A distributed data monitoring platform for natural ecological landscapes

Abstract

The present invention belongs to the technical field of landscape monitoring and management, and specifically relates to a distributed data monitoring platform for natural ecological landscapes, which includes a natural ecological landscape monitoring unit, a distributed storage unit, a landscape form analysis unit, a growth environment assessment unit, and a landscape management terminal; the present invention monitors the natural ecological landscape in real time through the natural ecological landscape monitoring unit, and the landscape form analysis unit determines whether a landscape form abnormal signal is generated through landscape form analysis. When a landscape form abnormal signal is generated, a cause investigation and analysis are carried out and reasonable improvement measures are made for the natural ecological landscape. In addition, when a landscape form abnormal signal is generated, the growth environment assessment and analysis are carried out to judge the relevance between the natural ecological landscape abnormality and the growth environment. When a growth environment abnormal signal is generated, the monitoring and management of the environment where the natural ecological landscape is located are strengthened, which is beneficial to avoiding damage to the natural ecological landscape and significantly reducing the supervision difficulty of the natural ecological landscape.

Description

Technical Field

[0001] The present invention relates to the technical field of landscape monitoring and management, and particularly to a distributed data monitoring platform for natural ecological landscapes. Background Art

[0002] With the increasingly severe environmental problems, the monitoring and protection of natural ecological landscapes have become particularly important. In a Chinese invention patent with the publication number CN103678707A, a monitoring system and method for street tree ecological landscapes are disclosed. The technical solution of this invention combines on-site investigation and information collection, health monitoring through database processing, and interactive methods such as mouse and keyboard operations. It can provide functions of real-time information correction and browsing and querying, and promptly provide more intuitive and vivid digital images, thereby providing a more effective and reliable reference basis for the planning, design, maintenance, monitoring, and management of street trees, and improving work efficiency;

[0003] However, the above-mentioned invention technical solution is only limited to street tree management in actual application, and cannot effectively monitor a certain area involving natural ecological landscapes and judge the changes in their landscape forms. Moreover, it is difficult to reasonably analyze the correlation between abnormal landscape form changes and the growth environment, and it is difficult for management personnel to make reasonable countermeasures in time, which is not conducive to avoiding damage to natural ecological landscapes, and the supervision of natural ecological landscapes is difficult;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a distributed data monitoring platform for natural ecological landscapes, which solves the problems that the prior art cannot effectively monitor a certain area involving natural ecological landscapes and judge the changes in their landscape forms, and it is difficult to reasonably analyze the correlation between abnormal landscape form changes and the growth environment, which is not conducive to avoiding damage to natural ecological landscapes and the supervision is difficult.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] A distributed data monitoring platform for natural ecological landscapes includes a natural ecological landscape monitoring unit, a distributed storage unit, a landscape form analysis unit, a growth environment assessment unit, and a landscape management terminal; the natural ecological landscape monitoring unit forms a data acquisition network through various sensors deployed in the natural ecological landscape, is responsible for real-time collecting various index data of the ecological environment, and sends the collected data to the distributed storage unit for storage;

[0008] The landscape form analysis unit retrieves the monitoring images of the natural ecological landscape from the distributed storage unit, conducts landscape form analysis based on the monitoring images, and accordingly determines whether to generate a landscape form anomaly signal. When a landscape form anomaly signal is generated, it is sent to the landscape management terminal and the growth environment assessment unit;

[0009] When the growth environment assessment unit receives a landscape form anomaly signal, it judges the relevance between the natural ecological landscape anomaly and the growth environment through growth environment assessment and analysis, and accordingly generates a growth environment qualified signal or a growth environment anomaly signal. When a growth environment anomaly signal is generated, it is sent to the landscape management terminal; when the landscape management terminal receives a landscape form anomaly signal or a growth environment anomaly signal, it issues a warning.

[0010] Furthermore, the specific analysis process of landscape form analysis is as follows:

[0011] In the natural ecological landscape, several monitoring areas are delimited, and the corresponding monitoring areas are marked as layout object i, where i is a natural number greater than 1; based on the monitoring images, the distribution area of the plants in the withered state in layout object i is collected and the ratio of it to the total plant distribution area is marked as the withered distribution occupancy value. The withered distribution occupancy value is compared numerically with the preset withered distribution occupancy threshold. If the withered distribution occupancy value exceeds the preset withered distribution occupancy threshold, layout object i is marked as a form anomaly object;

[0012] The ratio of the number of form anomaly objects in the natural ecological landscape is obtained and marked as the form anomaly detection value. The form anomaly detection value is compared numerically with the preset form anomaly detection threshold. If the form anomaly detection value exceeds the preset form anomaly detection threshold, a landscape form anomaly signal is generated; if the form anomaly detection value does not exceed the preset form anomaly detection threshold, the average value of the withered distribution occupancy values of all monitoring areas is calculated to obtain the withered assessment value, and the withered distribution occupancy value with the largest value is marked as the withered peak value;

[0013] The landscape form change coefficient is calculated by weighted summation of the form anomaly detection value, the withered assessment value, and the withered peak value. The landscape form change coefficient is compared numerically with the preset landscape form change coefficient threshold. If the landscape form change coefficient exceeds the preset landscape form change coefficient threshold, a landscape form anomaly signal is generated.

