CN116295620A - Environment monitoring, collecting and detecting method - Google Patents
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- CN116295620A CN116295620A CN202310130172.XA CN202310130172A CN116295620A CN 116295620 A CN116295620 A CN 116295620A CN 202310130172 A CN202310130172 A CN 202310130172A CN 116295620 A CN116295620 A CN 116295620A
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- 230000002159 abnormal effect Effects 0.000 claims description 17
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Abstract
The invention discloses an environment monitoring, collecting and detecting method, which relates to the technical field of environment monitoring and comprises the following steps: s1, data acquisition: acquiring temperature, humidity and dust information in an indoor environment through a data acquisition module; s2, preprocessing data; s3, data detection: adopting an SVM algorithm; s4, constructing a Lagrange equation; s5, information display: providing the data information calculated in the step S3 and the step S4 for a user through an information display module, and controlling the indoor environment by the user through an equipment management module according to the data information displayed in the information display module; s6, monitoring and early warning; the special information detected by the data acquisition module is screened, so that the stability of data acquisition by the data acquisition module is ensured, the accuracy of indoor environment acquisition and detection is also ensured, a user can accurately judge the indoor environment, and the possibility of misjudgment is reduced.
Description
Technical Field
The invention relates to the technical field of environmental monitoring, in particular to an environmental monitoring, collecting and detecting method.
Background
The indoor environment monitoring can ensure that the indoor environment is in a proper environment, has great relation to people or objects in the indoor environment, can ensure that the indoor environment is in a proper temperature and humidity through the indoor environment monitoring, can monitor the concentration of particles such as dust in real time, ensures that the indoor environment is suitable for living, corresponds to different materials for objects in the indoor environment, adjusts different temperature and humidity, can prevent fire disaster, and can also increase the storage time of the materials;
the current acquisition and detection method adopted by environmental monitoring is to acquire data information such as temperature, humidity and dust particle concentration in the indoor environment directly through a temperature and humidity sensor and a dust sensor, and because the indoor environment has character activities or machines are operated, individual data information has larger errors, so that the acquisition of the indoor environment data is inaccurate, the data provided by acquisition and detection is inaccurate, and the judgment of background users is influenced.
Disclosure of Invention
In order to overcome the technical problems, the invention aims to provide the environment monitoring, collecting and detecting method, through which the data acquisition module can be prevented from transmitting ineffective temperature, humidity or data information of particle content in air to the information display module, and through data preprocessing and SVM algorithm, special information detected by the data acquisition module can be screened, so that the stability of data acquisition by the data acquisition module is ensured, the accuracy of indoor environment acquisition and detection is also ensured, a user can accurately judge the indoor environment, and the possibility of misjudgment is reduced.
The aim of the invention can be achieved by the following technical scheme:
an environmental monitoring, collecting and detecting method comprises the following steps:
s1, data acquisition: acquiring temperature, humidity and dust information in an indoor environment through a data acquisition module;
s2, data preprocessing: sample data x collected in S1 i Is S, the special sample data is S min ,S min E is S, k is S min The k elements of (a) are:
X new ＝x i +(x i -x j )；
wherein S is min ∈S；x j Is x i Is one of k neighbors of (a);
s3, numberAnd (3) detecting: using SVM algorithm, in sample data x i Adding misclassification cost co i Represents the ith sample x i Is based on the SVM algorithm to be brought into x i The following steps are:
s.t.y i (x i ·w+b)≥1-ξ i ，
ξ i ≥0，i＝1，...，n
wherein II w II 2 Representing model complexity, Σ, as structural cost n i＝1 co i ξ i At the cost of experience; c is a relaxation factor, and the balance between the control cost and the structure cost is controlled;
s4, constructing Lagrange equation:
wherein the method comprises the steps of
For Lagrange coefficients, minimizing them, find the dual form of the optimization problem, then there are:
s5, information display: providing the data information calculated in the step S3 and the step S4 for a user through an information display module, and controlling the indoor environment by the user through an equipment management module according to the data information displayed in the information display module;
s6, monitoring and early warning: real-time monitoring sample data x by monitoring and early warning module i 。
As a further scheme of the invention: the data acquisition module comprises an Arduino development board, a temperature and humidity sensor, a dust sensor and a fan module, wherein the Arduino development board controls the temperature and humidity sensor and the dust sensor.
As a further scheme of the invention: the equipment management module in the S5 is connected with a user management module, the user management module carries out user management, equipment management and exception handling, and specifically comprises user information management, user addition and deletion, and the user management module carries out environment data viewing, including real-time data and historical data.
As a further scheme of the invention: the device management module manages the devices in the data acquisition module, and comprises operation records and information statistics of the devices, monitoring points to which the devices belong, device names and model numbers.
As a further scheme of the invention: the information display module visually displays the data uploaded by the data acquisition module, and draws curves and charts.
As a further scheme of the invention: the monitoring and early warning module divides according to abnormal states of the collected data, and builds a feedback mechanism of system early warning according to each abnormal state.
