CN116931486A - Intelligent library environment data analysis device and method based on HarmonyOS - Google Patents
Intelligent library environment data analysis device and method based on HarmonyOS Download PDFInfo
- Publication number
- CN116931486A CN116931486A CN202310902369.0A CN202310902369A CN116931486A CN 116931486 A CN116931486 A CN 116931486A CN 202310902369 A CN202310902369 A CN 202310902369A CN 116931486 A CN116931486 A CN 116931486A
- Authority
- CN
- China
- Prior art keywords
- data
- environment
- library
- sensor
- fusion
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000007405 data analysis Methods 0.000 title claims abstract description 19
- 230000007613 environmental effect Effects 0.000 claims abstract description 45
- 238000012544 monitoring process Methods 0.000 claims abstract description 32
- 238000011161 development Methods 0.000 claims abstract description 23
- 230000008569 process Effects 0.000 claims abstract description 13
- 238000012545 processing Methods 0.000 claims abstract description 9
- 230000001105 regulatory effect Effects 0.000 claims abstract description 8
- 230000004927 fusion Effects 0.000 claims description 46
- 230000005540 biological transmission Effects 0.000 claims description 29
- 230000006870 function Effects 0.000 claims description 15
- 238000005286 illumination Methods 0.000 claims description 14
- 239000000779 smoke Substances 0.000 claims description 12
- 230000008447 perception Effects 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 10
- 230000000694 effects Effects 0.000 claims description 6
- 230000005856 abnormality Effects 0.000 claims description 5
- 230000003750 conditioning effect Effects 0.000 claims description 5
- 238000007781 pre-processing Methods 0.000 claims description 5
- 230000003044 adaptive effect Effects 0.000 claims description 3
- 230000002159 abnormal effect Effects 0.000 abstract description 5
- 238000005259 measurement Methods 0.000 description 6
- 238000013461 design Methods 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 239000007789 gas Substances 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- UBAZGMLMVVQSCD-UHFFFAOYSA-N carbon dioxide;molecular oxygen Chemical compound O=O.O=C=O UBAZGMLMVVQSCD-UHFFFAOYSA-N 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0423—Input/output
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/38—Creation or generation of source code for implementing user interfaces
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/25—Pc structure of the system
- G05B2219/25257—Microcontroller
Abstract
The invention discloses a HarmonyOS-based intelligent library environment data analysis device and method, wherein the method comprises the following steps: the method comprises the steps of collecting information data of environments at different positions in a library by using a sensor, transmitting the information data to a development board through a ZigBee coordinator, processing the data by using the development board, and wirelessly transmitting the processed data to a HarmonyOS database and an environment adjusting module through an NB-IoT module; the HarmonyOS database receives and stores data, and the environment monitoring APP can call the environment information data in the HarmonyOS database and display the data to a user; when the measured value exceeds a preset threshold value, the environment monitoring APP warns a popup window to warn a manager that the current environment parameters are abnormal, and the environment of the library is regulated in an environment regulating module through a PID control algorithm. The device has excellent reliability and stability, and can collect the environmental data of the library in real time and correct and process the problems in time.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a HarmonyOS-based intelligent library environment data analysis device and method.
Background
The damage to books caused by the environmental factors of the library is ignored in the past, and the environment of the library can be influenced by factors such as illumination humidity, illumination intensity, the number of people in the library, temperature, harmful gas concentration and the like, so that the monitoring of the environment in the library can effectively help library management personnel to master the preservation condition of the books in the library.