[0014] Furthermore, the specific analysis process of growth environment assessment and analysis is as follows:

[0015] Set the detection period, collect the light duration, average light intensity, average atmospheric temperature, and average atmospheric humidity of the natural ecological landscape on the corresponding dates within the detection period. Mark the deviation value between the light duration and the corresponding preset light duration standard value as the light duration measurement value. Similarly, obtain the light intensity measurement value, atmospheric temperature measurement value, and atmospheric humidity measurement value. Calculate the upper-layer influence value by performing a weighted sum calculation on the light duration measurement value, light intensity measurement value, atmospheric temperature measurement value, and atmospheric humidity measurement value.

[0016] Compare the upper-layer influence value with the preset upper-layer influence threshold. If the upper-layer influence value exceeds the preset upper-layer influence threshold, mark the corresponding date as a landscape harmful day. If the upper-layer influence value does not exceed the preset upper-layer influence threshold, conduct soil damage detection and analysis to determine whether the corresponding date is a landscape harmful day.

[0017] Obtain the ratio of the number of landscape harmful days within the detection period and mark it as the harmful day detection value. Compare the harmful day detection value with the preset harmful day detection threshold. If the harmful day detection value exceeds the preset harmful day detection threshold, generate a growth environment anomaly signal.

[0018] Furthermore, the specific analysis process of soil damage detection and analysis is as follows:

[0019] Obtain the toxic substances and fertility substances to be monitored in the soil of the natural ecological landscape, collect the concentrations of various toxic substances and fertility substances, multiply the concentrations of various toxic substances by the corresponding preset hazard weight values respectively, and sum up the results of each group of products to obtain the soil toxicity coefficient. Similarly, obtain the soil fertility coefficient through calculation. Compare the soil toxicity coefficient and soil fertility coefficient with the preset soil toxicity coefficient threshold and preset soil fertility coefficient threshold respectively. If the soil toxicity coefficient exceeds the preset soil toxicity coefficient threshold or the soil fertility coefficient does not exceed the preset soil fertility coefficient threshold, mark the corresponding date as a landscape harmful day.

[0020] If the soil toxicity coefficient does not exceed the preset soil toxicity coefficient threshold and the soil fertility coefficient exceeds the preset soil fertility coefficient threshold, mark the deviation value of the soil temperature from the set standard temperature as the soil temperature characteristic value. Similarly, obtain the soil humidity characteristic value. Calculate the lower-layer influence value by performing a numerical calculation on the soil toxicity coefficient, soil fertility coefficient, soil temperature characteristic value, and soil humidity characteristic value. Compare the lower-layer influence value with the preset lower-layer influence threshold. If the lower-layer influence value exceeds the preset lower-layer influence threshold, mark the corresponding date as a landscape harmful day.

[0021] Further, the landscape management terminal is communicatively connected to the fire risk prediction and alarm unit and the behavior risk monitoring unit. The fire risk prediction and alarm unit analyzes the fire risk in the natural ecological landscape, determines whether to generate a fire risk alarm signal through the analysis, and sends it to the landscape management terminal when the fire risk alarm signal is generated. The landscape management terminal issues a warning when it receives the fire risk alarm signal;

[0022] The behavior risk monitoring unit monitors and analyzes the people entering the natural ecological landscape based on the monitoring images in the natural ecological landscape, determines whether to generate a behavior alarm signal through the analysis, and sends it to the landscape management terminal when the behavior alarm signal is generated. The landscape management terminal issues a warning when it receives the behavior alarm signal.

[0023] Further, the specific analysis process of the fire risk prediction and alarm unit is as follows:

[0024] Collect the temperature of the external environment where the natural ecological landscape is located and mark it as the external temperature detection value T, and collect the humidity of the external environment where the natural ecological landscape is located. Calculate the ratio of the value a to the humidity of the external environment where the natural ecological landscape is located to obtain the external humidity detection value H, and collect the wind speed of the external environment where the natural landscape is located and mark it as the external wind detection value W;

[0025] Calculate through the formula FWI = 0.5T + 0.3H + 0.2W and substitute the above data. Accordingly, obtain the fire risk alarm coefficient FWI; continuously compare the fire risk alarm coefficient in real time. If the fire risk alarm coefficient FWI is greater than 4.0 for three consecutive hours, generate a fire risk alarm signal.

