CN111006981A - Human body microenvironment air quality detection and prediction system based on intelligent mobile terminal - Google Patents

Human body microenvironment air quality detection and prediction system based on intelligent mobile terminal Download PDF

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Publication number
CN111006981A
CN111006981A CN201911217815.4A CN201911217815A CN111006981A CN 111006981 A CN111006981 A CN 111006981A CN 201911217815 A CN201911217815 A CN 201911217815A CN 111006981 A CN111006981 A CN 111006981A
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information
humidity
concentration
temperature
intelligent mobile
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王玲玲
富立
赵宇翔
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Beihang University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/06—Investigating concentration of particle suspensions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G—PHYSICS
    • G08—SIGNALLING
    • G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
    • G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
    • G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
    • H04M1/724—User interfaces specially adapted for cordless or mobile telephones
    • H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
    • H04M1/72409—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by interfacing with external accessories
    • H04M1/72412—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by interfacing with external accessories using two-way short-range wireless interfaces
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
    • Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters

Abstract

The invention discloses a human body microenvironment air quality detection and forecast system based on an intelligent mobile terminal, which is installed in the intelligent mobile terminal. The system consists of an information reading module, an information processing module and an air quality monitoring and forecasting module; the information reading module comprises temperature information, humidity information and PM2.5 concentration information which are acquired by an intelligent mobile terminal; the human body microenvironment information processed by the information processing module is displayed on a mobile phone screen, and meanwhile, the air quality in the subsequent time period is forecasted in the information normalization and monitoring forecasting module for the user to use. On the other hand, the human body microenvironment information obtained by the mobile phone user can be sent to relevant national departments, which is beneficial to making the best PM2.5 pollution control strategy and providing specific suggestions for people going out. By means of the smart phone, the atmosphere monitoring and forecasting method is more miniaturized and convenient to carry, and can detect the microenvironment of a human body at any time.

