CN116664333B - Information resource system based on Internet of Things - Google Patents
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Abstract
The invention relates to the technical field of information resource systems, and discloses an information resource system based on the Internet of things, which comprises a central server, wherein the central server is provided with an information acquisition module, an information preprocessing module, a data analysis module, a data comparison module and a cloud service storage module, and the information resource system based on the Internet of things collects relevant parameters of a crop growth environment by utilizing a sensor and the technology of the Internet of things. Through preprocessing, data analysis and comparison, the system can calculate seasonal difference parameters and carry out grading treatment according to the degree of difference, and meanwhile, the system also provides a cloud service storage module, so that the system is convenient for recording and backing up data, can help farmers or users monitor and manage crop growth environments, and improves crop yield and quality.
Description
Technical Field
The invention relates to the technical field of information resource systems, in particular to an information resource system based on the Internet of things.
Background
An information resource system is a comprehensive system for managing, storing, processing, and providing various information resources. Advanced information technology is commonly utilized, including computer science, network technology, database management, data analysis, etc., to provide efficient, secure, and convenient information services to users.
Crop planting refers to the act of planting agricultural crops in an organized manner in a farm or agricultural production area. It is an important component of agricultural production, and can be used for providing food sources of grains, vegetables and fruits for human beings, and can be used for industrial raw materials, animal husbandry feed and other purposes.
Traditional crop planting is carried out by depending on farmer experience or a greenhouse planting technology process, and the traditional experience and a basic planting technology have a certain narrowness for the differences of soil quality, climate and other changing factors in different areas, so that misjudgment or pipelining is easy to cause, and errors in the crop planting process are caused, so that the final yield and quality are affected.
Disclosure of Invention
The invention provides an information resource system based on the Internet of things, which has the beneficial effect of combining a planting technology, the Internet of things and the information resource system, and solves the problems that the prior art has a certain narrow nature on the differences of soil, climate and other change factors of different areas.
The invention provides the following technical scheme: the utility model provides an information resource system based on thing networking, includes central server, central server carries on information acquisition module, information preprocessing module, data analysis module, data comparison module to and cloud service storage module, its characterized in that:
the information acquisition module is used for collecting relevant parameters of crop environment information;
the information preprocessing module is used for preprocessing the acquired related parameters, deleting invalid parameters and extracting core parameter values:
the data analysis module is used for calculating the acquired parameter values so as to acquire seasonal difference parameters through the calculation of the refined core parameter values：
；
In the middle ofRepresents climate parameters>The average temperature is multiplied by the weight coefficient of the average temperature and the average humidity is multiplied by the weight coefficient of the average humidity, and the sum of the average temperature and the average humidity is compared with the sum of the two weight coefficients to obtain;
representative soil parameters obtained by the following formula:
；
in the middle ofRepresenting the soil nutrient system, < >>Representing the soil coefficient, & lt & gt>And->Are all weight coefficients, and、/>，/>and->The value of (2) is set by the customer, r represents the attenuation value of the land quality, t represents the interval time between the time of registration information and the time of actual inquiry, said +.>To correct parameters, and theThe value is set by the customer;
a and b respectively represent climate parametersSoil parameters->Weight value of (2), and->、，/>Represents a correction factor which is constant and +.>And +.>The values of the three are adjusted and set by a client;
the data comparison module is used for season difference parametersAnd seasonal reference frame->The number is calculated to obtain a difference value +.>And the difference value +.>And threshold->Sum threshold->Comparison is made for the difference value->Wherein the difference value is classified by the index of (2)>Threshold->The representative error is within a reasonable interval, a threshold value +.>Difference value->Threshold valueRepresenting that the error is within the critical interval, the difference value +.>Threshold->Representing that the error exceeds a threshold;
the cloud service storage module is used for the system to call cloud data, record the data collected and produced in the system workflow and simultaneously serve as cloud backup service.
As an alternative scheme of the information resource system based on the internet of things, the invention comprises the following steps: the information acquisition module acquires temperature coefficients corresponding to the temperature sensors through the temperature sensors and the humidity sensorsAnd humidity coefficient->；
The temperature coefficients acquired by a plurality of the temperature sensorsIs marked as->、/>、、/>、…、/>；
The humidity coefficients acquired by a plurality of the humidity sensorsIs marked as->、/>、、/>、…、/>；
The temperature sensors and the humidity sensors are connected through the Internet of things and are set through mobile phone application programs to establish working intervals.