[0026] Further, the specific analysis process of the behavior risk monitoring unit includes:

[0027] Obtain all types of bad behaviors that need to be monitored in the natural ecological landscape and mark them as excellent monitoring behaviors. Mark the corresponding excellent monitoring behaviors as k, and k is a natural number greater than 1; based on the monitoring images, continuously capture all excellent monitoring behaviors occurring in the natural ecological landscape. When an excellent monitoring behavior occurs in the natural ecological landscape, start timing. When the occurrence duration of the corresponding excellent monitoring behavior exceeds the corresponding preset occurrence duration threshold, generate a behavior alarm signal;

[0028] If there is no excellent monitoring behavior with an occurrence duration exceeding the corresponding preset occurrence duration threshold within a unit time, mark the occurrence frequency of the excellent monitoring behavior k within the unit time as the behavior frequency, and sum up the occurrence duration of each excellent monitoring behavior k within the unit time to obtain the behavior duration. Perform a weighted sum calculation on the behavior frequency and the behavior duration to obtain the behavior management difference value. Calculate the ratio of the behavior management difference value to the corresponding preset behavior management difference threshold. Accordingly, obtain the behavior management evaluation value;

[0029] If the behavior management evaluation value ≥ 1, mark the excellent monitoring behavior k as a strongly managed behavior; if there is a strongly managed behavior within a unit time, generate a behavior alarm signal.

[0030] Furthermore, if there is no strongly managed behavior within a unit time, preset a set of preset behavior hazard weight values for each type of excellent monitoring behavior respectively. Multiply the behavior management evaluation value of the excellent monitoring behavior k by the corresponding preset behavior hazard weight value to obtain a behavior risk detection value; sum up the behavior risk detection values of all types of excellent monitoring behaviors that occur within a unit time to obtain a total behavior risk value. Compare the total behavior risk value with a preset total behavior risk threshold value. If the total behavior risk value exceeds the preset total behavior risk threshold value, generate a behavior alarm signal.

[0031] Furthermore, if the total behavior risk value does not exceed the preset total behavior risk threshold value, obtain the real-time number of people existing in the natural ecological landscape and mark it as the measured value of personnel density. Compare the measured value of personnel density with a preset measured threshold value of personnel density. If the measured value of personnel density exceeds the preset measured threshold value of personnel density, it is determined that the natural ecological landscape is in an overloaded viewing state;

[0032] Obtain the total duration during which the natural ecological landscape is in an overloaded viewing state within a unit time and mark it as the overload detection value, and calculate the average value of all measured values of personnel density within a unit time to obtain a density evaluation value. Compare the overload detection value and the density evaluation value with a preset overload detection threshold value and a preset density evaluation threshold value respectively. If the overload detection value or the density evaluation value exceeds the corresponding preset threshold value, generate a behavior alarm signal.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. In the present invention, the natural ecological landscape monitoring unit comprehensively monitors the natural ecological landscape in real time. The landscape form analysis unit analyzes the landscape form to determine whether to generate a landscape form abnormal signal. When generating a landscape form abnormal signal, conduct a cause investigation and analysis and make reasonable improvement measures for the natural ecological landscape, and when generating a landscape form abnormal signal, judge the relevance between the natural ecological landscape abnormality and the growth environment through growth environment evaluation and analysis. When generating a growth environment abnormal signal, strengthen the monitoring and management of the environment where the natural ecological landscape is located, which is beneficial to avoiding damage to the natural ecological landscape and significantly reducing the supervision difficulty of the natural ecological landscape;

[0035] 2. In the present invention, the fire risk prediction and alarm unit analyzes the fire risk in the natural ecological landscape to determine whether to generate a fire risk alarm signal. When the fire risk alarm signal is generated, the fire monitoring and prevention are strengthened to avoid fires in the natural ecological landscape area. Moreover, the behavior risk monitoring unit monitors and analyzes the people entering the natural ecological landscape to determine whether to generate a behavior alarm signal. When the behavior alarm signal is generated, the management of the people's behavior in the natural ecological landscape is strengthened and the publicity of behavior norms is increased, further ensuring the safety of the natural ecological landscape and reducing its supervision difficulty, with a high level of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the accompanying drawings;

[0037] Figure 1 It is the system block diagram of the first embodiment in the present invention;

[0038] Figure 2 It is the system block diagram of the second and third embodiments in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0040] Embodiment 1: As Figure 1 shown, a distributed data monitoring platform for a natural ecological landscape proposed by the present invention includes a natural ecological landscape monitoring unit, a distributed storage unit, a landscape form analysis unit, a growth environment evaluation unit, and a landscape management terminal;

[0041] Among them, the natural ecological landscape monitoring unit forms a data acquisition network through various sensors (such as temperature and humidity sensors, soil humidity sensors, air quality sensors, water quality sensors, image sensors, etc.) deployed in the natural ecological landscape, is responsible for real-time collecting various index data of the ecological environment, and sends the collected various data to the distributed storage unit for storage;

[0042] It should be noted that the distributed storage unit uses distributed storage technology to disperse and store data on multiple nodes, realizing high availability, fault tolerance, and scalability of data, supporting the storage and management of massive data, and providing a basis for subsequent data analysis.