Description

Human body microenvironment air quality detection and prediction system based on intelligent mobile terminal
Technical Field
The invention relates to air quality detection and prediction in a human body microenvironment, in particular to an air quality detection and prediction system in a human body microenvironment, which operates on an intelligent mobile terminal.
Background
In recent years, air pollution is more and more serious, the influence of haze on the living environment of people is increased gradually, and the quality of the living environment is more and more poor. The main culprit is PM2.5, wherein PM2.5 refers to various suspended particulate matters with diameters less than or equal to 2.5 micrometers in the air, and the most direct method for treating PM2.5 is to treat PM2.5 around the microenvironment of a human body, so that the concentration, the temperature and the humidity of PM2.5 around the human body need to be detected, the quality of the living environment is deeply known, the haze can be resisted, and the living environment of people is protected.
At present, the method for detecting PM2.5 worldwide is mainly to establish a large-scale air quality detection station to detect the air pollution condition of an area or install some small-scale detection devices applied to public places such as markets, hospitals and the like. These detection devices simply read the data information of the air quality through the sensor.
In order to solve the problem of air quality detection and prediction under a single human body microenvironment, the invention designs an air quality detection and prediction system under a human body microenvironment, which operates on an intelligent mobile terminal.
Disclosure of Invention
The invention aims to design an air quality detection and forecast system under a human body microenvironment operating on an intelligent mobile terminal, and the system is installed in the intelligent mobile terminal (a smart phone). The system consists of an information reading module, an information processing module and an information normalization, monitoring and forecasting module; the information reading module comprises temperature information, humidity information and PM2.5 concentration information which are acquired by using a smart phone; the human body microenvironment information processed by the information processing module is displayed on a mobile phone screen, and meanwhile, the air quality in the subsequent time period is forecasted in the information normalization and monitoring forecasting module for the user to use. On the other hand, the human body microenvironment information obtained by the mobile phone user can be sent to relevant national departments, which is beneficial to making the best PM2.5 pollution control strategy and providing specific suggestions for people going out. By means of the smart phone, the atmosphere monitoring and forecasting method is more miniaturized and convenient to carry, and can detect the microenvironment of a human body at any time.
The invention relates to a human body microenvironment air quality detection and forecast system based on an intelligent mobile terminal, which is arranged in an intelligent mobile phone; the system consists of an information reading module, an information processing module and an information normalization, monitoring and forecasting module;
the information reading module comprises temperature information, humidity information and PM2.5 concentration information which are read by a smart phone; i.e. fGeneral assembly＝{XPM2.5,XTemperature of,XHumidity}，XTemperature ofTemperature information, X, for real-time readingHumidityHumidity information and X for real-time readingPM2.5PM2.5 concentration information is read in real time;
the information processing module is used for processing the fGeneral assembly＝{XPM2.5,XTemperature of,XHumidityReading in after delaying for 2 seconds, and recording the read PM2.5 concentration data frame as
Figure BDA0002299974050000021
Temperature data frame as
Figure BDA0002299974050000022
Humidity data frame as
Figure BDA0002299974050000023
While
Figure BDA0002299974050000024
And
Figure BDA0002299974050000025
combining the temperature information and the humidity information;
each group of the
Figure BDA0002299974050000026
Data comprising ten bytes; firstly, the header of a data frame and the mark information of successful receiving are received, and then PM2.5 concentration low byte and high byte signals are received successively; multiplying high byte information by 256 and adding low byte information, and then dividing by 10 to obtain the PM2.5 concentration value after each group of normalization;
each group of the temperature and humidity information data frames, wherein the first byte and the second byte respectively represent a high 8-bit byte signal and a low 8-bit byte signal of the humidity, and then the two bytes are combined to calculate a corresponding decimal number and divided by 10 to obtain the final humidity; the third byte and the fourth byte represent the upper 8-bit byte signals and the lower 8-bit byte signals of the temperature, then the two bytes are combined to calculate the corresponding decimal number, and the decimal number is divided by 10 to obtain the final temperature;
information normalization and monitoring and forecasting module and method
Figure BDA0002299974050000027
The normalized value is displayed on the screen of the smartphone as the PM2.5 concentration output value,
Figure BDA0002299974050000028
for the maximum value of the PM2.5 concentration data set read in real time,
Figure BDA0002299974050000029
is the minimum value of the PM2.5 concentration data set read in real time. In the same way, the temperature and humidity information can be normalized to obtain
Figure BDA00022999740500000210
The human body microenvironment air quality detection and forecast system based on the intelligent mobile terminal has the advantages that: the intelligent mobile phone based environment quality monitoring and forecasting device is convenient and fast equipment for monitoring and forecasting the ambient air environment quality of a human body by combining the intelligent mobile phone under the condition that the intelligent mobile phone is popularized.
Drawings
Fig. 1 is a flow chart of the human body microenvironment air quality detection and prediction system based on the intelligent mobile terminal.
Fig. 2 is an effect diagram of the human body microenvironment air quality detection and prediction system based on the intelligent mobile terminal.
The present invention will be described in further detail with reference to the accompanying drawings.
Referring to fig. 1, the system for detecting and forecasting the human body microenvironment air quality based on the intelligent mobile terminal is composed of an information reading module, an information processing module and an information normalization and monitoring forecasting module. The system is arranged on a smart phone carrier, and real-time preprocessing information f is read by the smart phoneGeneral assembly，fGeneral assembly＝{XPM2.5,XTemperature of,XHumidity}，XTemperature ofTemperature information, X, for real-time readingHumidityHumidity information and X for real-time readingPM2.5PM2.5 concentration information is read in real time; the preprocessing information fGeneral assemblyOr the data information collected by connecting an external temperature and humidity device and a PM2.5 concentration device through Bluetooth.
Preprocessing information f received by applying smart phoneGeneral assembly＝{XPM2.5,XTemperature of,XHumidityThe temperature information, humidity information and PM2.5 concentration information downloaded from a public network of a national institution may be used.