The development of the internet of things provides new possibilities for the development mode of libraries, and the "smart library" enables the advantages of the traditional library mode to be further optimized and the disadvantages to be resolved. In the aspect of in-library environment monitoring, the library can use some mobile equipment and wireless transmission's scheme to monitor the sightseeing in the library in real time, has reduced the consumption of manpower resources and has also reduced the holistic cost of equipment to with the data wireless transmission who gathers to cloud platform, more be favorable to the administrator to follow-up handling relevant data. The foreign intelligent library research starts early and has a wide research scope, and compared with domestic scholars, the foreign scholars pay more attention to the application and practice of the intelligent library, and the research content is more specific. Research on intelligent libraries in China has been rapidly developed in recent years, and personalized results are achieved in many universities, but many systems have more or less disadvantages. The existing library environment data processing system has the following defects: defects exist in the process of processing and analyzing the library environment monitoring and environment data, so that various data types cannot be analyzed completely, and the defects exist.
Disclosure of Invention
The invention aims to solve the technical problems that: the intelligent library environment data analysis device and method based on the HarmonyOS comprise a sensing layer, a transmission layer, an application layer and an environment adjusting module, and can automatically adjust weights according to the accuracy and reliability of each sensor to obtain an optimal fusion value, so that the reliability and stability of a system are improved, the remote monitoring and adjusting functions of library environment data are realized, and books in a library can be stored for a longer time in a proper environment.
The invention adopts the following technical scheme for solving the technical problems:
the invention provides a HarmonyOS-based intelligent library environment data analysis device which comprises a perception layer, a transmission layer, an application layer and an environment adjusting module.
The sensing layer is used for transmitting the acquired environmental information data to the transmission layer after processing;
the transmission layer is used for transmitting the received environmental information data to the application layer module and the environmental regulation module;
the application layer is used for storing environment information data and displaying the data to a user;
the environment adjusting module is used for comparing the collected environment information data with a set corresponding threshold value, and adjusting the data in the environment according to the comparison result so as to maintain the library environment in a proper state.
Wherein the transmission layer processes the environmental information data including:
step 1, preprocessing data by utilizing a Grabbs criterion;
step 2, collecting x data in a period of time, dividing the data into n groups, and calculating the average value and variance of each group of data;
step 3, according to the calculated average value and variance, the optimal estimated value of each sensor after data fusion and the total variance of each sensor after data fusion are obtained through a batch estimation theory;
step 4, reasonably distributing the weight of each sensor according to the principle that the total mean square error is minimum according to the calculated optimal estimated value after data fusion;
and 5, performing self-adaptive weighted fusion to obtain an optimal fusion result.
Further, the perception layer is configured to perform the following actions: the sensing layer comprises n nodes consisting of an air quality sensor, a temperature and humidity sensor, a smoke alarm sensor and an illumination intensity sensor and a ZigBee coordinator; the sensor respectively collects information data of temperature, humidity, smoke concentration, air quality and illumination intensity of environments at different positions in the library, transmits the data collected by n nodes to a ZigBee coordinator through a ZigBee network, and transmits the data to a transmission layer.
Further, the transport layer is configured to perform the following actions: the transport layer includes STM32F103C8T6 development boards and NB-IoT modules; the STM32F103C8T6 development board receives and processes the environmental information data from the perception layer and wirelessly transmits the processed data to the application layer module and the environmental conditioning module through the NB-IoT module.
Further, the application layer is configured to perform the following actions: the application layer comprises a HarmonyOS database and an environment monitoring APP, wherein the HarmonyOS database receives and stores the environment information data from the transmission layer, and the environment monitoring APP can call the environment information data in the HarmonyOS database and display the data to a user.
The development of the environment monitoring APP is based on DevEco Studio development software, the DevEco Studio provides a UI interface preview function, and the UI interface effect of the application/service can be checked; the functions of the APP include real-time data viewing, historical data viewing, and pop-up window alerting when a predetermined threshold is exceeded.
Further, the environmental conditioning module is configured to perform the following actions: the environment adjusting module comprises a heater unit, a humidifier unit, a fan unit and a light control unit, when the measured value exceeds a preset threshold value, the environment monitoring APP warns a manager of abnormality of the current environment parameters of the popup window, and the library environment is adjusted through a PID control algorithm.