[0043] The landscape form analysis unit retrieves the monitoring images of the natural ecological landscape from the distributed storage unit, conducts landscape form analysis based on the monitoring images, and accordingly determines whether to generate a landscape form anomaly signal. When a landscape form anomaly signal is generated, it is sent to the landscape management terminal and the growth environment assessment unit;

[0044] When the landscape management terminal receives a landscape form anomaly signal, it issues a warning to remind the management staff to conduct a timely investigation and analysis of the reasons, make reasonable improvement measures for the natural ecological landscape, and strengthen the subsequent monitoring and management of the natural ecological landscape, significantly reducing the supervision difficulty of the natural ecological landscape. The specific analysis process of the landscape form analysis is as follows:

[0045] In the natural ecological landscape, several monitoring areas are delimited, and the corresponding monitoring areas are marked as layout object i, where i is a natural number greater than 1. Based on the monitoring images, the distribution area of the plants in a withered state in layout object i is collected and the ratio of it to the total plant distribution area is marked as the withered distribution occupancy value;

[0046] The withered distribution occupancy value is compared numerically with the preset withered distribution occupancy threshold. If the withered distribution occupancy value exceeds the preset withered distribution occupancy threshold, it indicates that the growth condition of the plants in layout object i is poor, and then layout object i is marked as a form-anomaly object;

[0047] The ratio of the number of form-anomaly objects in the natural ecological landscape is obtained and marked as the form-anomaly detection value. The form-anomaly detection value is compared numerically with the preset form-anomaly detection threshold. If the form-anomaly detection value exceeds the preset form-anomaly detection threshold, it indicates that the growth condition of the plants in the natural ecological landscape is poor, and then a landscape form anomaly signal is generated; if the form-anomaly detection value does not exceed the preset form-anomaly detection threshold, the withered distribution occupancy values of all monitoring areas are averaged to obtain the withered assessment value, and the withered distribution occupancy value with the largest numerical value is marked as the withered amplitude value;

[0048] The landscape form change coefficient is calculated by weighted summation of the form-anomaly detection value, the withered assessment value, and the withered amplitude value, that is, corresponding preset weight coefficients are assigned to the form-anomaly detection value, the withered assessment value, and the withered amplitude value respectively, the form-anomaly detection value, the withered assessment value, and the withered amplitude value are multiplied by the corresponding preset weight coefficients respectively, and the sum value of the three groups of product results is marked as the landscape form change coefficient. Moreover, the larger the numerical value of the landscape form change coefficient, the worse the comprehensive growth condition of the plants in the natural ecological landscape;

[0049] The landscape form change coefficient is compared numerically with the preset landscape form change coefficient threshold. If the landscape form change coefficient exceeds the preset landscape form change coefficient threshold, it indicates that the comprehensive growth condition of the plants in the natural ecological landscape is poor, and then a landscape form anomaly signal is generated.

[0050] When the growth environment assessment unit receives the landscape form anomaly signal, it judges the relevance between the natural ecological landscape anomaly and the growth environment through growth environment assessment and analysis, and accordingly generates a growth environment qualified signal or a growth environment anomaly signal. When the growth environment anomaly signal is generated, it is sent to the landscape management terminal;

[0051] When the landscape management terminal receives the growth environment anomaly signal, it issues a warning to remind the management staff that the probability of the poor form of the natural ecological landscape due to environmental factors is relatively high, so as to strengthen the monitoring and management of the environment where the natural ecological landscape is located in a timely manner in the follow-up, which is conducive to ensuring the good growth of plants in the natural ecological landscape. The specific analysis process of the growth environment assessment and analysis is as follows:

[0052] Set the detection period, collect the light duration, average light intensity, average atmospheric temperature and average atmospheric humidity of the natural ecological landscape on the corresponding date within the detection period, and mark the deviation value between the light duration and the corresponding preset light duration standard value as the light measurement value. Similarly, obtain the light intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value;

[0053] Calculate the upper layer influence value by weighted summation of the light measurement value, light intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value; that is, assign corresponding preset weight coefficients to the light measurement value, light intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value, multiply the light measurement value, light intensity measurement value, atmospheric temperature measurement value and atmospheric humidity measurement value by the corresponding preset weight coefficients respectively, and mark the sum value of the four groups of product results as the upper layer influence value; moreover, the larger the value of the upper layer influence value, the worse the comprehensive external atmospheric environment condition of the natural ecological landscape.