As an alternative scheme of the information resource system based on the internet of things, the invention comprises the following steps: the information preprocessing module comprises a screening unit, wherein the screening unit is used for identifying an error data set and an abnormal data set, and deleting the error data set item and the abnormal data set item from the collection total item to purify the sample library.
As an alternative scheme of the information resource system based on the internet of things, the invention comprises the following steps: a column dividing unit is further arranged in the information preprocessing module, and the column dividing unit collects a plurality of temperature coefficients of the data processed by the screening unit through a summation formulaAnd several humidity coefficients->Processing the data to obtain average temperature coefficient->And average humidity coefficient>The specific formula is as follows:
；
；
wherein n represents the number of items;
and +.>Respectively represent temperature coefficient->Is the first term and humidity coefficient->Is the first item of (2);
and +.>Respectively represent temperature coefficient->End of (2) and humidity coefficient +.>Last item of (2).
As an alternative scheme of the information resource system based on the internet of things, the invention comprises the following steps: the climate parametersObtained by the following formula:
；
in the middle ofFor the average temperature coefficient obtained in the above step, < > about->For the average temperature coefficient->Weight coefficient of (2), and->；
For the average humidity coefficient obtained in the above step, < > water>For the average humidity coefficient->Weight value of (2), and->；
Is a correction constant, and said +.>And +.>The values of the three are adjusted and set by the customer.
As an alternative scheme of the information resource system based on the internet of things, the invention comprises the following steps: the information acquisition module also acquires the soil nutrient coefficient by calling the soil data in the cloud databaseAnd soil coefficient->。
As an alternative scheme of the information resource system based on the internet of things, the invention comprises the following steps: the data comparison module compares the seasonal difference parametersAnd seasonal reference frame->Data processing is performed to obtain a difference value +.>The specific formula is as follows:
；
wherein I is a correction index, and the specific value is adjusted and set by a client.
The invention has the following beneficial effects:
1. according to the information resource system based on the Internet of things, the sensor and the technology of the Internet of things are utilized to collect relevant parameters of the crop growth environment. Through preprocessing, data analysis and comparison, the system can calculate seasonal difference parameters and carry out grading treatment according to the degree of difference, and meanwhile, the system also provides a cloud service storage module, so that the data can be recorded and backed up conveniently, farmers or users can be helped to monitor and manage the crop growth environment, and crop yield and quality are improved.
2. According to the information resource system based on the Internet of things, the climate data and the soil data acquired in real time are utilized, the weight values of the climate and the soil parameters are flexibly adjusted, and the seasonal difference parameters Gx are obtained through adjustment of the correction factors. The parameter has important significance for knowing seasonal climate and soil changes, researching and deciding on agriculture, ecological environment and the like, and a customer can customize parameter setting according to own needs so as to better meet actual application scenes.
Drawings
FIG. 1 is a schematic diagram of a system according to the present invention.
FIG. 2 is a schematic flow chart of the system 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.
Example 1: referring to fig. 1-2, an information resource system based on the internet of things includes a central server, wherein the central server is provided with an information acquisition module, an information preprocessing module, a data analysis module, a data comparison module and a cloud service storage module:
the information acquisition module is used for collecting relevant parameters of crop environment information;
the information preprocessing module is used for preprocessing the acquired related parameters, deleting invalid parameters and extracting core parameter values:
the data analysis module is used for calculating the acquired parameter values so as to acquire seasonal difference parameters through the calculation of the extracted core parameter values：
；
In the middle ofRepresents climate parameters>The average temperature is multiplied by the weight coefficient of the average temperature and the average humidity is multiplied by the weight coefficient of the average humidity, and the sum of the average temperature and the average humidity is compared with the sum of the two weight coefficients to obtain;
representative soil parameters obtained by the following formula:
；
in the middle ofRepresenting the soil nutrient system, < >>Representing the soil coefficient, & lt & gt>And->Are all weight coefficients, and、/>，/>and->The value of (2) is set by the customer, r represents the attenuation value of the land quality, t represents the interval time between the time of registration information and the time of actual inquiry, said +.>To correct parameters, and theThe value is set by the customer;
a and b respectively represent climate parametersSoil parameters->Weight value of (2), and->、，/>Represents a correction factor which is constant and +.>And +.>The values of the three are adjusted and set by a client;
the data comparison module is used for season difference parametersAnd seasonal reference frame->The number is calculated to obtain a difference value +.>And the difference value +.>And threshold->Sum threshold->Comparison is made for the difference value->Carrying out grading treatment on the indexes of the (B);
the cloud service storage module is used for the system to call cloud data, record the data collected and produced in the flow and simultaneously serve as cloud backup service;
in this embodiment: the central server: as the core of the system, various functional modules are carried and data storage and processing capacity is provided;
and the information acquisition module is used for: the system comprises a monitoring device, a control device and a control device, wherein the monitoring device is used for collecting relevant parameters of crop environment information and monitoring various indexes of crop growth environments;
an information preprocessing module: and preprocessing the acquired related parameters. The main task of this module is to delete invalid parameters and extract core parameter values to reduce the amount of data and improve the quality of data;
and a data analysis module: and calculating the acquired parameter values, and calculating the obtained seasonal difference parameters Gx through the extracted core parameter values. According to a given formula, calculating a value of a seasonal difference parameter Gx by using weight values of the climate parameter and the soil parameter and a correction factor X;
and a data comparison module: and calculating the seasonal difference parameter Gx and the seasonal reference system CKxs to obtain a difference value Cz. And then comparing the difference value Cz with a preset threshold value Yz and a threshold value Qz, and grading the index of the difference value Cz. The module can help farmers or users to know the change condition of the crop growth environment and perform corresponding treatment or adjustment according to the degree of difference;
cloud service storage module: the cloud data storage system is used for storing cloud data which is called by the system, and recording and backing up data which are generated in the whole data acquisition and processing process. The module can provide long-term storage and backup of data, and ensure the safety and reliability of the data.