Furthermore, the invention also provides a HarmonyOS-based intelligent library environment data analysis method, which comprises the following steps:
s1, respectively acquiring information data of temperature, humidity, smoke concentration, air quality and illumination intensity of environments at different positions in a library by using sensors in a sensing layer, transmitting the data acquired by n nodes to a ZigBee coordinator through a ZigBee network, and transmitting the data to a transmission layer.
S2, the STM32F103C8T6 development board of the transmission layer receives and processes the environment information data from the perception layer, and the processed data is wirelessly transmitted to the application layer module and the environment adjusting module through the NB-IoT module.
S3, the HarmonyOS database of the application layer receives and stores the environmental information data from the transmission layer, and the environmental monitoring APP can call the environmental information data in the HarmonyOS database and display the data to a user.
And S4, when the measured value exceeds a preset threshold value, the environment monitoring APP warns the manager of abnormality of the current environment parameters of the popup window, and the environment of the library is regulated in the environment regulating module through a PID control algorithm.
Further, in step S2, the STM32F103C8T6 development board processing environment information data includes the following sub-steps:
s201, acquiring the library environment data by relying on a plurality of sensors, wherein in the acquisition process, the acquisition value has larger deviation due to the fact that the accuracy of the sensors and the node part can be faulty. Thus, data preprocessing is performed using the glabros criterion to reduce the effect of the bias.
S202, in order to further improve accuracy of measurement data, complexity and variability of a measurement environment are considered, and the variance of a measurement result is possibly caused to be large, so that the acquisition values of the same type of sensors are fused by using an improved self-adaptive weighted fusion algorithm, weights of the sensors are reasonably distributed, and self-adaptive weighted fusion is performed, so that an optimal fusion result is obtained.
Further, in step S202, the specific content of using the improved adaptive weighted fusion algorithm to fuse the collected values of the similar sensors is:
s2021, collecting x data in a period of time, dividing the data into n groups, and calculating the average value and variance of each group of data, wherein the specific formula is as follows:
wherein ,Xij The j-th data representing the i-th group, mean value of group i;representing the variance of the i-th group.
S2022, according to the calculated average value and variance, calculating an optimal estimated value of each sensor after data fusion and a total variance of each sensor after data fusion in the period of time by a batch estimation theory, wherein the specific formula is as follows:
wherein ,Xk Representing the optimal estimated value of the kth sensor after data fusion in the period of time,representing the total variance of the kth sensor acquired data after fusion.
S2023, according to the calculated optimal estimated value after data fusion, reasonably distributing the weight of each sensor according to the principle of minimum total mean square error, wherein the optimal weight meets the following conditions:
wherein m represents the number of similar sensors in the library, ω k Representing the optimal weight, sigma, of the kth sensor of the same class 2 The total mean square error is expressed as a function of:
solving the function f (omega 1 ,ω 2 ,……ω m ) The corresponding minimum value of (2) is the optimal weight value, and the weight value distribution formula is:
s2024, calculating an optimal fusion result according to the weight corresponding to each sensor, wherein the specific formula is as follows:
wherein ,indicating the optimal fusion result, X k Representing each sensor data fusionThe optimal estimated value is obtained.
Furthermore, the invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the steps of the intelligent library environment data analysis method based on HarmonyOS are realized when the processor executes the computer program.
Further, the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to execute the Harmony OS-based intelligent library environment data analysis method.
Compared with the prior art, the invention adopts the technical proposal and has the following remarkable technical effects:
1. according to the invention, the environment information of different positions of the library is acquired through n nodes, the temperature and humidity, the illumination intensity, the air quality and the smoke concentration of the library environment can be acquired in real time, the ZigBee coordinator receives data and transmits the data to the development board, the acquisition values of the same type of sensors are fused by adopting an improved self-adaptive weighted fusion algorithm, the fusion values are transmitted to the Harmony OS database through the NB-IoT module, and the analysis reason is further used for alarming according to different abnormal conditions. According to the accuracy and reliability of each sensor, the weight is automatically adjusted to obtain the optimal fusion value, so that the reliability and stability are improved.