[0054] Compare the upper layer influence value with the preset upper layer influence threshold value. If the upper layer influence value exceeds the preset upper layer influence threshold value, it indicates that the comprehensive external atmospheric environment condition of the natural ecological landscape on the corresponding date is relatively poor, then mark the corresponding date as the landscape harmful day;

[0055] If the upper layer influence value does not exceed the preset upper layer influence threshold value, then obtain the toxic substances and fertility substances (such as substances related to nitrogen, phosphorus and potassium elements) that need to be monitored in the soil of the natural ecological landscape, collect the concentrations of various toxic substances and fertility substances, and preset a set of preset hazard weight values greater than zero for each toxic substance in advance. Moreover, the greater the harm caused by the corresponding toxic substance to plant growth, the greater the value of the preset hazard weight value matched with it; multiply the concentrations of various toxic substances by the corresponding preset hazard weight values respectively, and calculate the sum of the product results of each group to obtain the soil toxicity coefficient;

[0056] Similarly, the soil fertility coefficient is obtained through calculation; that is, a set of preset beneficial weight values greater than zero are preset for each fertility substance in advance, and the more important the corresponding fertility substance is for plant growth, the larger the value of the preset beneficial weight value matching it; the concentrations of various fertility substances are multiplied by the corresponding preset beneficial weight values respectively, and the sum of the results of each group of multiplications is calculated to obtain the soil fertility coefficient;

[0057] The soil toxicity coefficient and the soil fertility coefficient are numerically compared with the preset soil toxicity coefficient threshold and the preset soil fertility coefficient threshold respectively. If the soil toxicity coefficient exceeds the preset soil toxicity coefficient threshold or the soil fertility coefficient does not exceed the preset soil fertility coefficient threshold, it indicates that the soil condition on the corresponding date is poor and is not conducive to the growth of plants in the natural ecological landscape, then the corresponding date is marked as a landscape harmful day;

[0058] If the soil toxicity coefficient does not exceed the preset soil toxicity coefficient threshold and the soil fertility coefficient exceeds the preset soil fertility coefficient threshold, then the deviation value of the soil temperature compared with the set standard temperature is marked as the soil temperature characteristic value, and similarly, the soil moisture characteristic value is obtained;

[0059] The soil toxicity coefficient Z, the soil fertility coefficient G, the soil temperature characteristic value N, and the soil moisture characteristic value P are numerically calculated through Yew = (c1×Z + c3×N + c4×P) / (c2×G + 1) to obtain the lower-layer influence value Yew; where c1, c2, c3, and c4 are preset proportionality coefficients greater than zero, and moreover, the larger the value of the lower-layer influence value Yew, the worse the comprehensive soil condition on the corresponding date and the more unfavorable it is to the growth of plants in the natural ecological landscape;

[0060] The above formula is dimensionless and takes its numerical calculation. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the real situation. The preset parameters in the formula are set by technicians in the field according to the actual situation;

[0061] The lower-layer influence value Yew is numerically compared with the preset lower-layer influence threshold. If the lower-layer influence value Yew exceeds the preset lower-layer influence threshold, it indicates that the comprehensive soil condition on the corresponding date is poor and is not conducive to the growth of plants in the natural ecological landscape, then the corresponding date is marked as a landscape harmful day;

[0062] The ratio of the number of landscape harmful days in the detection period is obtained and marked as the harmful day detection value. The harmful day detection value is numerically compared with the preset harmful day detection threshold. If the harmful day detection value exceeds the preset harmful day detection threshold, it indicates that the environmental condition of the environment where the natural ecological landscape is located is poor, and the probability of the poor form of the natural ecological landscape due to environmental factors is relatively large. It is necessary to strengthen the monitoring and management of the environment where the natural ecological landscape is located in the follow-up, which is beneficial to ensuring the good growth of plants in the natural ecological landscape, then a growth environment abnormal signal is generated.

[0063] Example 2: As Figure 2 shown, the difference between this embodiment and Embodiment 1 is that the landscape management terminal is communicatively connected to the fire risk prediction and alarm unit. The fire risk prediction and alarm unit analyzes the fire risk in the natural ecological landscape, determines whether to generate a fire risk alarm signal through the analysis, and sends it to the landscape management terminal when the fire risk alarm signal is generated. When the landscape management terminal receives the fire risk alarm signal, it issues a warning to remind the management personnel to strengthen the fire monitoring and prevention, avoid fires in the natural ecological landscape area, and help ensure the safety of the natural ecological landscape. The specific analysis process of the fire risk prediction and alarm unit is as follows:

[0064] Collect the temperature of the external environment where the natural ecological landscape is located and mark it as the external temperature detection value T, and collect the humidity of the external environment where the natural ecological landscape is located. Calculate the ratio of the value a (where a represents the determination value of the external environment humidity and the value of a is greater than 1) to the humidity of the external environment where the natural ecological landscape is located to obtain the external humidity detection value H, and collect the wind speed of the external environment where the natural landscape is located and mark it as the external wind detection value W;

[0065] Calculate using the formula FWI = 0.5T + 0.3H + 0.2W and substitute the above data to obtain the fire risk alarm coefficient FWI; Compare the fire risk alarm coefficient in real time. If the fire risk alarm coefficient FWI is greater than 4.0 for three consecutive hours, a fire risk alarm signal is generated.

