early warning execution conditions, and thus helps to improve the accuracy and reliability of the determined abnormal early warning execution conditions. In this way, it helps to improve the accuracy and timeliness of the early warning operation triggered by the abnormal early warning execution conditions.

[0209] In another optional embodiment, the monitoring and early warning module 304 determines whether the monitoring and early warning area meets the preset reasonable vegetation characteristic change conditions in the following ways:

[0210] Determine the duration of vegetation variation in the monitoring and early warning area, and identify specific vegetation planting records for the area. Based on the duration and the specific vegetation planting records, determine whether the monitoring and early warning area meets preset predictable vegetation characteristic anomaly conditions. If the monitoring and early warning area meets the predictable vegetation characteristic anomaly conditions, determine that it meets preset reasonable vegetation characteristic change conditions. If the monitoring and early warning area does not meet the predictable vegetation characteristic anomaly conditions, determine that it does not meet preset reasonable vegetation characteristic change conditions. And / or,

[0211] Based on current natural phenomena, the system determines the first change information regarding swaying and swaying caused by natural wind blowing through the monitoring and warning area. Based on the current actual vegetation swaying and swaying situation, it determines the second change information regarding swaying and swaying in the monitoring and warning area. Based on the first and second change information, it determines whether the monitoring and warning area meets the preset conditions for unnatural vegetation swaying. If the monitoring and warning area meets the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area does not meet the preset conditions for reasonable vegetation characteristic changes. If the monitoring and warning area does not meet the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area meets the preset conditions for reasonable vegetation characteristic changes. The first and second change information each include one or more of the following: swaying amplitude information, swaying trajectory information, swaying frequency information, swaying sound volume information, swaying frequency information, swaying amplitude information, swaying duration information, and swaying timbre information.

[0212] It is evident that implementation Figure 4The described system can also determine the results of predictable vegetation characteristic anomaly conditions based on the duration of vegetation variation growth phenomena and special vegetation planting records, and / or determine the results of non-natural vegetation shaking conditions based on current normal natural phenomena and current actual vegetation shaking and swaying. This further determines the results of reasonable vegetation characteristic change conditions, which helps to improve the comprehensiveness and rationality of the method for determining the results of reasonable vegetation characteristic change conditions, and helps to improve the diversity, flexibility and pertinence of the method for determining the results of reasonable vegetation characteristic change conditions, thereby improving the accuracy and reliability of the determined results of reasonable vegetation characteristic change conditions.

[0213] In another optional embodiment, the method by which the first parameter determination module 301 determines the first required operating parameters of the perimeter monitoring and early warning equipment based on weather and seasonal characteristics specifically includes:

[0214] Based on weather characteristics, determine the ambient light level, ambient noise level, ambient wind direction and force, and ambient medium density of the monitoring and early warning area;

[0215] Based on seasonal characteristics, determine the environmental temperature, plant growth and animal activity, and astronomical and geographical conditions of the monitoring and early warning area;

[0216] Based on the monitoring and early warning area and perimeter monitoring and early warning equipment, the media propagation stability requirements are determined according to the environmental wind direction and force, astronomical and geographical conditions and environmental temperature. The media penetration requirements are determined according to the environmental brightness, environmental media density and environmental noise. The media ecological effect requirements are determined according to the plant growth and animal activity.

[0217] Based on the requirements for media propagation stability, media penetration, and media ecological effects, the first sensing medium type and its corresponding sensing parameter information are determined to obtain the first required operating parameters for the perimeter monitoring and early warning equipment.

[0218] It is evident that implementation Figure 4 The described system can also provide a specific method for determining the first requirement operating parameters. Based on weather and seasonal characteristics, it determines the medium propagation stability requirements, medium penetration requirements, and medium ecological effect requirements, and further determines the first sensing medium type and its corresponding sensing parameter information. This is beneficial to improving the comprehensiveness and rationality of the method for determining the first requirement operating parameters, as well as the diversity, flexibility, and relevance of the parameters considered in determining the first requirement operating parameters. In turn, it is beneficial to improve the accuracy and reliability of the determined first requirement operating parameters, thereby optimizing the monitoring and early warning effect of subsequent perimeter monitoring and early warning equipment based on the first requirement operating parameters.

[0219] In another optional embodiment, the second parameter determination module 302 determines the second required operating parameters of the perimeter monitoring and early warning equipment based on vegetation conditions and topographical features in the following specific ways:

[0220] Based on vegetation and topography, determine the distribution of obstructions, the nature of the obstructions, and geographical conditions in the monitoring and early warning area;

[0221] Based on the monitoring and early warning area and perimeter monitoring and early warning equipment, and according to the distribution of obstructions, the nature of obstructions, and geographical conditions, the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, are determined.