2. According to the invention, various indexes in the library can be timely adjusted according to different abnormal conditions, so that the library environment can be conveniently maintained in a state suitable for life and work. And calling the data of the HarmonyOS database into the environment monitoring APP to finish the display of the real-time data and the historical data.
3. The library environment data can be acquired in real time by utilizing the sensing layer, so that the acquired data is ensured to have timeliness and effectiveness, the practicability and feasibility of data analysis are ensured, the historical data and the real-time data are compared, the generated problems and errors are corrected and processed in time, and false alarms caused by the errors of the acquired data are prevented.
Drawings
FIG. 1 is a block diagram of a HarmonyOS-based intelligent library environmental data analysis device of the present invention.
FIG. 2 is a schematic diagram of the function of the APP of the present invention.
FIG. 3 is a main interface of the environmental monitoring APP of the present invention.
Fig. 4 is a schematic structural diagram of an environment adjusting module according to the present invention.
FIG. 5 is a flowchart of the overall implementation of the Harmony OS-based intelligent library environmental data analysis method of the present invention.
Fig. 6 is an environmental real-time data interface of the environmental monitoring APP of the present invention.
FIG. 7 is an environmental history data interface of the environmental monitoring APP of the present invention.
FIG. 8 is an environmental historical temperature data of an environmental monitoring APP of the present invention.
FIG. 9 is an environmental monitoring APP popup alarm of the present invention.
FIG. 10 is a database internal environment data of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments of the present invention. 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.
The invention is described in further detail below with reference to the drawings and the detailed description.
In order to achieve the above objective, the present invention provides a smart library environment data analysis device based on HarmonyOS, as shown in FIG. 1, which includes a sensing layer, a transmission layer, an application layer and an environment adjustment module.
The sensing layer is used for transmitting the acquired environmental information data to the transmission layer after processing.
The transmission layer is used for transmitting the received environmental information data to the application layer module and the environmental regulation module.
The application layer is an interface of the Internet of things and a user, and is used for storing environment information data and displaying the data to the user.
The environment adjusting module is used for comparing the collected environment information data with a set corresponding threshold value, and adjusting the data in the environment according to the comparison result so as to maintain the library environment in a proper state.
The perception layer is configured to perform the following actions: the sensing layer comprises n nodes consisting of an air quality sensor, a temperature and humidity sensor, a smoke alarm sensor and an illumination intensity sensor and a ZigBee coordinator; the sensor respectively collects information data of temperature, humidity, smoke concentration, air quality and illumination intensity of environments at different positions in the library, transmits the data collected by n nodes to a ZigBee coordinator through a ZigBee network, and transmits the data to a transmission layer.
The transport layer is configured to perform the following actions: the transport layer includes STM32F103C8T6 development boards and NB-IoT modules; the STM32F103C8T6 development board receives and processes the environmental information data from the perception layer and wirelessly transmits the processed data to the application layer module and the environmental conditioning module through the NB-IoT module.
The application layer is configured to perform the following actions: the application layer comprises a HarmonyOS database and an environment monitoring APP, wherein the HarmonyOS database receives and stores the environment information data from the transmission layer, and the environment monitoring APP can call the environment information data in the HarmonyOS database and display the data to a user.
As shown in fig. 2, the development of the environment monitoring APP is based on the DevEco Studio development software, which is development software specially used for developing the hong-mo operating system, has a high-efficiency intelligent code writing function, supports multiple language programming and has multiple convenient functions of automatic code error checking, intelligent code complement, code searching and the like, and can improve the code writing efficiency. The DevEco Studio also supports low-code visual development, and in the aspect of interface design, the DevEco Studio can support freely dragging module components and data binding visual, so that the development difficulty is reduced, and meanwhile, the interface development efficiency is improved; the DevEco Studio supports real-time preview, can synchronously preview the running effect of the current code while developing, and supports multiple devices such as mobile phones, intelligent wearable devices and the like to carry out analog simulation preview. The functions of the APP include real-time data viewing, historical data viewing and popup warning when a predetermined threshold is exceeded, and the interface is shown in FIG. 3.
