CN117629314A - Environment intelligent monitoring system based on Internet of things - Google Patents
Environment intelligent monitoring system based on Internet of things Download PDFInfo
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- CN117629314A CN117629314A CN202410110176.6A CN202410110176A CN117629314A CN 117629314 A CN117629314 A CN 117629314A CN 202410110176 A CN202410110176 A CN 202410110176A CN 117629314 A CN117629314 A CN 117629314A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 142
- 238000004458 analytical method Methods 0.000 claims abstract description 55
- 239000002689 soil Substances 0.000 claims description 104
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 71
- 238000005286 illumination Methods 0.000 claims description 37
- 238000007405 data analysis Methods 0.000 claims description 31
- 238000005457 optimization Methods 0.000 claims description 30
- 201000010099 disease Diseases 0.000 claims description 25
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 25
- 238000013178 mathematical model Methods 0.000 claims description 20
- 238000012545 processing Methods 0.000 claims description 15
- 230000007613 environmental effect Effects 0.000 claims description 14
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 12
- 229910052760 oxygen Inorganic materials 0.000 claims description 12
- 239000001301 oxygen Substances 0.000 claims description 12
- 238000002834 transmittance Methods 0.000 claims description 12
- 230000000243 photosynthetic effect Effects 0.000 claims description 9
- 239000011148 porous material Substances 0.000 claims description 9
- 230000010211 insect pollination Effects 0.000 claims description 7
- 230000029553 photosynthesis Effects 0.000 claims description 7
- 238000010672 photosynthesis Methods 0.000 claims description 7
- 230000010152 pollination Effects 0.000 claims description 7
- 230000000007 visual effect Effects 0.000 claims description 7
- 238000012360 testing method Methods 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 3
- 238000001035 drying Methods 0.000 claims description 3
- 238000011835 investigation Methods 0.000 claims description 3
- 238000000034 method Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 238000005303 weighing Methods 0.000 claims description 3
- 230000006855 networking Effects 0.000 claims 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003902 lesion Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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Abstract
The invention discloses an environment intelligent monitoring system based on the Internet of things, and particularly relates to the field of the Internet of things. According to the intelligent monitoring system, data acquisition and analysis are carried out on the target crop planting area from two aspects of environment data and biological data, and finally, comprehensive analysis is carried out on the data to realize intelligent monitoring on the environment.
Description
Technical Field
The invention relates to the technical field of the Internet of things, in particular to an intelligent environment monitoring system based on the Internet of things.
Background
Traditional agricultural environment monitoring systems can only provide a single data source, and the data is too general and not comprehensive. Furthermore, the system typically only provides basic data analysis, such as average, maximum, minimum, etc., lacking accuracy and reliability. The data needs to be manually processed and analyzed, and cannot respond to environmental changes in time, so that the practical application of the system is limited. In order to solve the problems, an intelligent environment monitoring system based on the Internet of things is provided.
Disclosure of Invention
In order to overcome the defects in the prior art, the embodiment of the invention provides an intelligent environment monitoring system based on the Internet of things, which solves the problems in the background art through the following scheme.