The information resource system based on the Internet of things utilizes the sensor and the Internet of things technology to collect relevant parameters of the crop growth environment. Through preprocessing, data analysis and comparison, the system can calculate seasonal difference parameters and conduct grading processing according to the difference degree. Meanwhile, the system also provides a cloud service storage module, so that data can be recorded and backed up conveniently. Can also help farmers or users monitor and manage the crop growth environment and improve the crop yield and quality.
The information acquisition module also acquires the soil nutrient coefficient by calling the soil data in the cloud databaseAnd soil coefficient->。
When a user or a system needs to obtain the nutrient coefficient of the landAnd soil coefficient->And the information acquisition module is communicated with the cloud database. It initiates a query request and retrieves the corresponding data from the cloud database based on the specified land identification or other query criteria. Once the database returns the desired soil nutrient and soil texture coefficients, the information acquisition module will transmit these data to a data analysis module or other related module for further calculation, analysis or application
The information acquisition module realizes dynamic updating and real-time acquisition of the land characteristics by calling the land data in the cloud database, thereby providing accurate land nutrient and soil property information for users. The real-time property and the accuracy of the information have important significance in the fields of agriculture, environment monitoring, land management and the like, and the information resource system based on the Internet of things is more powerful and practical.
Calculating the simple difference between the time of the actual registration information and the time of the actual retrieval level information by an attenuation calculation formula in a data analysis module to obtain the interval t between the time of the registration information and the actual query time, obtaining an actual value at an attenuation value r registered by the attenuation formula, and calculating a weighting formula for the two values to obtain the required soil parameters。
The information resource system based on the Internet of things acquires soil data in real time and invokes data in a cloud database, and obtains soil parameters through a series of calculation and analysis. The soil parameters can provide important information about the soil quality and nutrient content for users, and help the users to make more scientific and reasonable decisions. Meanwhile, the user is allowed to adjust the weight coefficients v and m and the correction parameter alpha according to the self requirements so as to meet the application requirements in different scenes.
The information resource system based on the Internet of things utilizes the climate data and the soil data acquired in real time, and obtains the seasonal difference parameter Gx by flexibly adjusting the weight values of the climate and the soil parameters and then adjusting the correction factors. This parameter is of great importance for understanding seasonal climate and soil changes, as well as for research and decision making in agriculture, ecological environments, etc. The client can customize parameter setting according to own needs, so that the client can better meet the actual application scene.
The system compares the difference value Cz with a preset threshold value Qz and a preset threshold value Yz, and carries out grading treatment on the difference value Cz, so that the error degree and the accuracy of data are judged;
difference value Cz: the aforementioned difference value Cz is obtained by data processing and represents the degree of difference between the seasonal difference parameter Gx and the seasonal reference frame CKxs;
threshold Qz: the threshold is a set critical point and represents a threshold value of the error in a reasonable interval;
threshold Yz: the threshold is another set threshold that represents a threshold for errors within a critical interval.