The environmental conditioning module is configured to perform the following actions: as shown in fig. 4, the environment adjusting module comprises a heater unit, a humidifier unit, a fan unit and a light control unit, when the measured value exceeds a preset threshold value, the environment monitoring APP will pop-up the window to warn the manager that the current environment parameters are abnormal, and adjust the environment of the library through a PID control algorithm.
When the temperature is low, the heater unit is turned on, so that the temperature of the library is increased; when the temperature is high, the fan unit is turned on, so that the temperature of the library is reduced. When the light is darker, the light can be turned on, the brightness of the light is increased, the light of the library is enhanced, and the light supplementing effect is achieved. The humidifier unit is adjusted according to the humidity conditions in the library.
The temperature and humidity sensor unit detects the temperature and humidity of the library environment, and adjusts the temperature and humidity of the library environment according to the temperature and humidity values defined in advance after detection, so that the temperature and humidity of the library reach the defined temperature and humidity values.
The air quality sensor unit detects the content of oxygen, carbon dioxide and harmful gas in the air, transmits information to the popup alarm module to warn when the content of the harmful gas in the library environment reaches a certain degree, and starts the environment adjusting module to open the fan ventilation equipment to update the air in the library environment.
The invention also provides a HarmonyOS-based intelligent library environment data analysis method, which comprises the following steps as shown in fig. 5:
s1, respectively acquiring information data of temperature, humidity, smoke concentration, air quality and illumination intensity of environments at different positions in a library by using sensors in a sensing layer, transmitting the data acquired by n nodes to a ZigBee coordinator through a ZigBee network, and transmitting the data to a transmission layer.
S2, the STM32F103C8T6 development board of the transmission layer receives and processes the environment information data from the perception layer, and the processed data is wirelessly transmitted to the application layer module and the environment adjusting module through the NB-IoT module.
Wherein, STM32F103C8T6 development board processing environment information data comprises the following substeps:
s201, acquiring the library environment data by relying on a plurality of sensors, wherein in the acquisition process, the acquisition value has larger deviation due to the fact that the accuracy of the sensors and the node part can be faulty. Thus, data preprocessing is performed using the glabros criterion to reduce the effect of the bias.
S202, in order to further improve accuracy of measurement data, considering complexity and variability of a measurement environment, variance of measurement results may be larger, so that the acquisition values of the same type of sensors are fused by using an improved adaptive weighted fusion algorithm, and weights of the sensors are reasonably distributed, wherein the method comprises the following specific contents:
s2021, collecting x data in a period of time, dividing the data into 4 groups, and calculating the average value and variance of each group of data, wherein the specific formula is as follows:
wherein ,Xij The j-th data representing the i-th group,mean value of group i; />Representing the variance of the i-th group.
S2022, according to the calculated average value and variance, calculating an optimal estimated value of each sensor after data fusion and a total variance of each sensor after data fusion in the period of time by a batch estimation theory, wherein the specific formula is as follows:
wherein ,Xk Representing the optimal estimated value of the kth sensor after data fusion in the period of time,representing the total variance of the kth sensor acquired data after fusion.
S2023, according to the calculated optimal estimated value after data fusion, reasonably distributing the weight of each sensor according to the principle of minimum total mean square error, wherein the optimal weight meets the following conditions:
wherein m represents the number of similar sensors in the library, ω k Representing the optimal weight, sigma, of the kth sensor of the same class 2 The total mean square error is expressed as a function of:
solving the function f (omega 1 ,ω 2 ,……ω m ) The corresponding minimum value of (2) is the optimal weight value, and the weight value distribution formula is:
s2024, calculating an optimal fusion result according to the weight corresponding to each sensor, wherein the specific formula is as follows:
wherein ,indicating the optimal fusion result, X k And representing the optimal estimated value of each sensor after data fusion.