In order to achieve the above purpose, the present invention provides the following technical solutions: an intelligent environmental monitoring system based on the internet of things, comprising:
the monitoring area dividing module is used for determining a target crop planting area as a target monitoring area, dividing sub-monitoring areas with equal areas in the target monitoring area for sampling investigation, and marking the sub-monitoring areas as 1 and 2 … … n in sequence;
the environment data acquisition module is used for acquiring illumination parameters, soil parameters and water quality parameters of each sub-monitoring area and transmitting acquired data to the environment data analysis module;
the environment data analysis module comprises an illumination parameter analysis unit, a soil parameter analysis unit and a water quality parameter analysis unit, and is used for establishing a mathematical model, importing the data transmitted by the environment data acquisition module into the mathematical model, calculating photosynthesis efficiency index, soil characteristic index and water quality characteristic index of each sub-monitoring area, and transmitting the photosynthesis efficiency index, the soil characteristic index and the water quality characteristic index to the comprehensive analysis module;
the biological data acquisition module is used for acquiring the setting parameters, the growth parameters and the disease parameters of each sub-monitoring area and transmitting the acquired data to the biological data processing module;
the biological data processing module is used for processing the setting parameters, the growth parameters and the disease parameters transmitted by the biological data acquisition module and transmitting the processed data to the biological data analysis module;
the biological data analysis module is used for establishing a biological data analysis model, importing the data transmitted by the biological data processing module into the biological data analysis model, calculating the crop health index of each sub-monitoring area, and transmitting the crop health index to the comprehensive analysis module;
the comprehensive analysis module is used for establishing a comprehensive analysis model, importing the data transmitted by the biological data analysis module and the environmental data analysis module into the comprehensive analysis model, calculating the comprehensive optimization index of the target crop planting area, and transmitting the comprehensive optimization index to the intelligent early warning module;
the intelligent early warning module is used for carrying out intelligent early warning on the environment of the target crop planting area according to the comprehensive optimization index of the target crop planting area and the preset value of the comprehensive optimization index, which are transmitted by the comprehensive analysis module.
Preferably, the illumination parameters include illumination intensity, illumination time, greenhouse light transmittance and crop quantity, respectively marked as、/>、/>And +.>The soil parameters include soil quality, soil humidity, soil volume weight, soil pore volume, soil volume and soil pH value, respectively marked as +.>、/>、/>、/>、/>And +.>The water quality parameters include water flow rate, water pH value, water dissolved oxygen concentration and water turbidity, which are marked as +.>、/>、And +.>Where i=1, 2 … … n, i represents the i-th sub-monitoring region;
the setting parameters comprise setting number, bird feeding number, artificial pollination number and insect pollination number, which are marked as follows、/>、/>And +.>The growth parameters included crop sample quality and growth time, decibel mark +.>Anddisease parameters including disease area, leaf area, number of crop diseases and number of crop, respectively marked +.>、、/>And +.>Where i=1, 2 … … n, i represents the i-th sub-monitoring region.
Preferably, the environment data acquisition module acquires illumination intensity and illumination time by installing an illumination intensity sensor and a timer in a greenhouse, acquires greenhouse light transmittance by installing a light transmittance sensor on the surface of the greenhouse, acquires the quantity of crops by installing a visual sensor right above the crops, acquires a soil sample by a soil collector, acquires soil quality, soil humidity and soil volume weight of the soil sample by a drying weighing method, acquires soil pore volume and soil volume of the soil sample by placing the soil sample in a measuring cup, acquires soil pH value of the soil sample by a ph test paper, acquires water flow velocity by installing an ultrasonic flow meter at a water outlet, acquires water pH value by a ph test paper, acquires water dissolved oxygen concentration by a dissolved oxygen meter, and acquires water turbidity by a turbidity meter;
the biological data acquisition module acquires the sample quality of crops by installing a visual sensor right above the crops, namely real number acquisition, bird feeding number acquisition, insect pollination number acquisition, artificial pollination number acquisition, disease spot area acquisition, leaf area acquisition, crop disease number acquisition and crop quantity acquisition, namely, acquiring a crop sample quality in each sub-monitoring area acquisition mode.
Preferably, the illumination parameter analysis unit is configured to establish an illumination parameter analysis model, and the specific mathematical model is:，/>index of photosynthetic efficiency indicating the ith sub-monitoring region,/->Indicating the illumination intensity of the i-th sub-monitoring area, respectively>Indicating the illumination time of the ith sub-monitoring area, < ->Greenhouse light transmittance indicating the ith sub-monitored area, < ->Indicating the crop number of the ith sub-monitoring zone, < ->Indicating the number of sub-monitoring areas,/-, and>representing the area of each sub-monitoring area,/->Other influencing factors representing the photosynthetic efficiency index.
Preferably, the soil parameter analysis unit is configured to establish a soil parameter analysis model, and the specific mathematical model is:，/>soil characteristic index indicating the ith sub-monitored zone, < ->Indicating soil quality of the ith sub-monitored zone, < ->Represents soil moisture of the ith sub-monitoring zone, < ->Soil volume weight representing the ith sub-monitoring zone, < ->Soil pore volume representing the ith sub-monitored zone, +.>Soil volume representing the ith sub-monitored zone, +.>Soil pH value of the ith sub-monitoring area, < ->Other influencing factors representing the soil characteristic index.