When the difference Cz is less than or equal to the threshold Qz, the system considers the error of the data to be within an acceptable reasonable range;
when the difference Cz is greater than the threshold Qz and less than or equal to the threshold Yz, the system considers that the error of the data has entered a critical state, possibly requiring attention or further processing;
the difference value Cz is greater than the threshold Yz: when the discrepancy Cz exceeds the threshold Yz, the system determines that the error of the data has exceeded a critical value, possibly requiring urgent processing or correction. Example 2: referring to fig. 1-2, the information acquisition module acquires temperature coefficients corresponding to the temperature sensors and the humidity sensors through the temperature sensors and the humidity sensorsAnd humidity coefficient->；
Temperature coefficient acquired by a plurality of temperature sensorsIs marked as->、/>、、/>、…、/>；
Humidity coefficient collected by a plurality of humidity sensorsIs marked as->、/>、/>、、…、/>；
The temperature sensors and the humidity sensors are connected through the Internet of things and are set through mobile phone application programs to establish working intervals.
In this embodiment: a number of temperature and humidity sensors are used for data acquisition. The temperature coefficient collected by each sensor is recorded as WDxs1, WDxs2, WDxs3, WDxs4, … and WDxsn, the humidity coefficient collected by each sensor is recorded as SDxs1, SDxs2, SDxs3, SDxs4, … and SDxsn, and the sensors can be configured according to the quantity of actual requirements,
The temperature sensor and the humidity sensor are connected through the Internet of things, collected data are transmitted to the central server, meanwhile, a user can set the sensor through a mobile phone application program, and a working interval is formulated, namely the upper limit and the lower limit of temperature and humidity are set, so that environmental parameters are ensured to be in a reasonable range.
The information resource system based on the Internet of things collects environmental parameters by using the temperature sensor and the humidity sensor, and is set and controlled by the Internet of things connection and the mobile phone application program. Such a system may help a user monitor and manage ambient temperature and humidity in real time to provide better decision basis and to ensure proper operation of crops or other applications.
Example 3: referring to fig. 1-2, the information preprocessing module includes a filtering unit, which is used for identifying an error data set and an abnormal data set, and deleting the error data set item and the abnormal data set item from the collection total item to clean the sample library.
In this embodiment: the information preprocessing module is used for processing the acquired data in the information resource system based on the Internet of things so as to purify a sample library and ensure the data quality of subsequent analysis and application. The information preprocessing module comprises a screening unit, and the task of the screening unit is to identify error data groups and abnormal data groups, and delete the error data groups and the abnormal data groups from the collection total items so as to achieve the purpose of improving the coefficient effectiveness of the collection items.
Example 4: referring to fig. 1-2, a column dividing unit is further provided in the information preprocessing module, and the column dividing unit collects the data processed by the screening unit to a plurality of temperature coefficients collected by the collecting module through a summation formulaAnd several humidity coefficients->Processing the data to obtain average temperature coefficient->And average humidity coefficient>The specific formula is as follows:
；
；
wherein n represents the number of items;
and +.>Respectively represent temperature coefficient->Is the first term and humidity coefficient->Is the first item of (2);
and +.>Respectively represent temperature coefficient->End of (2) and humidity coefficient +.>Last item of (2).
In this embodiment: in the information preprocessing module, besides the screening unit, a column dividing unit is further arranged, the task of the column dividing unit is to further process the data processed by the screening unit to obtain an average temperature coefficient and an average humidity coefficient, and the calculating process is to obtain the average value of the temperature coefficient and the humidity coefficient, so that the environmental parameters are more comprehensively analyzed and judged. By means of the averaging process, random errors possibly existing in the data can be reduced, and stability and reliability of the data are improved. The resulting average temperature coefficient and average humidity coefficient may provide a more valuable reference for subsequent data analysis and decision making.
Example 5: referring to fig. 1-2, climate parametersObtained by the following formula:
；
in the middle ofFor the average temperature coefficient obtained in the above step, < > about->For the average temperature coefficient->Weight coefficient of (2), and->；
For the average humidity coefficient obtained in the above step, < > water>For the average humidity coefficient->Weight value of (2), and->；
Is a correction constant, and->And +.>The values of the three are adjusted and set by the customer.
In this embodiment: by this formula, isThe system can calculate comprehensive climate parameters according to the collected temperature and humidity data. The climate parameters provide important reference basis for evaluating and deciding the growth environment of crops. The client can flexibly adapt to different application scenes and requirements by adjusting the values of c, d and T, so that more accurate data analysis and decision making are realized.
Example 9: the data comparison module compares the season difference parametersAnd seasonal reference frame->Data processing is performed to obtain a difference value +.>The specific formula is as follows:
；
wherein I is a correction index, and the specific value is adjusted and set by a client.