[0066] Example 3: As Figure 2 shown, the differences between this embodiment and Embodiment 1 and Embodiment 2 are that the landscape management terminal is communicatively connected to the behavior risk monitoring unit. The behavior risk monitoring unit monitors and analyzes the personnel entering the natural ecological landscape based on the monitoring images in the natural ecological landscape, determines whether to generate a behavior alarm signal through the analysis, and sends it to the landscape management terminal when the behavior alarm signal is generated. When the landscape management terminal receives the behavior alarm signal, it issues a warning to remind the management personnel to strengthen the management of the personnel behavior in the natural ecological landscape and increase the publicity of behavior norms, further ensure the safety of the natural ecological landscape and reduce its supervision difficulty, with a high level of intelligence. The specific analysis process of the behavior risk monitoring unit is as follows:

[0067] Obtain all types of bad behaviors that need to be monitored in the natural ecological landscape (such as trampling on and kicking plants in the natural ecological landscape, etc.) and mark them as excellent monitoring behaviors, mark the corresponding excellent monitoring behaviors as k, and k is a natural number greater than 1; Based on the monitoring images, continuously capture all excellent monitoring behaviors occurring in the natural ecological landscape. When an excellent monitoring behavior occurs in the natural ecological landscape, start timing. When the occurrence duration of the corresponding excellent monitoring behavior exceeds the corresponding preset occurrence duration threshold, a behavior alarm signal is generated;

[0068] If there is no excellent monitoring behavior with a duration exceeding the corresponding preset duration threshold within a unit time, the occurrence frequency of the excellent monitoring behavior k within the unit time is marked as the behavior frequency, and the occurrence duration of each occurrence of the excellent monitoring behavior k within the unit time is summed up to obtain the behavior duration. The behavior frequency and the behavior duration are weighted and summed up to obtain the behavior management difference value, that is, corresponding preset weight coefficients are assigned to the behavior frequency and the behavior duration respectively, the behavior frequency and the behavior duration are multiplied by the corresponding preset weight coefficients respectively, and the sum value of the two groups of product results is marked as the behavior management difference value; moreover, the larger the value of the behavior management difference value, the more it indicates that the control of the corresponding excellent monitoring behavior needs to be strengthened;

[0069] The behavior management difference value is calculated by taking the ratio with the corresponding preset behavior management difference threshold to obtain the behavior management evaluation value; if the behavior management evaluation value ≥ 1, it indicates that the control of the corresponding excellent monitoring behavior is not good, then the excellent monitoring behavior k is marked as a strongly managed behavior; if there is a strongly managed behavior within a unit time, it indicates that the personnel behavior supervision in the natural ecological landscape area needs to be strengthened, and then a behavior alarm signal is generated;

[0070] If there is no strongly managed behavior within a unit time, a set of preset behavior hazard weight values greater than zero is set in advance for each type of excellent monitoring behavior (the higher the potential risk brought by the excellent monitoring behavior k to the natural ecological landscape, the larger the value of the corresponding preset behavior hazard weight value). The behavior management evaluation value of the excellent monitoring behavior k is multiplied by the corresponding preset behavior hazard weight value to obtain the behavior risk detection value;

[0071] The behavior risk detection values of all types of excellent monitoring behaviors occurring within a unit time are summed up to obtain the total behavior risk value. The total behavior risk value is numerically compared with the preset total behavior risk threshold. If the total behavior risk value exceeds the preset total behavior risk threshold, it indicates that the personnel behavior supervision in the natural ecological landscape area needs to be strengthened, and then a behavior alarm signal is generated.

[0072] Furthermore, if the total behavior risk value does not exceed the preset total behavior risk threshold, the real-time number of personnel existing in the natural ecological landscape is obtained and marked as the measured personnel density value. The measured personnel density value is numerically compared with the preset measured personnel density threshold. If the measured personnel density value exceeds the preset measured personnel density threshold, it indicates that the personnel in the natural ecological landscape area are relatively crowded and are likely to cause damage to the natural ecological landscape, then it is judged that the natural ecological landscape is in an overloaded viewing state;

[0073] Obtain the total duration of the natural ecological landscape being in an over - viewing overload state within a unit time and mark it as the overload detection value, and calculate the average value of all measured personnel density values within the unit time to obtain the density evaluation value. Numerically compare the overload detection value and the density evaluation value with the preset overload detection threshold and the preset density evaluation threshold respectively. If the overload detection value or the density evaluation value exceeds the corresponding preset threshold, indicating that the personnel management of the natural ecological landscape area needs to be strengthened, then generate a behavior alarm signal.