Preferably, the water quality parameter analysis unit is used for establishing a water quality parameter analysis model, and the specific mathematical model is as follows:，/>indicating the water quality characteristic index of the i-th sub-monitoring zone,/->Indicating the flow rate of the water flow in the ith sub-monitoring zone, etc.>Indicating the pH value of water in the ith sub-monitoring area, < ->Indicating the water dissolved oxygen concentration of the ith sub-monitoring area,/->Represents the ithSub-monitoring zone water turbidity, < >>Indicating the number of sub-monitoring areas,/-, and>other influencing factors representing the water quality characteristic index.
Preferably, the biological data analysis model is specifically expressed as:，/>crop health index indicating the ith sub-monitoring zone, < ->Indicating the firmness rate of the ith sub-monitored zone, < ->Indicating the growth rate of the ith sub-monitored area, etc.>Indicating the index of the condition of the ith sub-monitored zone, < ->Other influencing factors representing the crop health index.
Preferably, the comprehensive analysis model is specifically expressed as:，/>comprehensive optimization index representing the area of planting the target crop, < >>Crop health index indicating the ith sub-monitoring zone, < ->Index of photosynthetic efficiency indicating the ith sub-monitoring region,/->Represents the soil characteristic index of the i-th sub-monitoring area,indicating the index of the water quality characteristics of the i-th sub-monitoring zone.
Preferably, the integrated optimization index preset value is marked asWhen->When the preset value of the comprehensive optimization index is smaller than or equal to the comprehensive optimization index of the target crop planting area, the environment of the target crop planting area is normal, the monitoring of each sub-monitoring area is kept, and when->And when the preset value of the comprehensive optimization index is larger than the comprehensive optimization index of the target crop planting area, indicating that the environment of the target crop planting area is abnormal, sending out an early warning signal.
The invention has the technical effects and advantages that:
according to the intelligent monitoring system, data acquisition and analysis are carried out on a target crop planting area from two aspects of environment data and biological data, and finally, comprehensive analysis is carried out on the data to realize intelligent monitoring on the environment.
Drawings
Fig. 1 is a schematic diagram of the overall structure 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.
Referring to fig. 1, the environment intelligent monitoring system based on the internet of things comprises a monitoring area dividing module, an environment data acquisition module, an environment data analysis module, a biological data acquisition module, a biological data processing module, a biological data analysis module, a comprehensive analysis module and an intelligent early warning module.
The monitoring area dividing module is used for determining a target crop planting area as a target monitoring area, dividing sub-monitoring areas with equal areas in the target monitoring area for sampling investigation, and marking the sub-monitoring areas as 1 and 2 … … n in sequence.
The environment data acquisition module is used for acquiring illumination parameters, soil parameters and water quality parameters of each sub-monitoring area and transmitting acquired data to the environment data analysis module.
The illumination parameters comprise illumination intensity, illumination time, greenhouse light transmittance and crop quantity, which are respectively marked as、/>、/>And +.>The soil parameters include soil quality, soil humidity, soil volume weight, soil pore volume, soil volume and soil pH value, respectively marked as +.>、/>、/>、/>、/>And +.>The water quality parameters include water flow rate, water pH value, water dissolved oxygen concentration and water turbidity, which are marked as +.>、/>、/>AndWhere i=1, 2 … … n, i represents the i-th sub-monitoring region.
The environment data acquisition module acquires illumination intensity and illumination time by installing an illumination intensity sensor and a timer in a greenhouse, acquires greenhouse light transmittance by installing a light transmittance sensor on the surface of the greenhouse, acquires the quantity of crops by installing a visual sensor right above the crops, acquires a soil sample by a soil collector, acquires soil quality, soil humidity and soil volume weight of the soil sample by a drying weighing method, acquires soil pore volume and soil volume of the soil sample by placing the soil sample into a measuring cup, acquires soil pH value of the soil sample by a ph test paper, acquires water flow velocity by installing an ultrasonic flow meter at a water outlet, acquires water pH value by the ph test paper, acquires water dissolved oxygen concentration by a dissolved oxygen meter, and acquires water turbidity by a turbidity meter.