S3, the HarmonyOS database of the application layer receives and stores the environmental information data from the transmission layer, and the environmental monitoring APP can call the environmental information data in the HarmonyOS database and display the data to a user.
And S4, when the measured value exceeds a preset threshold value, the environment monitoring APP warns the manager of abnormality of the current environment parameters of the popup window, and the environment of the library is regulated in the environment regulating module through a PID control algorithm.
After clicking to enter the real-time data interface as shown in fig. 6, five data including temperature, humidity, smoke concentration, illumination intensity and air quality are displayed, the list adding module is used for displaying five data collected by the sensor, and clicking to return to the upper left corner can return to the main interface. After clicking the module entering the history data interface as shown in fig. 7 and 8, five environment parameters are displayed, clicking the module to be checked can pop up and check the history data of the corresponding module, and clicking the upper left return key can return to the main interface. When the currently measured value exceeds a preset threshold value as shown in fig. 9, the APP can pop-up window to warn the manager that the current environmental parameter is abnormal, and adjust the library environment through the PID control algorithm, so that the library environment is maintained in a proper state.
The system shown in fig. 10 uses a Navicat Premium database management tool to design a database, wherein the database mainly comprises a sensor acquisition information table which contains information of temperature, humidity, smoke concentration, air quality and illumination intensity. After the design of software and hardware is completed, an entity hardware circuit model is completed through building and the Internet of things platform is connected, and the NB-IoT module, database data synchronization and environment monitoring APP are respectively tested. The design requirement of the library environment monitoring system can be met.
The embodiment of the invention also provides an electronic device which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor. It should be noted that each module in the above system corresponds to a specific step of the method provided by the embodiment of the present invention, and has a corresponding functional module and beneficial effect of executing the method. Technical details not described in detail in this embodiment may be found in the methods provided in the embodiments of the present invention.
The embodiment of the invention also provides a computer readable storage medium, and the computer readable storage medium stores a computer program. It should be noted that each module in the above system corresponds to a specific step of the method provided by the embodiment of the present invention, and has a corresponding functional module and beneficial effect of executing the method. Technical details not described in detail in this embodiment may be found in the methods provided in the embodiments of the present invention.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (10)
1. The intelligent library environment data analysis device based on the HarmonyOS is characterized by comprising a perception layer, a transmission layer, an application layer and an environment adjustment module;
the sensing layer is used for transmitting the acquired environmental information data to the transmission layer after processing;
the transmission layer is used for transmitting the received environmental information data to the application layer module and the environmental regulation module;
the application layer is used for storing environment information data and displaying the data to a user;
the environment adjusting module is used for comparing the acquired environment information data with a set corresponding threshold value and adjusting the data in the environment according to the comparison result;
wherein the transmission layer processes the environmental information data including:
step 1, preprocessing data by utilizing a Grabbs criterion;
step 2, collecting x data in a period of time, dividing the data into n groups, and calculating the average value and variance of each group of data;
step 3, according to the calculated average value and variance, the optimal estimated value of each sensor after data fusion and the total variance of each sensor after data fusion are obtained through a batch estimation theory;
step 4, reasonably distributing the weight of each sensor according to the principle that the total mean square error is minimum according to the calculated optimal estimated value after data fusion;
and 5, performing self-adaptive weighted fusion to obtain an optimal fusion result.
2. The smart library environment data analysis device of claim 1, wherein the perception layer is configured to: the sensing layer comprises n nodes consisting of an air quality sensor, a temperature and humidity sensor, a smoke alarm sensor and an illumination intensity sensor and a ZigBee coordinator; the sensor respectively collects information data of temperature, humidity, smoke concentration, air quality and illumination intensity of environments at different positions in the library, transmits the data collected by n nodes to a ZigBee coordinator through a ZigBee network, and transmits the data to a transmission layer.