As a further scheme of the invention: the monitoring and early warning module can detect abnormality including blocking, abnormal return value and abnormal floating, and monitors indoor environment temperature and presets a temperature threshold value by controlling the temperature and humidity sensor.
As a further scheme of the invention: the data acquisition modules are in a plurality of groups and are uniformly distributed in the indoor environment to form a plurality of monitoring points.
The invention has the beneficial effects that:
1. according to the invention, by the acquisition detection method, the data acquisition module can be prevented from transmitting the ineffective temperature, humidity or data information of the particle content in the air to the information display module, and special information detected by the data acquisition module can be screened by the data preprocessing and SVM algorithm, so that the stability of data acquisition by the data acquisition module is ensured, the accuracy of indoor environment acquisition detection is also ensured, a user can accurately judge the indoor environment, and the possibility of misjudgment is reduced.
2. According to the invention, through the information display module, the data uploaded by the data acquisition module are visually displayed, and are drawn into curves and charts, so that a user can conveniently and intuitively see the data display effect in real time, the user can see the air quality data, the temperature and humidity data and the fan switch state of each monitoring point when entering the system, the data can be displayed in an hour unit, wherein the data are transmitted in real time, the charts are continuously updated, the user can see the data change condition of the last 30 days, statistics display is carried out on the air quality data, the highest temperature, the lowest temperature, the highest humidity and the lowest humidity of each day, and a system administrator can additionally see the specific information of each monitoring point device.
3. According to the invention, the monitoring and early warning module carries out comprehensive analysis processing on the acquired data, divides the acquired data according to abnormal states of the acquired data, and carries out feedback mechanism construction of system early warning according to each abnormal state, so that the safety, accuracy and timeliness of the system are improved, the sensor state can be evaluated through data analysis in the process of acquiring the data in real time, and the accuracy and reliability of the subsequent data acquisition are ensured by using the feedback mechanism.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a block flow diagram of the modules of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, an environmental monitoring, collecting and detecting method includes the following steps:
s1, data acquisition: acquiring temperature, humidity and dust information in an indoor environment through a data acquisition module;
s2, data preprocessing: sample data x collected in S1 i Is S, the special sample data is S min ,S min E is S, k is S min The k elements of (a) are:
X new ＝x i +(x i -x j )；
wherein S is min ∈S；x j Is x i Is one of k neighbors of (a);
s3, data detection: using SVM algorithm, in sample data x i Adding misclassification cost co i Represents the ith sample x i Is based on the SVM algorithm to be brought into x i The following steps are:
s.t.y i (x i ·w+b)≥1-ξ i ，
ξ i ≥0，i＝1，...，n
wherein II w II 2 Representing model complexity, Σ, as structural cost n i＝1 co i ξ i At the cost of experience; c is a relaxation factor, and the balance between the control cost and the structure cost is controlled;
s4, constructing Lagrange equation:
wherein the method comprises the steps of
For Lagrange coefficient, minimize it, find the optimization questionThe problem of dual forms is that:
by the method, the data acquisition module can be prevented from transmitting the data information of invalid temperature, humidity or particle content in the air to the information display module, special information detected by the data acquisition module can be screened through data preprocessing and SVM algorithm, the stability of data acquisition by the data acquisition module is ensured, the accuracy of indoor environment acquisition and detection is also ensured, a user can accurately judge the indoor environment, and the possibility of misjudgment is reduced.
S5, information display: providing the data information calculated in the step S3 and the step S4 for a user through an information display module, and controlling the indoor environment by the user through an equipment management module according to the data information displayed in the information display module;
s6, monitoring and early warning: real-time monitoring sample data x by monitoring and early warning module i 。
The data acquisition module comprises an Arduino development board, a temperature and humidity sensor, a dust sensor and a fan module, wherein the Arduino development board controls the temperature and humidity sensor and the dust sensor, the temperature and humidity sensor adopts an AM2320 digital sensor, the AM2320 digital sensor is in a passive working mode, and the Arduino development board wakes the AM2320 digital sensor by sending an electric signal control instruction, then sends a target instruction and obtains a corresponding temperature and humidity value; after the communication of the two parties is finished, the sensor triggers one-time temperature and humidity acquisition, if the system does not read the sensor value for a long time, the second measured value is taken as the latest measured value, after the acquisition is finished, the AM2320 digital sensor is automatically set to be in a dormant state, and when the next Arduino development board needs to read the AM2320 digital sensor data again, an instruction needs to be sent again to wake up the AM2320 digital sensor;
the dust sensor adopts a GP2Y1051 dust sensor, the GP2Y1051 dust sensor is composed of an infrared light emitting diode (IRED) and a photoelectron transistor which are diagonally arranged, and the dust concentration is calculated by detecting dust reflection light in air.