The environment data analysis module comprises an illumination parameter analysis unit, a soil parameter analysis unit and a water quality parameter analysis unit, and is used for establishing a mathematical model, importing the data transmitted by the environment data acquisition module into the mathematical model, calculating photosynthesis efficiency index, soil characteristic index and water quality characteristic index of each sub-monitoring area, and transmitting the photosynthesis efficiency index, the soil characteristic index and the water quality characteristic index to the comprehensive analysis module.
The illumination parameter analysis unit is used for establishing an illumination parameter analysis model, and the specific mathematical model is as follows:，/>index of photosynthetic efficiency indicating the ith sub-monitoring region,/->Indicating the illumination intensity of the i-th sub-monitoring area, respectively>Indicating the illumination time of the ith sub-monitoring area, < ->Greenhouse light transmittance indicating the ith sub-monitored area, < ->Indicating the crop number of the ith sub-monitoring zone, < ->Indicating the number of sub-monitoring areas,/-, and>representing the area of each sub-monitoring area,/->Other influencing factors representing the photosynthetic efficiency index.
The soil parameter analysis unit is used for establishing a soil parameter analysis model, and the specific mathematical model is as follows:，/>soil characteristic index indicating the ith sub-monitored zone, < ->Indicating soil quality of the ith sub-monitored zone, < ->Represents soil moisture of the ith sub-monitoring zone, < ->Soil volume weight representing the ith sub-monitoring zone, < ->Soil pore volume representing the ith sub-monitored zone, +.>Soil volume representing the ith sub-monitored zone, +.>Soil pH value of the ith sub-monitoring area, < ->Other influencing factors representing the soil characteristic index.
The water quality parameter analysis unit is used for establishing a water quality parameter analysis model, and the specific mathematical model is as follows:，/>indicating the water quality characteristic index of the i-th sub-monitoring zone,/->Indicating the flow rate of the water flow in the ith sub-monitoring zone, etc.>Indicating the pH value of water in the ith sub-monitoring area, < ->Indicating the water dissolved oxygen concentration of the ith sub-monitoring area,/->Indicating the turbidity of the water quality in the ith sub-monitoring zone, < ->Indicating the number of sub-monitoring areas,/-, and>other influencing factors representing the water quality characteristic index.
The biological data acquisition module is used for acquiring the setting parameters, the growth parameters and the disease parameters of each sub-monitoring area and transmitting the acquired data to the biological data processing module.
The setting parameters comprise setting number, bird feeding number, artificial pollination number and insect pollination number, which are marked as follows、/>、/>And +.>The growth parameters included crop sample quality and growth time, decibel mark +.>Anddisease parameters including disease area, leaf area, number of crop diseases and number of crop, respectively marked +.>、、/>And +.>Where i=1, 2 … … n, i represents the i-th sub-monitoring region.
The biological data acquisition module acquires the sample quality of crops by installing a visual sensor right above the crops, namely real number acquisition, bird feeding number acquisition, insect pollination number acquisition, artificial pollination number acquisition, disease spot area acquisition, leaf area acquisition, crop disease number acquisition and crop quantity acquisition, namely, acquiring a crop sample quality in each sub-monitoring area acquisition mode.
The biological data processing module is used for processing the setting parameters, the growth parameters and the disease parameters transmitted by the biological data acquisition module and transmitting the processed data to the biological data analysis module.