3. The smart library environment data analysis device of claim 1, wherein the transport layer is configured to: the transport layer includes STM32F103C8T6 development boards and NB-IoT modules; the STM32F103C8T6 development board receives and processes the environmental information data from the perception layer and wirelessly transmits the processed data to the application layer module and the environmental conditioning module through the NB-IoT module.
4. The smart library environment data analysis device of claim 1, wherein the application layer is configured to: the application layer comprises a HarmonyOS database and an environment monitoring APP, wherein the HarmonyOS database receives and stores the environment information data from the transmission layer, and the environment monitoring APP can call the environment information data in the HarmonyOS database and display the data to a user;
the development of the environment monitoring APP is based on DevEco Studio development software, the DevEco Studio provides a UI interface preview function, and the UI interface effect of the application/service can be checked; the functions of the APP include real-time data viewing, historical data viewing, and pop-up window alerting when a predetermined threshold is exceeded.
5. The smart library environment data analysis device of claim 1, wherein the environment adjustment module is configured to: the environment adjusting module comprises a heater unit, a humidifier unit, a fan unit and a light control unit, when the measured value exceeds a preset threshold value, the environment monitoring APP warns a manager of abnormality of the current environment parameters of the popup window, and the library environment is adjusted through a PID control algorithm.
6. A method for analyzing environmental data of a smart library based on a harmyos, comprising:
s1, respectively acquiring information data of temperature, humidity, smoke concentration, air quality and illumination intensity of environments at different positions in a library by using sensors in a sensing layer, transmitting the data acquired by n nodes to a ZigBee coordinator through a ZigBee network, and transmitting the data to a transmission layer;
s2, an STM32F103C8T6 development board of a transmission layer receives and processes environment information data from a perception layer, and the processed data is wirelessly transmitted to an application layer module and an environment adjusting module through an NB-IoT module;
s3, the HarmonyOS database of the application layer receives and stores the environmental information data from the transmission layer, and the environmental monitoring APP can call the environmental information data in the HarmonyOS database and display the data to a user;
and S4, when the measured value exceeds a preset threshold value, the environment monitoring APP warns the manager of abnormality of the current environment parameters of the popup window, and the environment of the library is regulated in the environment regulating module through a PID control algorithm.
7. The method for analyzing environmental data of a smart library based on harmyos of claim 6, wherein in step S2, the STM32F103C8T6 development board processes environmental information data comprising the sub-steps of:
s201, preprocessing data by utilizing a Grabbs criterion;
s202, utilizing an improved self-adaptive weighted fusion algorithm to fuse the acquired values of the same type of sensors, reasonably distributing the weight of each sensor, and carrying out self-adaptive weighted fusion to obtain the optimal fusion result.
8. The method for analyzing environmental data of a smart library based on harmyos of claim 7, wherein in step S202, the specific content of using the improved adaptive weighted fusion algorithm to fuse the collected values of the similar sensors is:
s2021, collecting x data in a period of time, dividing the data into n groups, and calculating the average value and variance of each group of data, wherein the specific formula is as follows:
wherein ,Xij The j-th data representing the i-th group,mean value of group i; />Representing the variance of group i;
s2022, according to the calculated average value and variance, calculating an optimal estimated value of each sensor after data fusion and a total variance of each sensor after data fusion in the period of time by a batch estimation theory, wherein the specific formula is as follows:
wherein ,Xk Representing the optimal estimated value of the kth sensor after data fusion in the period of time,representing the total variance of the k sensor acquired data after fusion;
s2023, according to the calculated optimal estimated value after data fusion, reasonably distributing the weight of each sensor according to the principle of minimum total mean square error, wherein the optimal weight meets the following conditions:
wherein m represents the number of similar sensors in the library, ω k Representing the optimal weight, sigma, of the kth sensor of the same class 2 The total mean square error is expressed as a function of:
solving the function f (omega 1 ,ω 2 ,……ω m ) The corresponding minimum value of (2) is the optimal weight value, and the weight value distribution formula is:
s2024, calculating an optimal fusion result according to the weight corresponding to each sensor, wherein the specific formula is as follows:
wherein ,indicating the optimal fusion result, X k And representing the optimal estimated value of each sensor after data fusion.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of claims 6 to 8 when the computer program is executed by the processor.