[0074] The working principle of the present invention: When in use, the natural ecological landscape monitoring unit collects various index data of the ecological environment in real - time and sends them to the distributed storage unit for storage, providing a basis for subsequent data analysis. The landscape form analysis unit conducts landscape form analysis based on the monitoring images, thereby judging whether to generate a landscape form abnormal signal. When a landscape form abnormal signal is generated, conduct cause investigation and analysis and make reasonable improvement measures for the natural ecological landscape. And when a landscape form abnormal signal is generated, conduct growth environment evaluation and analysis through the growth environment evaluation unit to judge the relevance between the natural ecological landscape abnormality and the growth environment. When a growth environment abnormal signal is generated, strengthen the monitoring and management of the environment where the natural ecological landscape is located, which is beneficial to ensuring the good growth of plants in the natural ecological landscape, significantly reducing the supervision difficulty of the natural ecological landscape, and having a high level of intelligence.

[0075] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not elaborate on all details and do not limit the invention to only the specific implementation manners. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the relevant technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A distributed data monitoring platform for natural ecological landscapes, characterized in that, It includes a natural ecological landscape monitoring unit, a distributed storage unit, a landscape morphology analysis unit, a growth environment assessment unit, and a landscape management terminal; the natural ecological landscape monitoring unit collects various index data of the ecological environment in real time and sends the collected data to the distributed storage unit for storage; the landscape morphology analysis unit conducts landscape morphology analysis based on the monitoring images from the distributed storage unit and sends the generated landscape morphology abnormal signals to the landscape management terminal and the growth environment assessment unit when they are generated. When the growth environment assessment unit receives the landscape morphology abnormal signal, it judges the relevance between the natural ecological landscape abnormality and the growth environment through growth environment assessment analysis, and accordingly generates a growth environment qualified signal or a growth environment abnormal signal, and sends the growth environment abnormal signal to the landscape management terminal when it is generated; when the landscape management terminal receives the landscape morphology abnormal signal or the growth environment abnormal signal, it issues a warning. The landscape management terminal is communicatively connected to a fire risk prediction and alarm unit and a behavior risk monitoring unit. The fire risk prediction and alarm unit analyzes the fire risk in the natural ecological landscape, judges whether to generate a fire risk alarm signal through analysis, and sends the fire risk alarm signal to the landscape management terminal when it is generated. The landscape management terminal issues a warning when it receives the fire risk alarm signal. The behavior risk monitoring unit monitors and analyzes the personnel entering the natural ecological landscape based on the monitoring images in the natural ecological landscape, judges whether to generate a behavior alarm signal through analysis, and sends the behavior alarm signal to the landscape management terminal when it is generated. The landscape management terminal issues a warning when it receives the behavior alarm signal. The specific analysis process of the fire risk prediction and alarm unit is as follows: The temperature of the external environment where the natural ecological landscape is located is collected and marked as the external temperature detection value T, and the humidity of the external environment where the natural ecological landscape is located is collected. The ratio of the value a to the humidity of the external environment where the natural ecological landscape is located is calculated to obtain the external humidity detection value H, where a represents the determination value of the external environment humidity and the value of a is greater than 1; and the wind speed of the external environment where the natural landscape is located is collected and marked as the external wind detection value W. The fire risk alarm coefficient FWI is obtained by calculating using the formula FWI = 0.5T + 0.3H + 0.2W and substituting the above data; the comparison of the fire risk alarm coefficient is carried out in real time. If the fire risk alarm coefficient FWI is greater than 4.0 for three consecutive hours, a fire risk alarm signal is generated. The specific analysis process of the behavior risk monitoring unit includes: All types of bad behaviors that need to be monitored in the natural ecological landscape are obtained and marked as excellent monitoring behaviors, and the corresponding excellent monitoring behaviors are marked as k, and k is a natural number greater than 1; all excellent monitoring behaviors occurring in the natural ecological landscape are captured in real time based on the monitoring images. When an excellent monitoring behavior is identified in the natural ecological landscape, timing is started. When the occurrence duration of the corresponding excellent monitoring behavior exceeds the corresponding preset occurrence duration threshold, a behavior alarm signal is generated. If there is no excellent monitoring behavior with a duration exceeding the corresponding preset duration threshold within a unit time, the occurrence frequency of the excellent monitoring behavior k within the unit time is marked as the behavior frequency, and the occurrence duration of each occurrence of the excellent monitoring behavior k within the unit time is summed up to obtain the behavior duration. The behavior frequency and the behavior duration are weighted and summed up to obtain the behavior management difference value. The behavior management difference value is calculated as a ratio with the corresponding preset behavior management difference threshold, and based on this, the behavior management evaluation value is obtained; If the behavior management evaluation value ≥ 1, the excellent monitoring behavior k is marked as a strongly managed behavior; if there is a strongly managed behavior within a unit time, a behavior alarm signal is generated; If there is no strongly managed behavior within a unit time, a set of preset behavior hazard weight values is set for each type of excellent monitoring behavior in advance. The behavior management evaluation value of the excellent monitoring behavior k is multiplied by the corresponding preset behavior hazard weight value, and based on this, the behavior risk detection value is obtained; the behavior risk detection values of all types