The information processing module is used for processing the fGeneral assembly＝{XPM2.5,XTemperature of,XHumidityReading in after delaying for 2 seconds, and recording the read PM2.5 concentration data frame as
Figure BDA0002299974050000031
Temperature data frame as
Figure BDA0002299974050000032
Humidity data frame as
Figure BDA0002299974050000033
While
Figure BDA0002299974050000034
And
Figure BDA0002299974050000035
the combination is temperature and humidity information.
Each group of the
Figure BDA0002299974050000036
Data comprising ten bytes; firstly, the header of a data frame and the mark information of successful receiving are received, and then PM2.5 concentration low byte and high byte signals are received successively; the high byte information is multiplied by 256 plus the low byte information and then divided by 10 to obtain the normalized PM2.5 concentration value for each group.
Each group of the temperature and humidity information data frames, wherein the first byte and the second byte respectively represent a high 8-bit byte signal and a low 8-bit byte signal of the humidity, and then the two bytes are combined to calculate a corresponding decimal number and divided by 10 to obtain the final humidity; the third and fourth bytes represent the upper 8-bit and lower 8-bit byte signals of the temperature, and then the two bytes are combined to calculate the corresponding decimal number, and the decimal number is divided by 10 to obtain the final temperature.
In the invention, the time delay of the read data information is to ensure the normal work of the data information, so that each connected external sensor can ensure the normal data acquisition after being started.
In the invention, after the information normalization and monitoring and forecasting module needs to delay for 100 seconds, PM2.5 concentration data are read and then stored, the PM2.5 concentration data are converted into a specific PM2.5 concentration value through data preprocessing, and the PM2.5 concentration data are displayed on a display screen of the smart phone; the data normalization processing of the PM2.5 concentration information is
Figure BDA0002299974050000037
Wherein
Figure BDA0002299974050000038
Is a normalized PM2.5 concentration value,
Figure BDA0002299974050000039
for the raw PM2.5 concentration data set,
Figure BDA00022999740500000310
at the maximum of the raw PM2.5 concentration data set,
Figure BDA00022999740500000311
is the minimum of the raw PM2.5 concentration data set. After the delay of 100 seconds, the temperature and humidity data and the PM2.5 concentration data are read and processed in a cycle of one time. And the data normalization processing process of the temperature and humidity information is the same as the data normalization processing of the PM2.5 concentration information.
In the invention, the information normalization and monitoring prediction module predicts the PM2.5 concentration data based on a Support Vector Regression (SVR) method. Compared with the huge data volume of tens of thousands to hundreds of thousands obtained by a large monitoring station, the PM2.5 concentration monitoring method has the advantages that the monitoring data volume obtained in a human body microenvironment is only hundreds of thousands of orders of magnitude of data in limited manual monitoring time, the data volume is small, and small sample sampling is not facilitated. The invention can obtain the global optimal solution by adopting the SVR method.
The forecasting method adopted by the invention is an SVR model, and normalized temperature and humidity data are converted through the non-linear transformation among PM2.5 concentration, temperature and humidity
Figure BDA0002299974050000041
And PM2.5 concentration data
Figure BDA0002299974050000042
As argument information x is mapped into the high-dimensional feature space.
The argument x can be reduced to a collective form consisting of a plurality of arguments, i.e., x1,x2,...,xi...,xm，x1Representing first argument information, x2Representing second argument information, xiI represents an identification number of the argument information; x is the number ofmRepresenting the last argument information, m representing the total number of argument information; for any one argument information xmAre made up of triplets, i.e. of
Figure BDA0002299974050000043
The upper corner mark T is a coordinate transpose symbol; wherein
Figure BDA0002299974050000044
Is normalized temperature data in the dimension of 1 x m,
Figure BDA0002299974050000045
is normalized humidity data in the 1 x m dimension,
Figure BDA0002299974050000046
the data is the PM2.5 concentration data normalized by the dimension of t multiplied by m, and t is the current sampling moment.
In the invention, for convenience of explaining the temperature and humidity and PM2.5 concentration information obtained at the real-time sampling moment, the previous moment positioned at the current sampling moment t is marked as a previous sampling moment t-1; the later moment under the current sampling moment t is recorded as a later sampling moment t + 1; the sampling information at the current sampling time t is recorded as xi(i.e., current sampling information); the sampling information at the post-sampling time t +1 is recorded as xj(i.e., post-sampling information). When x isiWhen the vector is a t + 2-dimensional vector, the normalized temperature and humidity value data at the current sampling time t and the normalized PM2.5 concentration value at the past continuous sampling time are included.
In the invention, a function capable of accurately indicating the relation between PM2.5 concentration data and temperature and humidity data is found in a high-dimensional characteristic space, and the SVR model for establishing PM2.5 concentration is established as follows:
Figure BDA0002299974050000047
wherein the content of the first and second substances,
Figure BDA0002299974050000048
is a Gaussian radial basis kernel function with PM2.5 concentration, temperature and humidity as independent variables, and sigma is a bandwidth parameter, wherein sigma is 0.2, αi≥0,
Figure BDA0002299974050000049
Is a lagrange multiplier.
In the SVR model of PM2.5 concentration of the invention, SVR model coefficients
Figure BDA0002299974050000051
Wherein, aj≥0,
Figure BDA0002299974050000052
For the Lagrange multiplier, ε is the SVR model output f (x) and the normalized PM2.5 concentration
Figure BDA0002299974050000053
The absolute value of the difference between them. After the independent variables are given, based on the already established SVR model
Figure BDA0002299974050000054
Predicted PM2.5 concentration data may be obtained
Figure BDA0002299974050000055
Namely, it is
Figure BDA0002299974050000056
Finally, Mean Squared Error (MSE) is adopted to describe the difference omega between the predicted value and the measured valueMSEWherein
Figure BDA0002299974050000057
Representing a predicted value of PM2.5 concentration, yiRepresenting the true value of the subsequent measured PM2.5 concentration, the mean square error is:
Figure BDA0002299974050000058
the decision coefficient R represents the quality of a fitting through the change of data, and the closer the decision coefficient R is to 1, the stronger the interpretation ability of the model to the variable is, the better the fitting of the model to the data is (as the comparison between the predicted value and the real value (measured value) shown in fig. 2), usually greater than 0.4 indicates that the fitting effect is good, and the expression is:
Figure BDA0002299974050000059
wherein the content of the first and second substances,
Figure BDA00022999740500000510
represents the predicted value of PM2.5 concentration, yiRepresents the true value of the PM2.5 concentration, and N is the number of samples.