The biological data processing module calculates the setting rate of each sub-monitoring area through setting parameters, and the specific mathematical model is as follows:，/>indicating the firmness rate of the ith sub-monitored zone, < ->Indicating the number of firmness of the ith sub-monitoring area, etc.>Representing the ith sub-Monitoring the birds feeding number of the area, +.>Indicating the number of artificial pollinations, < +.>The insect pollination number of the ith sub-monitoring area is represented, the growth speed of each sub-monitoring area is calculated through growth parameters, and the specific mathematical model is as follows: />，/>Indicating the growth rate of the ith sub-monitored area, etc.>Crop sample quality indicating the ith sub-monitoring area,/->Representing the growth time of the ith sub-monitoring area, and calculating the disease index of each sub-monitoring area through disease parameters, wherein a specific mathematical model is as follows: />，/>Indicating the index of the condition of the ith sub-monitored zone, < ->Represents the lesion area of the ith sub-monitoring area, < ->Represents the leaf area of the ith sub-monitoring zone, < ->Indicating the number of crop diseases in the ith sub-monitoring area,/-, for example>Indicating the crop number in the ith sub-monitored zone.
The biological data analysis module is used for establishing a biological data analysis model, importing the data transmitted by the biological data processing module into the biological data analysis model, calculating the crop health index of each sub-monitoring area, and transmitting the crop health index to the comprehensive analysis module.
The biological data analysis model is specifically expressed as:，/>crop health index indicating the ith sub-monitoring zone, < ->Indicating the firmness rate of the ith sub-monitored zone, < ->Indicating the growth rate of the ith sub-monitored area, etc.>Indicating the index of the condition of the ith sub-monitored zone, < ->Other influencing factors representing the crop health index.
The biological data analysis model is combined into a crop health index mathematical model by setting the setting rate, the growth speed and the disease index, so that the influence trend of factors of the setting rate, the growth speed and the disease index on a final result in the embodiment is reflected, and the visual influence of the mathematical model on the system is maximally presented.
The comprehensive analysis module is used for establishing a comprehensive analysis model, importing the data transmitted by the biological data analysis module and the environmental data analysis module into the comprehensive analysis model, calculating the comprehensive optimization index of the target crop planting area, and transmitting the comprehensive optimization index to the intelligent early warning module.
The comprehensive analysis model is specifically expressed as:，/>comprehensive optimization index representing the area of planting the target crop, < >>Crop health index indicating the ith sub-monitoring zone, < ->Index of photosynthetic efficiency indicating the ith sub-monitoring region,/->Soil characteristic index indicating the ith sub-monitored zone, < ->Indicating the index of the water quality characteristics of the i-th sub-monitoring zone.
The intelligent early warning module is used for carrying out intelligent early warning on the environment of the target crop planting area according to the comprehensive optimization index and the comprehensive optimization index preset value of the target crop planting area, which are transmitted by the comprehensive analysis module.
The preset value of the comprehensive optimization index is marked asWhen->When the preset value of the comprehensive optimization index is smaller than or equal to the comprehensive optimization index of the target crop planting area, the environment of the target crop planting area is normal, the monitoring of each sub-monitoring area is kept, and when->When the comprehensive optimization index preset value is larger than the target crop plantingAnd (5) comprehensively optimizing the index of the region, and sending out an early warning signal when the environment of the target crop planting region is abnormal.
According to the invention, a target crop planting area is divided into sub-monitoring areas and numbered through a monitoring area dividing module, illumination parameters, soil parameters and water quality parameters of the sub-monitoring areas are collected through an environment data collecting module, photosynthesis efficiency indexes, soil characteristic indexes and water quality characteristic indexes of the sub-monitoring areas are calculated through an environment data analyzing module, setting parameters, growth parameters and disease parameters of the sub-monitoring areas are collected through a biological data collecting module, data transmitted by the biological data collecting module are processed through a biological data processing module, crop health indexes of the sub-monitoring areas are calculated through a biological data analyzing module, comprehensive optimization indexes of the target crop planting areas are calculated through a comprehensive analyzing module, and intelligent early warning is carried out on the environment of the target crop planting area through an intelligent early warning module.
According to the intelligent monitoring system, data acquisition and analysis are carried out on a target crop planting area from two aspects of environment data and biological data, and finally, comprehensive analysis is carried out on the data to realize intelligent monitoring on the environment.