[0222] Based on the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, the type of the second sensing medium and its corresponding sensing parameter information are determined in order to obtain the second required operating parameters for the perimeter monitoring and early warning equipment.

[0223] It is evident that implementation Figure 4 The described system can also provide a specific method for determining the second requirement operating parameters. Based on vegetation and topography, it determines the requirements for the dispersion and penetration of the medium, as well as the requirements related to the medium's propagation trajectory, further determining the type of the second sensing medium and its corresponding sensing parameter information. This helps improve the comprehensiveness and rationality of the method for determining the second requirement operating parameters, and also helps improve the diversity, flexibility, and pertinence of the parameters considered in determining the second requirement operating parameters. In turn, it helps improve the accuracy and reliability of the determined second requirement operating parameters, thereby helping to optimize the monitoring and early warning effect of the subsequent perimeter monitoring and early warning equipment based on the second requirement operating parameters.

[0224] In yet another alternative embodiment, such as Figure 4 As shown, the system may also include:

[0225] The fault handling module 305 is used to, when an abnormal fault is detected in the perimeter monitoring and early warning device, acquire the device's operating data for the historical period preceding the occurrence of the abnormal fault; based on the operating data, determine whether the perimeter monitoring and early warning device meets preset predictable fault conditions; if the perimeter monitoring and early warning device meets the predictable fault conditions, generate a first prompt instruction to prompt maintenance personnel to handle the fault; if the perimeter monitoring and early warning device does not meet the predictable fault conditions, acquire the device monitoring data collected by the perimeter monitoring and early warning device and its surrounding devices during the historical period preceding the occurrence of the abnormal fault; based on the device monitoring data, determine whether the perimeter monitoring and early warning device meets preset biologically induced fault conditions; if the perimeter monitoring and early warning device meets the biologically induced fault conditions, generate a second prompt instruction to prompt maintenance personnel to handle the fault, and generate a third prompt instruction to prompt security personnel to respond to the alarm caused by the biological object.

[0226] It is evident that implementation Figure 4 The described system can also provide fault analysis and response methods for perimeter monitoring and early warning equipment. It determines the expected failure conditions based on the identified equipment operating data and the biologically induced failure conditions based on the equipment monitoring data. Based on the expected failure conditions and the biologically induced failure conditions, it matches corresponding fault response prompts, improving the comprehensiveness, rationality, and progressive nature of the fault analysis and response methods. This, in turn, enhances the diversity, flexibility, and relevance of the fault response prompt generation methods, thereby improving the accuracy and reliability of the determined fault response prompts. Furthermore, it improves the accuracy and reliability of fault response for perimeter monitoring and early warning equipment, and helps address situations where equipment malfunctions due to malicious damage.

[0227] In another optional embodiment, the fault handling module 305 determines whether the perimeter monitoring and early warning device meets the preset predictable fault conditions based on the device operation data, specifically including:

[0228] Based on the equipment operation data, determine the usage time of the perimeter monitoring and early warning equipment, and based on the usage time, determine whether the perimeter monitoring and early warning equipment meets the preset lifespan-induced failure conditions.

[0229] When it is determined that the perimeter monitoring and early warning equipment meets the life-related failure conditions, it is determined that the perimeter monitoring and early warning equipment meets the preset predictable failure conditions.

[0230] When it is determined that the perimeter monitoring and early warning equipment does not meet the conditions for failure due to its lifespan, the operating effect of the perimeter monitoring and early warning equipment is determined based on the equipment operation data, and based on the operating effect, it is determined whether the perimeter monitoring and early warning equipment meets the preset intermittent failure conditions.

[0231] When it is determined that the perimeter monitoring and early warning equipment meets the intermittent failure condition, it is determined that the perimeter monitoring and early warning equipment meets the preset predictable failure condition.

[0232] When it is determined that the perimeter monitoring and early warning equipment does not meet the intermittent failure conditions, it is determined that the perimeter monitoring and early warning equipment does not meet the preset predictable failure conditions.

[0233] It is evident that implementation Figure 4 The described system can also determine the fulfillment results of lifetime-induced failure conditions and intermittent failure conditions, and further determine the fulfillment results of predictable failure conditions. This helps to improve the comprehensiveness, rationality, and progressive nature of the fulfillment results of predictable failure conditions, and helps to improve the diversity and flexibility of the parameters considered in determining the fulfillment results of predictable failure conditions. In turn, it helps to improve the accuracy and reliability of the determined fulfillment results of predictable failure conditions, thereby improving the accuracy and timeliness of subsequent failure response operations triggered by the fulfillment results of predictable failure conditions.

[0234] Example 4

[0235] Please see Figure 5 , Figure 5 This is a schematic diagram of another perimeter monitoring and intelligent early warning system based on environmental interference factors disclosed in an embodiment of the present invention. Wherein, Figure 5 The described system may include a server, which may be a local server or a cloud server; this embodiment of the invention does not limit the scope. Figure 5 As shown, the system may include:

[0236] Memory 401 storing executable program code;

[0237] Processor 402 coupled to memory 401;

[0238] Furthermore, it may also include an input interface 403 coupled to the processor 402 and an output interface 404;

[0239] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the perimeter monitoring and intelligent early warning method based on environmental interference factors described in Embodiment 1 or Embodiment 2.

[0240] Example 5

[0241] This invention discloses a computer storage medium that stores a computer program for electronic data interchange, wherein the computer program causes a computer to execute the steps in the perimeter monitoring and intelligent early warning method based on environmental interference factors described in Embodiment 1 or Embodiment 2.

[0242] Example 6

[0243] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the perimeter monitoring and intelligent early warning method based on environmental interference factors described in Embodiment 1 or Embodiment 2.

[0244] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0245] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0246] Finally, it should be noted that the perimeter monitoring and intelligent early warning method and system based on environmental interference factors disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A perimeter monitoring and intelligent early warning method based on environmental interference factors, characterized in that, The method includes: The system acquires real-time weather and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determines the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather and seasonal characteristics. The vegetation and topography of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning device are obtained, and the second required operating parameters of the perimeter monitoring and early warning device are determined based on the vegetation and topography. Based on the real-time weather characteristics, seasonal characteristics, vegetation conditions, and topographic features, the current routine natural phenomena in the monitoring and early warning area are determined. Based on the first required operating parameters, the second required operating parameters, and the current normal natural phenomena, the perimeter monitoring and early warning equipment is controlled to perform corresponding monitoring analysis and early warning operations on the monitored and early warning area. And, determining the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather characteristics and the seasonal characteristics includes: Based on the real-time weather characteristics, determine the ambient brightness, ambient noise, ambient wind direction and force, and ambient medium density of the monitoring and early warning area; Based on the seasonal characteristics, determine the environmental temperature, plant growth and animal activity, and astronomical and geographical conditions of the monitoring and early warning area; Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the medium propagation stability requirements are determined according to the environmental wind direction and force, the astronomical and geographical conditions, and the environmental temperature. The medium penetration requirements are determined according to the environmental brightness, the environmental medium density, and the environmental noise. The medium ecological effect requirements are determined according to the plant growth and animal activity. Based on the medium propagation stability requirements, the medium penetration requirements, and the medium ecological effect requirements, the first sensing medium type and its corresponding sensing parameter information are determined to obtain the first required operating parameters of the perimeter monitoring and early warning equipment. And, determining the second required operating parameters of the perimeter monitoring and early warning equipment based on the vegetation and topographical conditions includes: Based on the vegetation and topography, determine the distribution of obstructions, the nature of the obstructions, and the geographical conditions of the monitoring and early warning area. Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, are determined according to the distribution of the obstructions, the nature of the obstructions, and the geographical conditions. Based on the requirements for the dispersion and penetration of the medium and the requirements related to the propagation trajectory of the medium, the second sensing medium type and its corresponding sensing parameter information are determined to obtain the second required operating parameters of the perimeter monitoring and early warning equipment.

2. The perimeter monitoring and intelligent early warning method based on environmental interference factors according to claim 1, characterized in that, The step of controlling the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first required operating parameters, the second required operating parameters, and the current normal natural phenomena includes: Based on the vegetation conditions, the current actual vegetation phenomena in the monitoring and early warning area are determined. The current actual vegetation phenomena include one or more of the following: current actual vegetation density, current actual vegetation swaying and rattling, and current actual vegetation growth and shape. Based on the current normal natural phenomena and the current actual vegetation phenomena, determine whether the perimeter monitoring and early warning equipment meets the preset abnormal early warning execution conditions; When it is determined that the perimeter monitoring and early warning device meets the abnormal early warning execution conditions, the target early warning object and its related characteristic information are determined based on the current normal natural phenomena and the current actual vegetation phenomena; based on the target early warning object and its related characteristic information, the first required operating parameters, and the second required operating parameters, the targeted early warning operation mode of the perimeter monitoring and early warning device is determined; based on the targeted early warning operation mode, the perimeter monitoring and early warning device is controlled to perform corresponding early warning operations; When it is determined that the perimeter monitoring and early warning device does not meet the abnormal early warning execution conditions, the normal early warning operation mode of the perimeter monitoring and early warning device is determined according to the first required operation parameters and the second required operation parameters; according to the normal early warning operation mode, the perimeter monitoring and early warning device is controlled to perform the corresponding early warning operation.

3. The perimeter monitoring and intelligent early warning method based on environmental interference factors according to claim 2, characterized in that, The step of determining whether the perimeter monitoring and early warning device meets the preset abnormal early warning execution conditions based on the current normal natural phenomena and the current actual vegetation phenomena includes: Based on the current actual vegetation density, the current actual vegetation growth and shape, the actual vegetation characteristics of the monitoring and early warning area are determined; Based on the actual vegetation characteristics and the current conventional natural phenomena, determine whether the monitoring and early warning area meets the preset unconventional vegetation characteristic conditions; When it is determined that the monitoring and early warning area meets the unconventional vegetation characteristic conditions, it is determined whether the monitoring and early warning area meets the preset reasonable vegetation characteristic change conditions. When it is determined that the monitoring and early warning area meets the reasonable vegetation characteristic change conditions, it is determined that the perimeter monitoring and early warning device does not meet the preset abnormal early warning execution conditions. When it is determined that the monitoring and early warning area does not meet the reasonable vegetation characteristic change conditions, the perimeter monitoring and early warning device is determined to meet the preset abnormal early warning execution conditions.

4. The perimeter monitoring and intelligent early warning method based on environmental interference factors according to claim 3, characterized in that, The determination of whether the monitored and early warning area meets the preset reasonable vegetation characteristic change conditions includes: The duration of vegetation mutation in the monitored and early warning area is determined, and special vegetation planting records for the monitored and early warning area are identified. Based on the duration of the mutation and the special vegetation planting records, it is determined whether the monitored and early warning area meets preset predictable vegetation characteristic anomaly conditions. When it is determined that the monitored and early warning area meets the predictable vegetation characteristic anomaly conditions, it is determined that the monitored and early warning area meets preset reasonable vegetation characteristic change conditions. When it is determined that the monitored and early warning area does not meet the predictable vegetation characteristic anomaly conditions, it is determined that the monitored and early warning area does not meet preset reasonable vegetation characteristic change conditions; and / or, Based on the current normal natural phenomena, the first change information regarding the swaying and swaying sound caused by natural wind blowing through the monitoring and warning area is determined. Based on the current actual vegetation swaying and swaying sound, the second change information regarding the swaying and swaying sound currently occurring in the monitoring and warning area is determined. Based on the first and second change information, it is determined whether the monitoring and warning area meets the preset conditions for unnatural vegetation swaying. When it is determined that the monitoring and warning area meets the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area does not meet the preset conditions for reasonable vegetation characteristic changes. When it is determined that the monitoring and warning area does not meet the conditions for unnatural vegetation swaying, it is determined that the monitoring and warning area meets the preset conditions for reasonable vegetation characteristic changes. Wherein, the first and second change information each include one or more of the following: swaying amplitude information, swaying trajectory information, swaying frequency information, swaying sound volume information, swaying sound frequency information, swaying sound amplitude information, swaying sound duration information, and swaying sound timbre information.

5. The perimeter monitoring and intelligent early warning method based on environmental interference factors according to claim 1, characterized in that, The method further includes: When an abnormal malfunction is detected in the perimeter monitoring and early warning device, the device operation data of the perimeter monitoring and early warning device in the historical time period before the abnormal malfunction occurred is obtained. Based on the equipment operation data, determine whether the perimeter monitoring and early warning equipment meets the preset predictable fault conditions; When it is determined that the perimeter monitoring and early warning device meets the predictable fault conditions, a first prompting instruction is generated to prompt maintenance personnel to handle the fault of the perimeter monitoring and early warning device. When it is determined that the perimeter monitoring and early warning device does not meet the predictable fault conditions, the device monitoring data collected by the perimeter monitoring and early warning device and its surrounding devices in the historical time period before the occurrence of the abnormal fault phenomenon is obtained. Based on the device monitoring data, determine whether the perimeter monitoring and early warning device meets the preset biological fault conditions; When it is determined that the perimeter monitoring and early warning device meets the conditions for malfunction caused by the organism, a second prompt instruction is generated to prompt maintenance personnel to handle the malfunction of the perimeter monitoring and early warning device, and a third prompt instruction is generated to prompt security personnel to respond to the alarm for the organism that caused the malfunction.