of excellent monitoring behaviors occurring within the unit time are summed up to obtain the total behavior risk value. The total behavior risk value is numerically compared with the preset total behavior risk threshold. If the total behavior risk value exceeds the preset total behavior risk threshold, a behavior alarm signal is generated; If the total behavior risk value does not exceed the preset total behavior risk threshold, the real-time number of people existing in the natural ecological landscape is obtained and marked as the measured value of the personnel density. The measured value of the personnel density is numerically compared with the preset measured threshold of the personnel density. If the measured value of the personnel density exceeds the preset measured threshold of the personnel density, it is determined that the natural ecological landscape is in an overloaded viewing state; The total duration during which the natural ecological landscape is in an overloaded viewing state within a unit time is obtained and marked as the overload detection value, and the average value of all the measured values of the personnel density within the unit time is calculated to obtain the density evaluation value. The overload detection value and the density evaluation value are numerically compared with the preset overload detection threshold and the preset density evaluation threshold respectively. If the overload detection value or the density evaluation value exceeds the corresponding preset threshold, a behavior alarm signal is generated; The specific analysis process of the landscape form analysis is as follows: Several monitoring areas are delimited in the natural ecological landscape, and the corresponding monitoring areas are marked as layout object i, where i is a natural number greater than 1; based on the monitoring images, the distribution area of the plants in a withered state in the layout object i is collected and the ratio of it to the total plant distribution area is marked as the withered distribution occupancy value. The withered distribution occupancy value is numerically compared with the preset withered distribution occupancy threshold. If the withered distribution occupancy value exceeds the preset withered distribution occupancy threshold, the layout object i is marked as a form-different object; The ratio of the number of form-different objects in the natural ecological landscape is obtained and marked as the form-different detection value. The form-different detection value is numerically compared with the preset form-different detection threshold. If the form-different detection value exceeds the preset form-different detection threshold, a landscape form anomaly signal is generated; if the form-different detection value does not exceed the preset form-different detection threshold, the average value of the withered distribution occupancy values of all the monitoring areas is calculated to obtain the withered evaluation value, and the withered distribution occupancy value with the largest numerical value is marked as the withered representation value; The landscape form change coefficient is calculated by weighted summation of the form difference detection value, the withering evaluation value, and the withering table amplitude value. The landscape form change coefficient is numerically compared with the preset landscape form change coefficient threshold. If the landscape form change coefficient exceeds the preset landscape form change coefficient threshold, a landscape form anomaly signal is generated; The specific analysis process of the growth environment assessment and analysis is as follows: Set the detection period. The light duration, average light intensity, average atmospheric temperature, and average atmospheric humidity of the natural ecological landscape on the corresponding dates within the detection period are collected. The deviation value of the light duration from the corresponding preset light duration standard value is marked as the light time measurement value. Similarly, the light intensity measurement value, atmospheric temperature measurement value, and atmospheric humidity measurement value are obtained. The upper layer influence value is calculated by weighted summation of the light time measurement value, light intensity measurement value, atmospheric temperature measurement value, and atmospheric humidity measurement value; The upper layer influence value is numerically compared with the preset upper layer influence threshold. If the upper layer influence value exceeds the preset upper layer influence threshold, the corresponding date is marked as a landscape harmful day. If the upper layer influence value does not exceed the preset upper layer influence threshold, soil damage detection and analysis are performed to determine whether the corresponding date is a landscape harmful day; The ratio of the number of landscape harmful days within the detection period is obtained and marked as the harmful day detection value. The harmful day detection value is numerically compared with the preset harmful day detection threshold. If the harmful day detection value exceeds the preset harmful day detection threshold, a growth environment anomaly signal is generated; The specific analysis process of the soil damage detection and analysis is as follows: The toxic substances and fertility substances to be monitored in the soil of the natural ecological landscape are obtained, and the concentrations of various toxic substances and fertility substances are collected. The concentrations of various toxic substances are respectively multiplied by the corresponding preset hazard weight values, and the sum of the product results of each group is calculated to obtain the soil toxicity coefficient. Similarly, the soil fertility coefficient is obtained through calculation; The soil toxicity coefficient and soil fertility coefficient are numerically compared with the preset soil toxicity coefficient threshold and preset soil fertility coefficient threshold respectively. If the soil toxicity coefficient exceeds the preset soil toxicity coefficient threshold or the soil fertility coefficient does not exceed the preset soil fertility coefficient threshold, the corresponding date is marked as a landscape harmful day; If the soil toxicity coefficient does not exceed the preset soil toxicity coefficient threshold and the soil fertility coefficient exceeds the preset soil fertility coefficient threshold, the deviation value of the soil temperature from the set standard temperature is marked as the soil temperature characteristic value. Similarly, the soil humidity characteristic value is obtained; The lower layer influence value is obtained through numerical calculation of the soil toxicity coefficient, soil fertility coefficient, soil temperature characteristic value, and soil humidity characteristic value. The lower layer influence value is numerically compared with the preset lower layer influence threshold. If the lower layer influence value exceeds the preset lower layer influence threshold, the corresponding date is marked as a landscape harmful day.

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