In this embodiment: the information resource system based on the Internet of things is characterized in that a data comparison module is utilized to process seasonal difference parameters Gx and a seasonal reference system CKxs, and a difference value Cz is obtained through calculation, so that a user is helped to know the influence of seasonal variation, and a data processing result is adjusted according to a correction index I set by the user so as to meet different use requirements. This can be applied to various scenarios where data analysis and decision making according to seasonal variations are required.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the scope of the invention.
Claims (7)
1. The utility model provides an information resource system based on thing networking, includes central server, central server carries on information acquisition module, information preprocessing module, data analysis module, data comparison module to and cloud service storage module, its characterized in that:
the information acquisition module is used for collecting relevant parameters of crop environment information;
the information preprocessing module is used for preprocessing the acquired related parameters, deleting invalid parameters and extracting core parameter values:
the data analysis module is used for calculating the acquired parameter values so as to acquire seasonal difference parameters through the calculation of the refined core parameter values：
；
In the middle ofRepresents climate parameters>The average humidity is multiplied by the average temperature multiplied by the weight coefficient of the average temperature multiplied by the average humidityThe sum of the weight coefficients of the degree is obtained by comparing the sum of the weight coefficients with the sum of the weight coefficients of the degree;
representative soil parameters obtained by the following formula:
；
in the middle ofRepresenting the soil nutrient system, < >>Representing the soil coefficient, & lt & gt>And->Are all weight coefficients, and +.>、/>，/>And->The value of (2) is set by the customer, r represents the attenuation value of the land quality, t represents the interval time between the time of registration information and the time of actual inquiry, said +.>For correcting parameters, and said +.>The value is set by the customer;
a and b respectively represent climate parametersSoil parameters->Weight value of (2), and->、，/>Represents a correction factor which is constant and +.>And +.>The values of the three are adjusted and set by a client;
the data comparison module is used for season difference parametersAnd seasonal reference frame->The number is calculated to obtain a difference value +.>And the difference value +.>And threshold->Sum threshold->Comparison is made for the difference value->Wherein the difference value is classified by the index of (2)>Threshold->The representative error is within a reasonable interval, a threshold value +.>Difference value->Threshold->Representing that the error is within the critical interval, the difference value +.>Threshold->Representing that the error exceeds a threshold;
the cloud service storage module is used for the system to call cloud data, record the data collected and produced in the system workflow and simultaneously serve as cloud backup service.
2. The information resource system based on the internet of things according to claim 1, wherein: the information acquisition module acquires temperature coefficients corresponding to the temperature sensors through the temperature sensors and the humidity sensorsAnd coefficient of humidity；
The temperature coefficients acquired by a plurality of the temperature sensorsIs marked as->、/>、/>、/>、…、/>；
The humidity coefficients acquired by a plurality of the humidity sensorsIs marked as->、/>、/>、、…、/>；
The temperature sensors and the humidity sensors are connected through the Internet of things and are set through mobile phone application programs to establish working intervals.
3. The information resource system based on the internet of things according to claim 2, wherein:
the information preprocessing module comprises a screening unit, wherein the screening unit is used for identifying an error data set and an abnormal data set, and deleting the error data set item and the abnormal data set item from the collection total item to purify the sample library.
4. The internet of things-based information resource system of claim 3, wherein: a column dividing unit is further arranged in the information preprocessing module, and the column dividing unit collects a plurality of temperature coefficients of the data processed by the screening unit through a summation formulaAnd several humidity coefficients->Data processing is carried out to obtain an average temperature coefficientAnd average humidity coefficient>The specific formula is as follows:
；
；
wherein n represents the number of items;
and +.>Respectively represent temperature coefficient->Is the first term and humidity coefficient->Is the first item of (2);
and +.>Respectively represent temperature coefficient->End of (2) and humidity coefficient +.>Last item of (2).
5. The information resource system based on the internet of things according to claim 4, wherein: the climate parametersObtained by the following formula:
；
wherein:represented by average temperature coefficient>For the average temperature coefficient->And (2) weight coefficient of；
Represented as average humidity coefficient>For the average humidity coefficient->Weight value of (2), and->；
Is a correction constant, and said +.>And +.>The values of the three are adjusted and set by the customer.
6. The internet of things-based information resource system of claim 5, wherein: the information acquisition module also acquires the soil nutrient coefficient by calling the soil data in the cloud databaseAnd soil coefficient->。
7. The internet of things-based information resource system of claim 6, wherein: the data comparison module compares the seasonal difference parametersAnd seasonal reference frame->Data processing is performed to obtain a difference value +.>The specific formula is as follows:
；
wherein I is a correction index, and the specific value is adjusted and set by a client.
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