6. The perimeter monitoring and intelligent early warning method based on environmental interference factors according to claim 5, characterized in that, The step of determining whether the perimeter monitoring and early warning device meets preset predictable fault conditions based on the device operation data includes: Based on the equipment operation data, determine the usage time of the perimeter monitoring and early warning equipment, and based on the usage time, determine whether the perimeter monitoring and early warning equipment meets the preset lifespan-induced failure conditions. When it is determined that the perimeter monitoring and early warning device meets the lifespan-induced failure condition, it is determined that the perimeter monitoring and early warning device meets the preset predictable failure condition. When it is determined that the perimeter monitoring and early warning device does not meet the lifespan-induced failure conditions, the operating effect of the perimeter monitoring and early warning device is determined based on the device operating data, and the operating effect is used to determine whether the perimeter monitoring and early warning device meets the preset intermittent failure conditions. When it is determined that the perimeter monitoring and early warning device meets the intermittent failure condition, it is determined that the perimeter monitoring and early warning device meets the preset predictable failure condition. When it is determined that the perimeter monitoring and early warning device does not meet the intermittent fault condition, it is determined that the perimeter monitoring and early warning device does not meet the preset predictable fault condition.

7. A perimeter monitoring and intelligent early warning system based on environmental interference factors, characterized in that, The system includes: The first parameter determination module is used to obtain the real-time weather characteristics and seasonal characteristics of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning equipment, and determine the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather characteristics and seasonal characteristics. The second parameter determination module is used to obtain the vegetation and topography of the monitoring and early warning area under the responsibility of the perimeter monitoring and early warning device, and determine the second required operating parameters of the perimeter monitoring and early warning device based on the vegetation and topography. The routine phenomenon determination module is used to determine the current routine natural phenomena in the monitoring and early warning area based on the real-time weather characteristics, seasonal characteristics, vegetation conditions, and topography. The monitoring and early warning module is used to control the perimeter monitoring and early warning equipment to perform corresponding monitoring analysis and early warning operations on the monitoring and early warning area based on the first required operating parameters, the second required operating parameters, and the current normal natural phenomena. Furthermore, the method by which the first parameter determining module determines the first required operating parameters of the perimeter monitoring and early warning equipment based on the real-time weather characteristics and the seasonal characteristics specifically includes: Based on the real-time weather characteristics, determine the ambient brightness, ambient noise, ambient wind direction and force, and ambient medium density of the monitoring and early warning area; Based on the seasonal characteristics, determine the environmental temperature, plant growth and animal activity, and astronomical and geographical conditions of the monitoring and early warning area; Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the medium propagation stability requirements are determined according to the environmental wind direction and force, the astronomical and geographical conditions, and the environmental temperature. The medium penetration requirements are determined according to the environmental brightness, the environmental medium density, and the environmental noise. The medium ecological effect requirements are determined according to the plant growth and animal activity. Based on the medium propagation stability requirements, the medium penetration requirements, and the medium ecological effect requirements, the first sensing medium type and its corresponding sensing parameter information are determined to obtain the first required operating parameters of the perimeter monitoring and early warning equipment. Furthermore, the method by which the second parameter determining module determines the second required operating parameters of the perimeter monitoring and early warning equipment based on the vegetation and topographical conditions specifically includes: Based on the vegetation and topography, determine the distribution of obstructions, the nature of the obstructions, and the geographical conditions of the monitoring and early warning area. Based on the monitoring and early warning area and the perimeter monitoring and early warning equipment, the requirements for media divergence and penetration, as well as the requirements related to media propagation trajectory, are determined according to the distribution of the obstructions, the nature of the obstructions, and the geographical conditions. Based on the requirements for the dispersion and penetration of the medium and the requirements related to the propagation trajectory of the medium, the second sensing medium type and its corresponding sensing parameter information are determined to obtain the second required operating parameters of the perimeter monitoring and early warning equipment.

8. A perimeter monitoring and intelligent early warning system based on environmental interference factors, characterized in that, The system includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the perimeter monitoring and intelligent early warning method based on environmental interference factors as described in any one of claims 1-6.

9. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the perimeter monitoring and intelligent early warning method based on environmental interference factors as described in any one of claims 1-6.

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