Claims (4)

1. A human body microenvironment air quality detection, forecast and prediction system based on an intelligent mobile terminal is installed in the intelligent mobile terminal; the method is characterized in that: the system consists of an information reading module, an information processing module and an air quality monitoring and forecasting module;
the information reading module comprises temperature information, humidity information and PM2.5 concentration information which are read by an intelligent mobile terminal; i.e. fGeneral assembly＝{XPM2.5,XTemperature of,XHumidity}，XTemperature ofTemperature information, X, for real-time readingHumidityHumidity information and X for real-time readingPM2.5PM2.5 concentration information is read in real time;
the information processing module is used for processing the fGeneral assembly＝{XPM2.5,XTemperature of,XHumidityReading in after delaying for 2 seconds, and recording the read PM2.5 concentration data frame as f1 inTemperature data frame as
Figure FDA0002299974040000011
Humidity data frame as
Figure FDA0002299974040000012
While
Figure FDA0002299974040000013
And
Figure FDA0002299974040000014
combining the temperature information and the humidity information;
each group of f1 inData comprising ten bytes; firstly, the header of a data frame and the mark information of successful receiving are received, and then PM2.5 concentration low byte and high byte signals are received successively; multiplying high byte information by 256 and adding low byte information, and then dividing by 10 to obtain the PM2.5 concentration value after each group of normalization;
each group of the temperature and humidity information data frames, wherein the first byte and the second byte respectively represent a high 8-bit byte signal and a low 8-bit byte signal of the humidity, and then the two bytes are combined to calculate a corresponding decimal number and divided by 10 to obtain the final humidity; the third byte and the fourth byte represent the upper 8-bit byte signals and the lower 8-bit byte signals of the temperature, then the two bytes are combined to calculate the corresponding decimal number, and the decimal number is divided by 10 to obtain the final temperature;
air quality monitoring and forecasting module and
Figure FDA0002299974040000015
displayed on the screen of the smart phone as the PM2.5 concentration output value,
Figure FDA0002299974040000016
for the maximum value of the PM2.5 concentration data set read in real time,
Figure FDA0002299974040000017
is the minimum value of the PM2.5 concentration data set read in real time. In the same way, the temperature and humidity information can be normalized to obtain
Figure FDA0002299974040000018
2. The intelligent mobile terminal-based human body microenvironment air quality detection and prediction system according to claim 1, wherein: the air quality monitoring and forecasting module processes and forecasts the PM2.5 concentration information by a support vector regression method.
3. The intelligent mobile terminal-based human body microenvironment air quality detection and prediction system according to claim 1, wherein: connect humiture device, PM2.5 concentration device through the bluetooth.
4. The intelligent mobile terminal-based human body microenvironment air quality detection and prediction system according to claim 1, wherein: the intelligent mobile terminal is an intelligent mobile phone.
CN201911217815.4A 2019-12-03 2019-12-03 Human body microenvironment air quality detection and prediction system based on intelligent mobile terminal Pending CN111006981A (en)

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