The equipment management module in S5 is connected with a user management module, the user management module carries out user management, equipment management and exception handling, and specifically comprises user information management, user addition and deletion, the user management module carries out environment data viewing, and comprises real-time data and historical data, the user management module is divided into two operation authorities of a system manager and a common user, and the system manager has the highest operation authority of the whole system and can carry out user management, equipment management and exception handling, and specifically comprises user information management, user addition and deletion. The equipment management comprises information management of monitoring points and equipment, and addition and deletion can be performed to view environmental data, including real-time data and historical data;
the rights of the common user are data viewing rights and executive device control rights, the user is firstly registered in the system, and can see real-time data change and data history change conditions of the system after logging in the system, and control of corresponding executive devices can be carried out.
The equipment management module manages the equipment in the data acquisition module, and comprises operation records and information statistics of the equipment, monitoring points to which the equipment belongs, equipment names and models.
The information display module is used for visually displaying the data uploaded by the data acquisition module, specifically, the data are transmitted to a PC terminal or a mobile terminal device and drawn into curves and charts, so that a user can conveniently and intuitively see the data display effect in real time, the user can see the air quality data, the temperature and humidity data and the fan switch state of each monitoring point when entering the system, the data are displayed in an hour unit, the data are transmitted in real time, the charts are continuously updated, the user can see the data change condition of the last 30 days, statistics display is carried out on the air quality data, the highest temperature, the lowest temperature, the highest humidity and the lowest humidity of each day, and a system administrator can additionally see the specific information of each monitoring point device.
The monitoring and early warning module performs comprehensive analysis processing on the collected data, divides the collected data according to abnormal states, and builds a feedback mechanism of system early warning according to each abnormal state, so that the safety, accuracy and timeliness of the system are improved. And in the process of acquiring the subsequent data in real time, the sensor state can be evaluated through data analysis, and the accuracy and reliability of the subsequent data acquisition are ensured by using a feedback mechanism.
When the monitoring and early warning module evaluates that the sensor is abnormal, the system pops up corresponding abnormal information prompt, judges the abnormal type, reminds the corresponding abnormal type, and allows an administrator to carry out subsequent processing. The anomalies that the system can detect include types of stuck, return anomalies, abnormal floats, etc. In addition, the system also has a temperature monitoring function, the temperature control function is mainly realized through preset logic at the server side, a temperature threshold is preset, and when the temperature exceeds the threshold, the fan is started.
The data acquisition modules are in a plurality of groups and are uniformly distributed in the indoor environment to form a plurality of monitoring points.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (8)
1. The environment monitoring, collecting and detecting method is characterized by comprising the following steps:
s1, data acquisition: acquiring temperature, humidity and dust information in an indoor environment through a data acquisition module;
s2, data preprocessing: sample data x collected in S1 i Is S, the special sample data is S min ,S min E is S, k is S min The k elements of (a) are:
X new ＝x i +(x i -x j )；
wherein S is min ∈S；x j Is x i Is one of k neighbors of (a);
s3, data detection: using SVM algorithm, in sample data x i Adding misclassification cost co i Represents the ith sample x i Is based on the SVM algorithm to be brought into x i The following steps are:
s.t.y i (x i ·w+b)≥1-ξ i ，
ξ i ≥0，i＝1，...，n
wherein II w II 2 Representing model complexity, Σ, as structural cost n i＝1 co i ξ i At the cost of experience; c is a relaxation factor, and the balance between the control cost and the structure cost is controlled;
s4, constructing Lagrange equation:
wherein the method comprises the steps of
For Lagrange coefficients, minimizing them, find the dual form of the optimization problem, then there are:
s5, information display: providing the data information calculated in the step S3 and the step S4 for a user through an information display module, and controlling the indoor environment by the user through an equipment management module according to the data information displayed in the information display module;
s6, monitoring and early warning: real-time monitoring sample data x by monitoring and early warning module i 。
2. The method according to claim 1, wherein the data acquisition module comprises an Arduino development board, a temperature and humidity sensor, a dust sensor and a fan module, and the Arduino development board controls the temperature and humidity sensor and the dust sensor.
3. The method for detecting environmental monitoring and collecting according to claim 1, wherein the device management module in S5 is connected with a user management module, the user management module performs user management, device management and exception handling, specifically includes user information management, user addition and deletion, and the user management module performs environmental data viewing, including real-time data and history data.
4. The method for detecting environmental monitoring and collecting according to claim 1, wherein the device management module manages the devices in the data collection module, and includes operation records and information statistics of the devices, monitoring points to which the devices belong, device names and model numbers.
5. The method for detecting environmental monitoring and collecting according to claim 1, wherein the information display module visually displays the data uploaded by the data collection module, and draws the data into curves and charts.
6. The method according to claim 1, wherein the monitoring and early warning module divides the data according to abnormal states of the collected data, and builds a feedback mechanism of system early warning according to each abnormal state.
7. The method for detecting and collecting environmental monitoring according to claim 6, wherein the detectable anomalies of the monitoring and early warning module comprise a stuck condition, abnormal return values and abnormal floating, and the monitoring and early warning module monitors the indoor environmental temperature by controlling the temperature and humidity sensor and presets a temperature threshold.
8. The method for detecting and monitoring environment according to claim 1, wherein the data acquisition modules are in a plurality of groups and are uniformly distributed in an indoor environment to form a plurality of monitoring points.
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