Garden Carbon Emission Monitoring System Based on Multi-Source Sensors

Abstract

The present invention discloses a garden carbon emission monitoring system based on multi-source sensors, which relates to the technical field of carbon emission monitoring. It includes a monitoring center, a data acquisition module, a data processing module, a carbon emission calculation module, and a carbon emission supervision module. The data acquisition module selects several carbon emission monitoring points in the garden to arrange sensing and acquisition modules for collecting carbon emission-related data of each carbon emission monitoring point in the garden. The data processing module connects each sensing and acquisition module to the data processing network, and the data processing network performs data correction and communication transmission on the carbon emission-related data. The carbon emission calculation module receives all the carbon emission-related data for carbon emission calculation to obtain the dynamic carbon emission concentration of each carbon emission monitoring point. The carbon emission supervision module conducts data analysis based on the dynamic carbon emission concentration of each carbon emission monitoring point, warns the carbon emission monitoring points in abnormal carbon emission situations, and takes supervision measures for processing.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission monitoring, specifically a garden carbon emission monitoring system based on multi-source sensors. Background Art

[0002] Currently, the carbon emission monitoring technology for green spaces such as gardens or parks mainly relies on single sensors or simple monitoring systems. These technologies have the following limitations in practical applications:

[0003] Single layout of monitoring points: Existing technologies often only arrange a limited number of monitoring points in the garden, unable to comprehensively cover all areas of the garden, resulting in incomplete monitoring data.

[0004] Insufficient data accuracy: Due to the lack of an effective data correction mechanism, the data accuracy of existing monitoring systems is limited, affecting the reliability of monitoring results.

[0005] Weak early warning and supervision capabilities: Existing monitoring systems lack effective early warning and supervision mechanisms, and the handling of abnormal carbon emission situations is not timely, making it difficult to effectively control garden carbon emissions.

[0006] Therefore, it has become an urgent task to study a garden carbon emission monitoring system based on multi-source sensors. Summary of the Invention

[0007] In order to solve the above problems, the purpose of the present invention is to provide a garden carbon emission monitoring system based on multi-source sensors.

[0008] The purpose of the present invention can be achieved through the following technical solutions: A garden carbon emission monitoring system based on multi-source sensors, including a monitoring center, which is communicatively connected to a data acquisition module, a data processing module, a carbon emission calculation module, and a carbon emission supervision module;

[0009] The data acquisition module is used to select a number of carbon emission monitoring points in the garden, and arrange a sensing and acquisition module composed of a carbon dioxide sensor, a temperature sensor, a humidity sensor, and a light sensor at each carbon emission monitoring point, so as to collect carbon emission-related data at a number of carbon emission monitoring points in the garden;

[0010] The data processing module is used to connect a number of sensing and acquisition modules to a corresponding data processing network, and the data processing network performs data correction and communication transmission on the carbon emission-related data collected by the corresponding sensing and acquisition modules;

[0011] The carbon emission calculation module is used to receive all the carbon emission-related data communicated and transmitted by the data processing network, and perform carbon emission calculation based on all the carbon emission-related data, so as to obtain the dynamic carbon emission concentration at each carbon emission monitoring point;

[0012] The carbon emission supervision module is used to analyze data based on the dynamic carbon emission concentration of each carbon emission monitoring point, and then warn the carbon emission monitoring points in abnormal carbon emission situations, and take supervision measures to handle the abnormal carbon emission situations.

[0013] Further, the process of selecting several carbon emission monitoring points in the garden and arranging a sensing and acquisition module composed of a carbon dioxide sensor, a temperature sensor, a humidity sensor, and a light sensor at each carbon emission monitoring point to collect carbon emission-related data in the garden includes:

[0014] Number the several carbon emission monitoring points selected in the garden and record them as i, where i = 1, 2, 3,..., n, and n is a natural number greater than 0. Arrange different types of sensors at each carbon emission monitoring point, and judge whether there are abnormalities in the respective real-time operation parameters of different types of sensors;

[0015] If there is an abnormality, initialize the data of the sensor with the abnormality, and analyze whether the real-time operation parameters return to normal after the data initialization. If so, start the sensor to collect data. If not, arrange maintenance personnel to perform offline maintenance on the sensor with the abnormality;

[0016] If there is no abnormality, directly start the sensor, network all types of sensors under the same carbon emission monitoring point to the same local area network, and then form the corresponding sensing and acquisition module, and collect the carbon emission-related data of the corresponding carbon emission monitoring point through the sensing and acquisition module. The carbon emission-related data includes carbon dioxide concentration change data, temperature change data, humidity change data, and light change data.

[0017] Further, the process of connecting several sensing and acquisition modules to the corresponding data processing network includes:

[0018] Each sensing and acquisition module of each carbon emission monitoring point constructs its own data access request. Denote the data access request of the sensing and acquisition module corresponding to the carbon emission monitoring point numbered i as Request[i], and send the data access request of each sensing and acquisition module to the data processing network for review;

[0019] If the review is passed, establish a data access relationship between the corresponding sensing and acquisition module and the data processing network, and enter the carbon emission-related data of the corresponding carbon emission monitoring point collected by the sensing and acquisition module into the data processing network;

[0020] If the audit fails, mark the corresponding data access request as an illegal access request and prohibit the sensing acquisition module of the carbon emission monitoring point corresponding to the illegal access request from accessing the data processing network.

[0021] Further, the process of data correction and communication transmission of the carbon emission-related data collected by the corresponding sensing acquisition module by the data processing network includes:

[0022] After the data processing network receives the carbon emission-related data collected by the sensing acquisition modules corresponding to all carbon emission monitoring points, perform data correction on all the carbon emission-related data through the data processing network. After completing the data correction, encapsulate the carbon emission-related data of each carbon emission monitoring point into a preset blank data file, and then generate the corresponding file to be transmitted;

[0023] The data processing network performs data encryption and data compression on each file to be transmitted, and then converts each file to be transmitted into a corresponding encrypted file stream. Establish a number of communication channels between the data processing network and the carbon emission measurement module, and each communication channel is used for the communication transmission of an encrypted file stream.

[0024] Further, the process of receiving all the carbon emission-related data communicated and transmitted by the data processing network and performing carbon emission measurement based on all the carbon emission-related data to obtain the dynamic carbon emission concentration of each carbon emission monitoring point includes:

[0025] The carbon emission measurement module receives the encrypted file streams transmitted by several communication channels in the data processing network respectively, and performs data decompression and data decryption on all the encrypted file streams, and then restores the carbon emission-related data corresponding to each of the several carbon emission monitoring points in the garden;

[0026] Construct a carbon emission measurement model for performing carbon emission measurement on each of the several carbon emission monitoring points. The carbon emission measurement model consists of a measurement data input layer and a measurement result output layer;

[0027] Construct a temperature change regression function, a humidity change regression function, and a light intensity change regression function at each carbon emission monitoring point according to the temperature change data, humidity change data, and light intensity change data in the carbon emission-related data;

[0028] Construct a Cartesian coordinate system, and construct a carbon dioxide concentration change trend curve on the Cartesian coordinate system according to the carbon dioxide concentration change data;

[0029] After combining the temperature change regression function, the humidity change regression function, and the light intensity change regression function with the carbon dioxide concentration change trend curve in sequence, they are respectively input into the measurement data input layer. The measurement result output layer outputs the relevant data on the impacts of temperature change, humidity change, and light intensity change on carbon dioxide concentration change respectively, and labels them as the first measurement data, the second measurement data, and the third measurement data;

[0030] Set different weight coefficients for the first measurement data, the second measurement data, and the third measurement data that affect the carbon dioxide concentration change. Take the first measurement data, the second measurement data, the third measurement data, and the carbon dioxide concentration change data at each carbon emission monitoring point as the input data of the measurement data input layer of the carbon emission measurement model, and the measurement result output layer outputs the corresponding dynamic carbon emission concentration for each carbon emission monitoring point.

[0031] Furthermore, the process of analyzing the data based on the dynamic carbon emission concentration of each carbon emission monitoring point and then warning the carbon emission monitoring points in the abnormal carbon emission situation includes:

[0032] The dynamic carbon emission concentration of each carbon emission monitoring point is represented in the form of a line graph. The line graph is used to record the dynamic changes in carbon emission concentration at several time points, and set the critical emission threshold of carbon emission concentration;

[0033] Mark all time points with carbon emission concentration greater than or equal to the critical emission threshold as abnormal carbon emission nodes, and mark all time points with carbon emission concentration less than the critical emission threshold as normal carbon emission nodes. Set the abnormal determination threshold corresponding to whether the carbon emission monitoring point is in the abnormal carbon emission situation, and denote it as μ;

[0034] Denote the number of abnormal carbon emission nodes and normal carbon emission nodes at the carbon emission monitoring point as N 异常 and N 正常 , respectively. According to N 异常 and N 正常 obtain the abnormal point occupancy ratio, and denote the abnormal point occupancy ratio as Er. Then there is Er = N 异常 / (N 异常 +N 正常 );

[0035] When Er > μ, warn that the current carbon emission monitoring point is in the abnormal carbon emission situation;

[0036] When Er ≤ μ, it means that the current carbon emission monitoring point is in the normal carbon emission situation;

[0037] Warn all carbon emission monitoring points in the abnormal carbon emission situation, and label different warning levels for the carbon emission monitoring points in the abnormal carbon emission situation.

[0038] Further, the process of labeling different warning levels for the carbon emission monitoring points in the abnormal carbon emission situation includes:

[0039] Set different level intervals, including the first interval, the second interval, and the third interval, denoted as Ω1, Ω2, and Ω3 respectively;

[0040] When Er ∈ Ω1, label the warning level of the current carbon emission monitoring point as a yellow warning, indicating that the current carbon emission concentration is slightly abnormal;

[0041] When Er ∈ Ω2, label the warning level of the current carbon emission monitoring point as an orange warning, indicating that the current carbon emission concentration is moderately abnormal;

[0042] When Er ∈ Ω3, label the warning level of the current carbon emission monitoring point as a red warning, indicating that the current carbon emission concentration is severely abnormal.

[0043] Further, the process of taking regulatory measures to handle the abnormal carbon emission situation includes:

[0044] According to the warning level corresponding to the carbon emission monitoring point, set corresponding processing priorities for several carbon emission monitoring points. The processing priorities include the highest priority, the second highest priority, and the general priority. The specific correspondence between the warning level and the processing priority is as follows:

[0045] Yellow warning - general priority;

[0046] Orange warning - second highest priority;

[0047] Red warning - highest priority;

[0048] In the execution order of the highest priority, the second highest priority, and the general priority, take regulatory measures for each carbon emission monitoring point in turn. After implementing the corresponding regulatory measures, reduce the dynamic carbon emission concentration of the corresponding carbon emission monitoring point to the carbon emission concentration corresponding to the normal carbon emission situation.

[0049] Compared with the prior art, the beneficial effects of the present invention are:

[0050] 1. By selecting multiple carbon emission monitoring points in the garden to arrange the sensing and acquisition module, the comprehensive coverage acquisition of carbon emission-related data in the garden area is realized. Through the data processing network, data correction and communication transmission are carried out on the collected carbon emission-related data, improving the accuracy of the data and the stability of the transmission.

[0051] 2. Through the carbon emission measurement module and the carbon emission supervision module, real-time monitoring of the corresponding dynamic carbon emission concentration at each carbon emission monitoring point is achieved, improving the real-time nature of the monitoring. After analyzing the data of the dynamic carbon emission concentration, carbon emission monitoring points with abnormal carbon emission situations are promptly warned, and corresponding supervision measures are taken to handle the abnormal carbon emission situations, effectively controlling the carbon emissions of the entire garden. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0053] As Figure 1 shown, the garden carbon emission monitoring system based on multi-source sensors includes a monitoring center, and the monitoring center is communicatively connected with a data acquisition module, a data processing module, a carbon emission measurement module, and a carbon emission supervision module;

[0054] The data acquisition module is used to select several carbon emission monitoring points in the garden, and arrange a sensing and acquisition module composed of a carbon dioxide sensor, a temperature sensor, a humidity sensor, and a light sensor at each carbon emission monitoring point, so as to collect the carbon emission-related data of several carbon emission monitoring points in the garden;

[0055] The data processing module is used to connect several sensing and acquisition modules to the corresponding data processing network, and the data processing network performs data correction and communication transmission on the carbon emission-related data collected by the corresponding sensing and acquisition modules;

[0056] The carbon emission measurement module is used to receive all the carbon emission-related data communicatively transmitted by the data processing network, and perform carbon emission measurement based on all the carbon emission-related data, so as to obtain the dynamic carbon emission concentration of each carbon emission monitoring point;

[0057] The carbon emission supervision module is used to perform data analysis based on the dynamic carbon emission concentration of each carbon emission monitoring point, so as to warn the carbon emission monitoring points in the abnormal carbon emission situation, and take supervision measures to handle the abnormal carbon emission situation.

[0058] It should be further noted that in the specific implementation process, the process of selecting several carbon emission monitoring points in the garden and arranging a sensing and acquisition module composed of a carbon dioxide sensor, a temperature sensor, a humidity sensor, and a light sensor at each carbon emission monitoring point, and then collecting the carbon emission-related data of several carbon emission monitoring points in the garden includes:

[0059] Number several carbon emission monitoring points selected in the garden, and record the numbers as i, where i = 1, 2, 3, ……, n, and n is a natural number greater than 0. At each carbon emission monitoring point, different types of sensors are arranged. Different types of sensors include carbon dioxide sensors, temperature sensors, humidity sensors, and light sensors;

[0060] Judge whether there are any abnormalities in the real-time operation parameters of the carbon dioxide sensor, temperature sensor, humidity sensor, and light sensor respectively. If there are abnormalities, initialize the data of the sensors with abnormalities, and analyze whether the real-time operation parameters return to normal after data initialization. If so, start the sensors to collect data. If not, arrange maintenance personnel to perform offline maintenance on the sensors with abnormalities;

[0061] If there are no abnormalities, directly start the sensors with normal real-time operation parameters, and network all types of sensors at the same carbon emission monitoring point into the same local area network, and then form the corresponding sensing and acquisition module;

[0062] Among them, the carbon dioxide concentration change data, temperature change data, humidity change data, and light change data of the corresponding carbon emission monitoring points are collected through the carbon dioxide sensor, temperature sensor, humidity sensor, and light sensor respectively, and after integration, they are used as the carbon emission related data of the corresponding carbon emission monitoring points.

[0063] It should be further noted that in the specific implementation process, the process of connecting several sensing and acquisition modules to the corresponding data processing network includes:

[0064] Each sensing and acquisition module at each carbon emission monitoring point constructs its own corresponding data access request, and uses the number of its carbon emission monitoring point as the identity credential of the data processing request. Denote the data access request of the sensing and acquisition module corresponding to the carbon emission monitoring point numbered i as Request[i];

[0065] Send the data access request of each sensing and acquisition module to the data processing network. After being approved by the data processing network, establish the data access relationship between the corresponding sensing and acquisition module and the data processing network, and then input the carbon emission related data of the corresponding carbon emission monitoring point collected by the sensing and acquisition module into the data processing network;

[0066] Mark the data access requests that fail to pass the review by the data processing network as illegal access requests, and prohibit the sensing and acquisition modules corresponding to the illegal access requests from accessing the data processing network; for the sensing and acquisition modules whose data access requests fail to pass the review, set the corresponding error access upper limit value for their data access requests;

[0067] When the number of data access requests is less than or equal to the error access upper limit value, the sensing and acquisition module reconstructs the corresponding data access request and sends it, along with the collected carbon emission-related data, to the data processing network until the data processing network approves the data access request and allows the carbon emission-related data it carries to be entered into the data processing network;

[0068] When the number of data access requests is greater than the error access upper limit value, the number of the sensing and acquisition module that sent the data access request is included in the blacklist.

[0069] It should be further noted that in the specific implementation process, the process of the data processing network performing data correction and communication transmission on the carbon emission-related data collected by the corresponding sensing and acquisition module includes:

[0070] After the data processing network receives the carbon emission-related data collected by the sensing and acquisition modules corresponding to all carbon emission monitoring points, it performs data correction on all the carbon emission-related data through the data processing network. After completing the data correction, it encapsulates the carbon emission-related data of each carbon emission monitoring point into a preset blank data file, and then generates a corresponding file to be transmitted;

[0071] The content of the data correction includes: detecting and correcting the data belonging to the error type in the carbon emission-related data, where the error type includes spelling errors and format errors, identifying and processing outliers and missing values in the carbon emission-related data, correcting the outliers, supplementing the missing values, and applying a filtering algorithm to remove the noise information in the carbon emission-related data;

[0072] The data processing network encrypts and compresses each file to be transmitted, and then converts each file to be transmitted into a corresponding encrypted file stream. It establishes several communication channels between the data processing network and the carbon emission calculation module, and each communication channel is used for the communication transmission of an encrypted file stream;

[0073] When the encrypted file stream enters the communication channel, each encrypted file stream constructs an environmental monitoring task correspondingly, and obtains the control permission code of each environmental monitoring task and sends it to the monitoring center. The monitoring center monitors the real-time transmission environment of each encrypted file stream during communication transmission after it enters the communication channel. When it detects that the real-time transmission environment of the corresponding communication channel is abnormal, the monitoring center issues a warning, and the administrator responsible for the maintenance of the data processing network performs abnormal processing.

[0074] It should be further noted that in the specific implementation process, the process of receiving all the carbon emission-related data communicated and transmitted by the data processing network and performing carbon emission calculation based on all the carbon emission-related data, and then obtaining the dynamic carbon emission concentration of each carbon emission monitoring point includes:

[0075] The carbon emission measurement module receives the encrypted file streams transmitted by several communication channels in the data processing network, decompresses and decrypts all the encrypted file streams, and then restores the carbon emission-related data corresponding to several carbon emission monitoring points in the garden;

[0076] Perform carbon emission measurement based on the carbon emission-related data. The content of the carbon emission measurement is as follows:

[0077] Decompose the carbon emission-related data into carbon dioxide concentration change data, temperature change data, humidity change data, and light intensity change data;

[0078] The carbon dioxide concentration change data consists of the carbon dioxide concentrations corresponding to several time points, the temperature change data consists of the temperature values corresponding to several time points, the humidity change data consists of the humidity values corresponding to several time points, and the light intensity change data consists of the light intensity values corresponding to several time points;

[0079] Construct a carbon emission measurement model. The carbon emission measurement model is used to perform carbon emission measurement for several carbon emission monitoring points respectively. The carbon emission measurement model consists of a measurement data input layer and a measurement result output layer;

[0080] Construct a temperature change regression function for the temperature value at each carbon emission monitoring point changing with time; construct a humidity change regression function for the humidity value at each carbon emission monitoring point changing with time; construct a light intensity change regression function for the light intensity value at each carbon emission monitoring point changing with time;

[0081] Construct a Cartesian coordinate system. Take the several time points corresponding to the carbon dioxide concentration change data at each carbon emission monitoring point as the mapping elements on the abscissa, and take the carbon dioxide concentrations corresponding to the several time points respectively as the mapping elements on the ordinate. Then construct a carbon dioxide concentration change trend curve on the Cartesian coordinate system;

[0082] Input the temperature change regression function and the carbon dioxide concentration change trend curve into the measurement data input layer. The measurement result output layer outputs the influence-related data between the temperature change and the carbon dioxide concentration change, and labels it as the first measurement data;

[0083] Input the humidity change regression function and the carbon dioxide concentration change trend curve into the measurement data input layer. The measurement result output layer outputs the influence-related data between the humidity change and the carbon dioxide concentration change, and labels it as the second measurement data;

[0084] Input the light intensity change regression function and the carbon dioxide concentration change trend curve into the measurement data input layer. The measurement result output layer outputs the relevant data on the influence between the light intensity change and the carbon dioxide concentration change, and labels it as the third measurement data;

[0085] Set different weight coefficients that affect the carbon dioxide concentration change for the first measurement data, the second measurement data, and the third measurement data, and denote the respective weight coefficients of the first measurement data, the second measurement data, and the third measurement data as Qz1, Qz2, and 1 - Qz1 - Qz2;

[0086] Among them, 0 < Qz1 < 1, 0 < Qz2 < 1, 0 < 1 - Qz1 - Qz2 < 1;

[0087] The different weight coefficients are set by professionals in the actual application scenario according to the degree of influence of temperature change, humidity change, and ambient light intensity change on the carbon dioxide concentration change;

[0088] Take the first measurement data, the second measurement data, the third measurement data, and the carbon dioxide concentration change data at each carbon emission monitoring point as the input data of the corresponding measurement data input layer of the carbon emission measurement model, and then the measurement result output layer outputs the corresponding dynamic carbon emission concentration for each carbon emission monitoring point.

[0089] It should be further noted that in the specific implementation process, the process of analyzing the data according to the dynamic carbon emission concentration of each carbon emission monitoring point and then warning the carbon emission monitoring points in the abnormal carbon emission situation includes:

[0090] The dynamic carbon emission concentration corresponding to each carbon emission monitoring point is represented in the form of a line chart. The line chart is used to record the dynamic changes of the carbon emission concentration corresponding to several time points. Set the critical emission threshold of the carbon emission concentration. The critical emission threshold is the corresponding value of the maximum allowable carbon emission concentration when the carbon emission concentration is in the normal situation;

[0091] Mark all time points with a carbon emission concentration greater than or equal to the critical emission threshold as abnormal carbon emission nodes, mark all time points with a carbon emission concentration less than the critical emission threshold as normal carbon emission nodes, set an abnormal determination threshold corresponding to whether the carbon emission monitoring point is in the abnormal carbon emission situation, and denote the abnormal determination threshold as μ;

[0092] Taking a carbon emission monitoring point as an example, count the respective numbers of the carbon emission concentrations corresponding to several time points marked as abnormal carbon emission nodes and normal carbon emission nodes. Denote the number of abnormal carbon emission nodes as N 异常 and denote the number of normal carbon emission nodes as N 正常 ;

[0093] According to N 异常 and N 正常 Obtain the ratio of the number of abnormal points at each carbon emission monitoring point, and denote the ratio of the number of abnormal points as Er. Then Er = N 异常 / (N 异常 + N 正常 );

[0094] When Er > μ, it is warned that the current carbon emission monitoring point is in an abnormal carbon emission situation;

[0095] When Er ≤ μ, it means that the current carbon emission monitoring point is in a normal carbon emission situation;

[0096] Obtain the ratio of the number of abnormal points at each of several carbon emission monitoring points, and based on the numerical size relationship between the ratio of the number of abnormal points and the abnormal determination threshold, warn all the carbon emission monitoring points that are in an abnormal carbon emission situation.

[0097] Furthermore, different warning levels are marked for the carbon emission monitoring points in an abnormal carbon emission situation, specifically as follows:

[0098] Set different grade intervals, and the grade intervals include a first interval, a second interval, and a third interval, denoted as Ω1, Ω2, and Ω3 respectively;

[0099] When Er ∈ Ω1, mark the warning level of the current carbon emission monitoring point as a yellow warning, indicating that the current carbon emission concentration is slightly abnormal;

[0100] When Er ∈ Ω2, mark the warning level of the current carbon emission monitoring point as an orange warning, indicating that the current carbon emission concentration is moderately abnormal;

[0101] When Er ∈ Ω3, mark the warning level of the current carbon emission monitoring point as a red warning, indicating that the current carbon emission concentration is severely abnormal.

[0102] Among them, Ω1 = (μ, d1], Ω2 = (d1, d2], Ω3 = (d2, 1], 0 < μ < d1 < d2 < 1, and the values of d1 and d2 can be changed by the management personnel in the later stage according to the actual carbon emission monitoring situation.

[0103] It should be further noted that in the specific implementation process, the process of taking regulatory measures to deal with the abnormal carbon emission situation includes:

[0104] According to the warning level corresponding to the carbon emission monitoring point, set corresponding processing priorities for several carbon emission monitoring points. The processing priorities include the highest priority, the second highest priority, and the general priority. The specific correspondence between the warning level and the processing priority is as follows:

[0105] Yellow warning - general priority;

[0106] Orange warning - second highest priority;

[0107] Red warning - highest priority;

[0108] According to the execution order of the highest priority, the second highest priority, and the general priority, regulatory measures are taken for each carbon emission monitoring point in turn. After implementing the corresponding regulatory measures, the dynamic carbon emission concentration of the corresponding carbon emission monitoring point is reduced to the carbon emission concentration corresponding to the normal carbon emission situation;

[0109] The content of the above-mentioned regulatory measures includes the following:

[0110] Dispatch professional and technical personnel to investigate the carbon emission monitoring points in the abnormal carbon emission situation to evaluate the reasons for their abnormal carbon emissions, collect the meteorological condition data, vegetation condition data, and soil type data of the current carbon emission monitoring points, temporarily cover the vegetation near the current carbon emission monitoring points, and restrict tourists from entering the garden or reduce their activities in the garden to reduce carbon emissions;

[0111] Optimize the garden vegetation configuration, increase the types of plants with strong carbon sequestration ability, increase the organic matter content in the soil to improve the soil structure, use carbon capture and carbon sequestration technologies to reduce carbon emissions, install air purification devices or add green belts to absorb excess carbon emissions;

[0112] Carry out environmental renovation on the carbon emission monitoring points in the abnormal carbon emission situation, clean up the garbage and rotten plants at the corresponding carbon emission monitoring points in the garden, reduce the carbon emissions caused by the decomposition of organic matter, and repair the damaged vegetation.

[0113] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A garden carbon emission monitoring system based on multi-source sensors, including a monitoring center, characterized in that, The monitoring center is communicatively connected to a data acquisition module, a data processing module, a carbon emission calculation module, and a carbon emission supervision module; The data acquisition module is used to select several carbon emission monitoring points in the garden, and arrange a sensing and acquisition module composed of a carbon dioxide sensor, a temperature sensor, a humidity sensor, and a light sensor at each carbon emission monitoring point, so as to collect carbon emission-related data of several carbon emission monitoring points in the garden; The data processing module is used to connect several sensing and acquisition modules to the corresponding data processing network, and the data processing network performs data correction and communication transmission on the carbon emission-related data collected by the corresponding sensing and acquisition modules; The carbon emission calculation module is used to receive all the carbon emission-related data communicatively transmitted by the data processing network, and perform carbon emission calculation based on all the carbon emission-related data, so as to obtain the dynamic carbon emission concentration of each carbon emission monitoring point; The carbon emission supervision module is used to perform data analysis based on the dynamic carbon emission concentration of each carbon emission monitoring point, so as to warn the carbon emission monitoring points in the abnormal carbon emission situation, and take supervision measures to deal with the abnormal carbon emission situation; The process of selecting several carbon emission monitoring points in the garden and arranging a sensing and acquisition module composed of a carbon dioxide sensor, a temperature sensor, a humidity sensor, and a light sensor at each carbon emission monitoring point, and then collecting carbon emission-related data of several carbon emission monitoring points in the garden includes: Number the several carbon emission monitoring points selected in the garden, and denote them as i, i = 1, 2, 3, ……, n, where n is a natural number greater than 0. Arrange different types of sensors at each carbon emission monitoring point, and judge whether there are abnormalities in the respective real-time operation parameters of different types of sensors; If there are abnormalities, initialize the data of the sensors with abnormalities, and analyze whether the real-time operation parameters after data initialization return to normal. If so, start the sensors to collect data. If not, arrange maintenance personnel to perform offline maintenance on the sensors with abnormalities; If there are no abnormalities, directly start the sensors, network all types of sensors under the same carbon emission monitoring point to the same local area network, and then form the corresponding sensing and acquisition module, and collect carbon emission-related data of the corresponding carbon emission monitoring point through the sensing and acquisition module. The carbon emission-related data includes carbon dioxide concentration change data, temperature change data, humidity change data, and light change data.

2. The garden carbon emission monitoring system based on multi-source sensors according to claim 1, characterized in that, The process of connecting several sensing and acquisition modules to the corresponding data processing network includes: Each sensing and acquisition module of the carbon emission monitoring point constructs its own data access request. Denote the data access request of the sensing and acquisition module corresponding to the carbon emission monitoring point numbered i as Request[i], and send the data access request of each sensing and acquisition module to the data processing network for review; If the review is passed, establish a data access relationship between the corresponding sensing and acquisition module and the data processing network, and enter the carbon emission-related data of the corresponding carbon emission monitoring point collected by the sensing and acquisition module into the data processing network; If the audit fails, mark the corresponding data access request as an illegal access request, and prohibit the sensing and acquisition module of the carbon emission monitoring point corresponding to the illegal access request from accessing the data processing network.

3. The garden carbon emission monitoring system based on multi-source sensors according to claim 2, characterized in that, The process of data calibration and communication transmission of the carbon emission-related data collected by the corresponding sensing and acquisition module by the data processing network includes: After the data processing network receives the carbon emission-related data collected by the sensing and acquisition modules corresponding to all carbon emission monitoring points, the data processing network performs data calibration on all the carbon emission-related data. After completing the data calibration, encapsulate the carbon emission-related data of each carbon emission monitoring point into a preset blank data file, and then generate the corresponding file to be transmitted; The data processing network encrypts and compresses each file to be transmitted, and then converts each file to be transmitted into a corresponding encrypted file stream. Establish several communication channels between the data processing network and the carbon emission measurement module, and each communication channel is used for the communication transmission of an encrypted file stream.

4. The garden carbon emission monitoring system based on multi-source sensors according to claim 3, characterized in that The process of receiving all the carbon emission-related data communicated and transmitted by the data processing network and calculating the carbon emissions based on all the carbon emission-related data, and then obtaining the dynamic carbon emission concentration of each carbon emission monitoring point includes: The carbon emission measurement module receives the encrypted file streams transmitted by several communication channels in the data processing network, and decompresses and decrypts all the encrypted file streams, and then restores the carbon emission-related data corresponding to each of the several carbon emission monitoring points in the garden; Construct a carbon emission measurement model for measuring the carbon emissions of each of the several carbon emission monitoring points. The carbon emission measurement model consists of a measurement data input layer and a measurement result output layer; Construct a temperature change regression function, a humidity change regression function, and a light intensity change regression function at each carbon emission monitoring point based on the temperature change data, humidity change data, and light change data in the carbon emission-related data; Construct a Cartesian coordinate system, and construct a carbon dioxide concentration change trend curve on the Cartesian coordinate system based on the carbon dioxide concentration change data; After combining the temperature change regression function, the humidity change regression function, and the light intensity change regression function with the carbon dioxide concentration change trend curve in sequence, input them into the measurement data input layer respectively. The measurement result output layer outputs the influence-related data between the temperature change, humidity change, and light intensity change and the carbon dioxide concentration change respectively, and labels them as the first measurement data, the second measurement data, and the third measurement data respectively; Set different weight coefficients for the first measurement data, the second measurement data, and the third measurement data that affect the carbon dioxide concentration change. Use the first measurement data, the second measurement data, the third measurement data, and the carbon dioxide concentration change data at each carbon emission monitoring point as the input data of the measurement data input layer of the carbon emission measurement model, and the measurement result output layer outputs the corresponding dynamic carbon emission concentration of each carbon emission monitoring point.

5. The garden carbon emission monitoring system based on multi-source sensors according to claim 4, characterized in that, The process of data analysis based on the dynamic carbon emission concentration of each carbon emission monitoring point and then warning the carbon emission monitoring points in the abnormal carbon emission situation includes: The dynamic carbon emission concentration of each carbon emission monitoring point is represented in the form of a line chart, which is used to record the dynamic changes of the carbon emission concentration at several time points, and set the critical emission threshold of the carbon emission concentration; Mark all time points with carbon emission concentration greater than or equal to the critical emission threshold as abnormal carbon emission nodes, mark all time points with carbon emission concentration less than the critical emission threshold as normal carbon emission nodes, and set the abnormal determination threshold corresponding to whether the carbon emission monitoring point is in the abnormal carbon emission situation, denoted as μ; Denote the numbers of abnormal carbon emission nodes and normal carbon emission nodes respectively as N 异常 and N 正常 under the carbon emission monitoring points. Based on N 异常 and N 正常 , obtain the ratio of abnormal points, and denote the ratio of abnormal points as Er. Then Er = N 异常 / (N 异常 + N 正常 ); When Er > μ, it is warned that the current carbon emission monitoring point is in the abnormal carbon emission situation; When Er ≤ μ, it means that the current carbon emission monitoring point is in the normal carbon emission situation; Warn all carbon emission monitoring points in the abnormal carbon emission situation, and mark different warning levels for the carbon emission monitoring points in the abnormal carbon emission situation.

6. The garden carbon emission monitoring system based on multi-source sensors according to claim 5, characterized in that The process of marking different warning levels for the carbon emission monitoring points in the abnormal carbon emission situation includes: Set different grade intervals, which include the first interval, the second interval and the third interval, denoted as Ω1, Ω2 and Ω3 respectively; When Er ∈ Ω1, mark the warning level of the current carbon emission monitoring point as a yellow warning, indicating that the current carbon emission concentration is slightly abnormal; When Er ∈ Ω2, mark the warning level of the current carbon emission monitoring point as an orange warning, indicating that the current carbon emission concentration is moderately abnormal; When Er ∈ Ω3, mark the warning level of the current carbon emission monitoring point as a red warning, indicating that the current carbon emission concentration is severely abnormal.

7. The garden carbon emission monitoring system based on multi-source sensors according to claim 6, characterized in that, The process of taking supervision measures to deal with the abnormal carbon emission situation includes: According to the warning levels corresponding to the carbon emission monitoring points, set corresponding processing priorities for several carbon emission monitoring points. The processing priorities include the highest priority, the second highest priority and the general priority. The specific correspondence between the warning levels and the processing priorities is as follows: Yellow warning - general priority; Orange warning - second highest priority; Red warning - highest priority; According to the execution order of the highest priority, the second highest priority, and the general priority, take supervision measures for each carbon emission monitoring point in turn. After executing the corresponding supervision measures, reduce the dynamic carbon emission concentration of the corresponding carbon emission monitoring point to the carbon emission concentration corresponding to the normal carbon emission situation.

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