Secondly: in the drawings of the disclosed embodiments, only the structures related to the embodiments of the present disclosure are referred to, and other structures can refer to the common design, so that the same embodiment and different embodiments of the present disclosure can be combined with each other under the condition of no conflict;
finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (9)
1. An environmental intelligent monitoring system based on thing networking, its characterized in that includes:
the monitoring area dividing module is used for determining a target crop planting area as a target monitoring area, dividing sub-monitoring areas with equal areas in the target monitoring area for sampling investigation, and marking the sub-monitoring areas as 1 and 2 … … n in sequence;
the environment data acquisition module is used for acquiring illumination parameters, soil parameters and water quality parameters of each sub-monitoring area and transmitting acquired data to the environment data analysis module;
the environment data analysis module comprises an illumination parameter analysis unit, a soil parameter analysis unit and a water quality parameter analysis unit, and is used for establishing a mathematical model, importing the data transmitted by the environment data acquisition module into the mathematical model, calculating photosynthesis efficiency index, soil characteristic index and water quality characteristic index of each sub-monitoring area, and transmitting the photosynthesis efficiency index, the soil characteristic index and the water quality characteristic index to the comprehensive analysis module;
the biological data acquisition module is used for acquiring the setting parameters, the growth parameters and the disease parameters of each sub-monitoring area and transmitting the acquired data to the biological data processing module;
the biological data processing module is used for processing the setting parameters, the growth parameters and the disease parameters transmitted by the biological data acquisition module and transmitting the processed data to the biological data analysis module;
the biological data analysis module is used for establishing a biological data analysis model, importing the data transmitted by the biological data processing module into the biological data analysis model, calculating the crop health index of each sub-monitoring area, and transmitting the crop health index to the comprehensive analysis module;
the comprehensive analysis module is used for establishing a comprehensive analysis model, importing the data transmitted by the biological data analysis module and the environmental data analysis module into the comprehensive analysis model, calculating the comprehensive optimization index of the target crop planting area, and transmitting the comprehensive optimization index to the intelligent early warning module;
the intelligent early warning module is used for carrying out intelligent early warning on the environment of the target crop planting area according to the comprehensive optimization index of the target crop planting area and the preset value of the comprehensive optimization index, which are transmitted by the comprehensive analysis module.
2. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the illumination parameters comprise illumination intensity, illumination time, greenhouse light transmittance and crop quantity, which are respectively marked as、/>、/>And +.>The soil parameters include soil quality, soil humidity, soil volume weight, soil pore volume, soil volume and soil pH value, respectively marked as +.>、/>、/>、/>、/>And +.>The water quality parameters comprise water flow rate, water pH value, water dissolved oxygen concentration and water turbidity, respectivelyMarked as->、/>、/>And +.>Where i=1, 2 … … n, i represents the i-th sub-monitoring region;
the setting parameters comprise setting number, bird feeding number, artificial pollination number and insect pollination number, which are marked as follows、、/>And +.>The growth parameters included crop sample quality and growth time, decibel mark +.>And->Disease parameters including disease area, leaf area, number of crop diseases and number of crop, respectively marked +.>、/>、And +.>Where i=1, 2 … … n, i represents the i-th sub-monitoring region.
3. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the environment data acquisition module acquires illumination intensity and illumination time by installing an illumination intensity sensor and a timer in a greenhouse, acquires greenhouse light transmittance by installing a light transmittance sensor on the surface of the greenhouse, acquires the quantity of crops by installing a visual sensor right above the crops, acquires a soil sample by a soil collector, acquires the soil quality, the soil humidity and the soil volume weight of the soil sample by a drying weighing method, acquires the soil pore volume and the soil volume of the soil sample by placing the soil sample in a measuring cup, acquires the soil pH value of the soil sample by a ph test paper, acquires the flow velocity of water flow by installing an ultrasonic flow meter at a water outlet, acquires the pH value of water by a ph test paper, acquires the concentration of water dissolved oxygen by a dissolved oxygen meter, and acquires the turbidity of water by a turbidity meter;
the biological data acquisition module acquires the sample quality of crops by installing a visual sensor right above the crops, namely real number acquisition, bird feeding number acquisition, insect pollination number acquisition, artificial pollination number acquisition, disease spot area acquisition, leaf area acquisition, crop disease number acquisition and crop quantity acquisition, namely, acquiring a crop sample quality in each sub-monitoring area acquisition mode.
4. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the illumination parameter analysis unit is used for establishing an illumination parameter analysis model, and the specific mathematical model is as follows:，/>index of photosynthetic efficiency indicating the ith sub-monitoring region,/->Indicating the illumination intensity of the i-th sub-monitoring area, respectively>Indicating the illumination time of the ith sub-monitoring area, < ->Greenhouse light transmittance indicating the ith sub-monitored area, < ->Indicating the crop number of the ith sub-monitoring zone, < ->Indicating the number of sub-monitoring areas,/-, and>representing the area of each sub-monitoring area,/->Other influencing factors representing the photosynthetic efficiency index.
5. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the soil parameter analysis unit is used for establishing a soil parameter analysis model, and the specific mathematical model is as follows:，/>soil characteristic index indicating the ith sub-monitored zone, < ->Indicating soil quality of the ith sub-monitored zone, < ->Represents soil moisture of the ith sub-monitoring zone, < ->Soil volume weight representing the ith sub-monitoring zone, < ->Soil pore volume representing the ith sub-monitored zone, +.>Soil volume representing the ith sub-monitored zone, +.>Soil pH value of the ith sub-monitoring area, < ->Other influencing factors representing the soil characteristic index.
6. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the water quality parameter analysis unit is used for establishing a water quality parameter analysis model, and the specific mathematical model is as follows:，/>indicating the water quality characteristic index of the i-th sub-monitoring zone,/->Indicating the flow rate of the water flow in the ith sub-monitoring zone, etc.>Indicating the pH value of water in the ith sub-monitoring area, < ->Indicating the water dissolved oxygen concentration of the ith sub-monitoring area,/->Indicating the turbidity of the water quality in the ith sub-monitoring zone, < ->Indicating the number of sub-monitoring areas,/-, and>other influencing factors representing the water quality characteristic index.
7. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the biological data analysis model is specifically expressed as:，/>crop health index indicating the ith sub-monitoring zone, < ->Indicating the firmness rate of the ith sub-monitored zone, < ->Indicating the growth rate of the ith sub-monitored area, etc.>Indicating the index of the condition of the ith sub-monitored zone, < ->Other influencing factors representing the crop health index.
8. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the comprehensive analysis model is specifically expressed as:，/>comprehensive optimization index representing the area of planting the target crop, < >>Crop health index indicating the ith sub-monitoring zone, < ->Index of photosynthetic efficiency indicating the ith sub-monitoring region,/->Soil characteristic index indicating the ith sub-monitored zone, < ->Indicating the index of the water quality characteristics of the i-th sub-monitoring zone.
9. The intelligent environmental monitoring system based on the internet of things according to claim 1, wherein: the preset value of the comprehensive optimization index is marked asWhen->When the preset value of the comprehensive optimization index is smaller than or equal to the comprehensive optimization index of the target crop planting area, the environment of the target crop planting area is normal,the monitoring of each sub-monitoring area is maintained when +.>And when the preset value of the comprehensive optimization index is larger than the comprehensive optimization index of the target crop planting area, indicating that the environment of the target crop planting area is abnormal, sending out an early warning signal.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117829381A (en) * | 2024-03-05 | 2024-04-05 | 成都农业科技职业学院 | Agricultural greenhouse data optimization acquisition system based on Internet of things |
| CN117891859A (en) * | 2024-03-15 | 2024-04-16 | 山东盛途互联网科技有限公司 | Data processing method and system for industrial Internet of things |
| CN117973803A (en) * | 2024-03-28 | 2024-05-03 | 山东盛途互联网科技有限公司 | Intelligent management system for realizing design and production of communication equipment based on 5G technology |
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| CN117891859A (en) * | 2024-03-15 | 2024-04-16 | 山东盛途互联网科技有限公司 | Data processing method and system for industrial Internet of things |
| CN117891859B (en) * | 2024-03-15 | 2024-05-28 | 山东盛途互联网科技有限公司 | Data processing method and system for industrial Internet of things |
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