10. A computer-readable storage medium storing a computer program, characterized in that the computer program when executed by a processor performs the method of any one of claims 6 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310902369.0A CN116931486A (en) | 2023-07-21 | 2023-07-21 | Intelligent library environment data analysis device and method based on HarmonyOS |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310902369.0A CN116931486A (en) | 2023-07-21 | 2023-07-21 | Intelligent library environment data analysis device and method based on HarmonyOS |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116931486A true CN116931486A (en) | 2023-10-24 |
Family
ID=88389202
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310902369.0A Pending CN116931486A (en) | 2023-07-21 | 2023-07-21 | Intelligent library environment data analysis device and method based on HarmonyOS |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116931486A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117148900A (en) * | 2023-10-27 | 2023-12-01 | 济南泰格电子技术有限公司 | Environment safety management method and device for archive |
-
2023
- 2023-07-21 CN CN202310902369.0A patent/CN116931486A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117148900A (en) * | 2023-10-27 | 2023-12-01 | 济南泰格电子技术有限公司 | Environment safety management method and device for archive |
| CN117148900B (en) * | 2023-10-27 | 2024-02-02 | 济南泰格电子技术有限公司 | Environment safety management method and device for archive |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115512520B (en) | Gas use safety early warning method based on intelligent gas and Internet of things system | |
| CN108172288A (en) | Medical Devices intelligent control method, device and computer readable storage medium | |
| CN116931486A (en) | Intelligent library environment data analysis device and method based on HarmonyOS | |
| CN111754715B (en) | Fire-fighting emergency response method, device and system | |
| CN114266944B (en) | Rapid model training result checking system | |
| CN105674491A (en) | Cloud platform-based indoor environment management system | |
| CN113687609A (en) | Intelligent monitoring system and monitoring method for Internet of things applied to abnormal environment | |
| CN114518143A (en) | Intelligent environment sensing system | |
| CN112738236A (en) | Intelligent fire-fighting management system and method for building end | |
| US20230152757A1 (en) | Building data platform with digital twin based fault detection and diagnostics | |
| CN113959477A (en) | Environmental control monitoring reminding method and system based on Internet of things | |
| US20230065717A1 (en) | Support system and support method | |
| CN117236559A (en) | Intelligent charging pile data analysis method and device based on Internet of things | |
| CN116184851A (en) | Sleep mode adjusting method, device, terminal and storage medium | |
| CN115899991A (en) | Air conditioner operation control method and device, electronic equipment and storage medium | |
| WO2018222140A1 (en) | Method and apparatus for deriving and/or controlling individual comfort parameters | |
| Akbar et al. | Smart light recommending system using artificial neural network algorithm | |
| CN109038825A (en) | Substation equipment monitoring method, device and substation equipment monitor | |
| CN114594692A (en) | Intelligent household control system based on mobile phone terminal and Internet of things | |
| CN114646735A (en) | Carbon dioxide concentration monitoring system in air | |
| CN110955286A (en) | Poultry egg monitoring method and device | |
| CN109858576A (en) | The gradual self feed back concentration Entropy Changes prediction technique of gas, system and storage medium | |
| CN109974784A (en) | Semi-automatic detection device | |
| CN114546006B (en) | Intelligent control method and system for cashew nut storage environment | |
| CN108881988A (en) | Television set monitoring process method, television set and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |