CN110727301B - Intelligent early warning method and system for environment - Google Patents
Intelligent early warning method and system for environment Download PDFInfo
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Abstract
The application provides an environment intelligent early warning method and system, which comprises the steps of obtaining environment detection data of target crops, types of the target crops and a growth stage of the target crops; extracting a corresponding early warning model from a preset environmental data early warning model library according to the type and the growth stage of the target crop; analyzing whether the target crop has an early warning precondition or not according to the early warning model; if the target crop has the early warning precondition, analyzing whether various environmental data in the environmental detection data meet the early warning precondition; if various environmental data in the environmental detection data meet the early warning precondition, judging an early warning state, and starting a corresponding warning device to give an early warning prompt; the environment can be warned more accurately.
Description
Technical Field
The application relates to the technical field of environmental monitoring, in particular to an intelligent early warning method and system for an environment.
Background
With the development of the internet of things technology, agriculture also gradually develops to automation, intellectualization and remote. By using the technology of the Internet of things, the growth environment of things can be monitored, and the growth environment of things can be better controlled. When the growth environment of crops is monitored, if the detected environmental data exceed the set threshold value, the alarm device can be used for alarming. However, in the above manner, when a certain environmental parameter in the greenhouse reaches a set threshold value, the environmental parameter is generally reminded of failing to reach the standard or exceeding a normal state, influence relations among various environmental parameters are not considered, and an early warning result is not accurate enough.
Disclosure of Invention
The application aims to provide an environment intelligent early warning method and system, which are used for achieving the technical effect of early warning on a more accurately centered crop growth environment.
In a first aspect, the application provides an intelligent environmental early warning method, which includes acquiring environmental detection data of a target crop, and a type and a growth stage of the target crop; extracting a corresponding early warning model from a preset environmental data early warning model library according to the type and the growth stage of the target crop; analyzing whether an early warning precondition exists in the target crop according to the early warning model; the early warning precondition is set according to the relevance among various types of environmental data in the environmental detection data; if the early warning precondition exists in the target crop, analyzing whether various types of environmental data in the environmental detection data meet the early warning precondition; the method comprises the following steps: when one item of environmental data is abnormal and whether early warning is needed to be determined, analyzing whether the state of the environmental data influenced by the abnormal environmental data meets the conditions set in the precondition of the environmental data; if various environmental data in the environmental detection data meet the early warning precondition, judging an early warning state, and starting a corresponding warning device to give an early warning prompt; the environmental data are changed in stages, and the execution time of the early warning model is divided into 1 or more different time periods in the whole day.
In the implementation process, the control terminal firstly acquires information such as environment detection data of the target crop, the type and the growth stage of the target crop and the like through the corresponding detection device, and then extracts a corresponding early warning model from a preset environment data early warning model library according to the type and the growth stage of the target crop; analyzing whether the target crop has an early warning precondition or not according to the early warning model, and if the early warning precondition exists, analyzing whether various environmental data in the environmental detection data meet the early warning precondition or not; judging the early warning state under the condition that various environmental data in the environmental detection data meet the early warning precondition, and controlling an alarm device to perform early warning prompt; the accuracy of the early warning prompt result is improved.
Further, the step of analyzing whether the various types of environmental data in the environmental detection data satisfy the pre-warning precondition further includes: whether various types of environmental data in preconditions which can affect abnormal environmental data are in a set interval range meeting the standard or not is analyzed.
Further, the method further comprises: establishing the early warning model according to the type of the crop, the growth stage of the crop and the environment standard required by each growth stage of the crop; and establishing the environmental data early warning model library according to the early warning models corresponding to various types of crops.
In the implementation process, the early warning model is established according to the type of the crop, the growth stage of the crop and the environment standard required by the crop in each growth stage, and then the early warning models corresponding to various types of crops are integrated to form an environment data early warning model library capable of realizing early warning on multiple growth stages of various crops.
Further, the method further comprises: setting the execution time of the early warning model at regular time according to a preset execution time period; the step of analyzing whether the target crop has the early warning precondition according to the early warning model further comprises the following steps: and analyzing whether the early warning model is in the execution time period, and if the early warning model is not in the execution time period, ending the early warning process.
In the implementation process, considering that the environmental parameters in the greenhouse generally change in a staged manner, in order to reduce power consumption, an execution time period of the early warning model can be set, and early warning analysis is continued only when the execution time period of the early warning model is reached.
In a second aspect, the present application provides an intelligent early warning system for environment, comprising environment detection devices disposed in a plurality of greenhouses; the control terminal is in communication connection with the environment detection device; the alarm device is connected with the control terminal; the environment detection device is used for detecting environment detection data of a target crop; the control terminal is used for acquiring the environment detection data, the type and the growth stage of the target crop; extracting a corresponding early warning model from a preset environmental data early warning model library according to the type and the growth stage of the target crop; analyzing whether an early warning precondition exists in the target crop according to the early warning model; if the early warning precondition exists in the target crop, analyzing whether various types of environmental data in the environmental detection data meet the early warning precondition; the method comprises the following steps: when one item of environmental data is abnormal and whether early warning is needed to be determined, analyzing whether the state of the environmental data influenced by the abnormal environmental data meets the conditions set in the precondition of the environmental data; if various environmental data in the environmental detection data meet the early warning precondition, judging an early warning state, and starting a corresponding warning device to give an early warning prompt; the environmental data are changed in stages, and the execution time of the early warning model is divided into 1 or more different time periods in the whole day.
In the implementation process, the environment detection device detects and obtains environment detection data in the greenhouse; the control terminal acquires the environment detection data, the type and the growth stage of the target crop, and then extracts a corresponding early warning model from a preset environment data early warning model library according to the type and the growth stage of the target crop; analyzing whether the target crop has an early warning precondition or not according to the early warning model; the early warning precondition is set according to the relevance of various types of environment data in the environment detection data. When various environmental data in the environmental detection data meet the pre-warning condition, judging the pre-warning state, and controlling an alarm device to give a pre-warning prompt; the early warning result is more accurate.
Further, the environment detection device comprises an illumination sensor, a carbon dioxide concentration sensor and a temperature sensor.
Furthermore, the alarm device comprises at least one of a voice alarm, an audible and visual alarm and a short message module.
In the implementation process, the alarm device comprises at least one of a voice alarm, a sound-light alarm and a short message module, and voice prompt can be carried out through the voice alarm when early warning is required; and the audible and visual alarm is used for audible and visual alarm, and the short message module is used for sending a notification short message to the mobile phone of the operator so as to inform the relevant operator in time.
Furthermore, the environment intelligent early warning system also comprises an image recognition device used for recognizing the type and the growth stage of the target crop.
In the implementation process, the environment intelligent early warning system is also provided with an image recognition device, and the type and the growth stage of crops can be automatically recognized through the image recognition device.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a general flow chart of an environment intelligent early warning method provided in an embodiment of the present application;
fig. 2 is a structural block diagram of an environment intelligent early warning system provided in the embodiment of the present application.
Icon: 10-an environment intelligent early warning system; 100-a control terminal; 200-an alarm device; 210-a voice alarm; 220-short message module; 230-audible and visual alarm; 300-a display; 400-an environment detection device; 410-an illumination sensor; 420-a carbon dioxide concentration sensor; 430-a temperature sensor; 500-image recognition means; 510-a camera; 520-a processor; 530 — memory.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
The applicant researches and discovers that the existing environment early warning system generally gives an alarm when a certain environmental parameter in a greenhouse exceeds a set threshold value or is lower than the set threshold value, but the implementation mode does not consider the mutual influence relation among various environmental parameters in the environment, so that the early warning result is not very accurate. Therefore, in order to perform early warning prompt more accurately, embodiments of the present application provide an environment intelligent early warning method and system, and the specific content thereof is as follows.
Referring to fig. 1, fig. 1 is a general flow chart of an environment intelligent warning method according to an embodiment of the present disclosure.
The intelligent early warning method for the environment provided by the embodiment of the application considers the existence of correlation among a plurality of environment parameters in the environment, so that the early warning method is provided, and the specific content is as follows.
Step S101, obtaining environment detection data of target crops, types and growth stages of the target crops.
The environment detection data can be acquired through various sensors arranged in the device. For example, a temperature sensor may be used to detect ambient temperature; the intensity of light is detected using a light sensor, and the concentration of carbon dioxide is detected using a carbon dioxide concentration sensor.
The type and the growth stage of the target crop can obtain the image of the target crop through the camera, and then the operator performs corresponding configuration according to the growth condition of the target crop. In another embodiment, the type and growth stage of the target crop may also be obtained by first obtaining an image of the target crop by using a camera, and then performing image recognition in a processor or a control terminal by using a deep learning algorithm to obtain the type and growth stage of the target crop.
Considering that the environmental parameters generally change in a stepwise manner, the sensor can be started at regular time according to a set time period to acquire data when acquiring environmental data. For example, the sensor can be started to acquire data at regular time in three time periods of 06:00-08:00, 12:00-16:00 and 16:00-18:00, and by the mode, the power consumption of the sensor can be reduced while early warning is performed by acquiring data. The sensor may also be maintained in an on state at all times if ambient temperature is to be sensed throughout the day.
And S102, extracting a corresponding early warning model from a preset environmental data early warning model library according to the type and the growth stage of the target crop.
Before the early warning system is used, an early warning model of the crop can be established according to the type of the crop, the growth stage of the crop and the environment standard required by each growth stage of the crop, then the early warning models of various crops are integrated, an environment data early warning model library is established, and an early warning model library capable of carrying out environment early warning on various crops is formed.
And S103, analyzing whether the target crop has an early warning precondition or not according to the early warning model.
After the early warning model corresponding to the target crop is extracted according to the type and the growth stage of the target crop, whether the early warning model has an early warning precondition or not can be analyzed; the pre-warning condition can be set according to the relevance among various types of environmental data in the environmental detection data. The preconditions may be set to the following two types:
1) environmental state: when a certain item of environmental data needs to be pre-warned, whether the state of a certain condition set in the affected precondition meets the set condition is analyzed.
2) Data interval: and setting a data interval of the environmental detection data corresponding to the precondition, and performing early warning when the environmental detection data is in a specified interval or outside the specified interval.
It should be noted that the pre-warning condition may not be set.
And step S104, if the early warning precondition exists in the target crop, analyzing whether various environmental data in the environmental detection data meet the early warning precondition.
For example, the carbon dioxide concentration in the greenhouse environment affects the temperature in the greenhouse, so when the carbon dioxide concentration early warning prompt is performed, the precondition can be set according to the environmental standard of each growth stage of the crop, and when the temperature in the greenhouse reaches the set threshold, the carbon dioxide concentration early warning prompt is performed.
In addition, the illumination intensity can also influence the carbon dioxide concentration in the greenhouse, when the carbon dioxide concentration needs to be warned, whether the detected illumination intensity is in the set interval range meeting the standard or not can be analyzed, and if the illumination intensity is in the set interval range, the warning state of the carbon dioxide concentration is judged and warning prompt is carried out. Meanwhile, the data interval of the precondition can be set to be an interval range which does not accord with the standard, and when the illumination intensity is not in the interval range which does not accord with the standard, the early warning state of the carbon dioxide concentration is judged and early warning prompt is carried out.
It should be noted that the number of preconditions is not limited to one, and a plurality of preconditions may be set according to the influence relationship between various types of environmental data.
And S105, if various environmental data in the environmental detection data meet the early warning precondition, judging an early warning state, and starting a corresponding alarm device to perform early warning prompt.
When various environmental data in the environmental detection data meet the corresponding precondition, the specific early warning state of the data can be analyzed, and an alarm device is started to give an early warning prompt.
For example, when the carbon dioxide concentration is early-warned, if the illumination intensity meets the interval range of the set standard and the carbon dioxide concentration is too low, the warning device is started to inform operators that the carbon dioxide concentration in the greenhouse is too low, so that the carbon dioxide gas fertilizer can be used for supplementing in time; when carrying out the early warning of carbon dioxide concentration, if illumination intensity accords with the interval scope that sets up the standard, and carbon dioxide concentration is too high this moment, then just start alarm device, inform the too high of carbon dioxide concentration in the operation personnel big-arch shelter to in time ventilate and handle.
Please refer to fig. 2, fig. 2 is a schematic structural diagram of an environment intelligent warning system according to an embodiment of the present disclosure.
The environment intelligent early warning system 10 provided by the embodiment of the application comprises a control terminal 100; an environment detection device 400 of a plurality connected to the control terminal 100; the alarm device 200 is connected to the control terminal 100. The environment detection device 400 sends detected environment detection data to the control terminal 100, the control terminal 100 obtains the detection data, meanwhile, the control terminal 100 reads information such as the type and growth stage of a target crop stored in the control terminal 100, then extracts a corresponding early warning model from an established environment data early warning model library according to the type and growth stage of the target crop, analyzes whether an early warning precondition exists in the target crop or not according to the early warning model, and analyzes whether various environment data in the environment detection data meet the early warning precondition or not if the early warning precondition exists in the target crop; if various environmental data in the environmental detection data meet the corresponding pre-warning precondition, the pre-warning state is judged, and the corresponding warning device 200 is started to perform pre-warning prompt.
In an implementation mode, the intelligent environment early warning method can be applied to a greenhouse. The environment detection device 400 includes an illumination sensor 410, a carbon dioxide concentration sensor 420, a temperature sensor 430 (e.g., a soil temperature sensor, an air temperature sensor, etc.); the control terminal 100 may be a mobile phone, a notebook computer, or other electronic devices capable of implementing the same or similar functions. The alarm device 200 can be selected from a voice alarm 210, a short message module 220, an audible and visual alarm 230, and the like, and when early warning prompt is required, the voice alarm 210 can be used for broadcasting corresponding voice alarm information, and the audible and visual alarm 230 can be used for audible and visual alarm; the notification information may also be sent to the operator through the short message module 220 (e.g., GSM short message module).
The intelligent early warning system 10 is also provided with an image recognition device 500 and a display 300 connected with the control terminal 100. The display 300 is used for displaying the detection data of the environment detection apparatus 400, and may be an LCD display or an LED display. Image recognition device 500 includes a camera 510, a processor 520, and a memory 530; the camera 510 is used for acquiring an image of a target crop; the processor 520 is used for analyzing the images and identifying the type and the growth stage of the target crop; the memory 530 is used for storing programs, images, types and growth stages of target crops, and the like. The type and growth stage of the target crop can be acquired by the camera 510 of the image recognition device 500, and then the processor 520 recognizes the image and sends the recognition result to the control terminal 100. It should be noted that the type and the growth stage of the target crop may also be obtained by only using the set camera 510 to collect an image, then sending the collected image to the control terminal 100, and the control terminal 100 identifies the image to analyze the type and the growth stage of the target crop.
It should be noted that the foregoing embodiments are only some implementable manners provided by the present application, and the environment intelligent warning method provided by the present application is not limited to a greenhouse, and may also be applied to other environments, such as a field and a farm. Meanwhile, the type of the sensor can be selected according to the actual application requirements of the actual application place. For example, a soil humidity sensor, a soil temperature sensor, a soil fertility detector and the like can be added into the greenhouse according to actual needs; the PM2.5 sensor can also be added in the field and other places.
In summary, the embodiment of the present application provides an environment intelligent early warning method and system, including acquiring environment detection data of a target crop, a type of the target crop and a growth stage; extracting a corresponding early warning model from a preset environmental data early warning model library according to the type and the growth stage of the target crop; analyzing whether the target crop has an early warning precondition or not according to the early warning model; setting an early warning precondition according to the relevance among various types of environmental data in the environmental detection data; if the target crop has the early warning precondition, analyzing whether various environmental data in the environmental detection data meet the early warning precondition; if various environmental data in the environmental detection data meet the early warning precondition, judging an early warning state, and starting a corresponding warning device to give an early warning prompt; the environment can be warned more accurately.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. An environment intelligent early warning method is characterized by comprising the following steps:
acquiring environmental detection data of a target crop, and the type and the growth stage of the target crop;
extracting a corresponding early warning model from a preset environmental data early warning model library according to the type and the growth stage of the target crop;
analyzing whether an early warning precondition exists in the target crop according to the early warning model; the early warning precondition is set according to the relevance among various types of environmental data in the environmental detection data;
if the early warning precondition exists in the target crop, analyzing whether various types of environmental data in the environmental detection data meet the early warning precondition; the method comprises the following steps: when one item of environmental data is abnormal and whether early warning is needed to be determined, analyzing whether the state of the environmental data influenced by the abnormal environmental data meets the conditions set in the precondition of the environmental data;
if various environmental data in the environmental detection data meet the early warning precondition, judging an early warning state, and starting a corresponding warning device to give an early warning prompt;
the environmental data are changed in stages, and the execution time of the early warning model is divided into 1 or more different time periods in the whole day.
2. The method of claim 1, wherein the step of analyzing whether the various types of environmental data in the environmental test data satisfy the pre-warning precondition further comprises: whether various types of environmental data in preconditions which can affect abnormal environmental data are in a set interval range meeting the standard or not is analyzed.
3. The method of claim 1, further comprising: establishing the early warning model according to the type of the crop, the growth stage of the crop and the environment standard required by each growth stage of the crop; and establishing the environmental data early warning model library according to the early warning models corresponding to the crops of multiple types.
4. The method of claim 3, further comprising: setting the execution time of the early warning model at regular time according to a preset execution time period; the step of analyzing whether the target crop has the early warning precondition according to the early warning model further comprises the following steps: and analyzing whether the early warning model is in the execution time period, and if the early warning model is not in the execution time period, ending the early warning process.
5. An environmental intelligent early warning system, comprising: the environment detection devices are arranged in the plurality of greenhouses; the control terminal is in communication connection with the environment detection device; the alarm device is connected with the control terminal; the environment detection device is used for detecting environment detection data of a target crop; the control terminal is used for acquiring the environment detection data, the type and the growth stage of the target crop; extracting a corresponding early warning model from a preset environmental data early warning model library according to the type and the growth stage of the target crop; analyzing whether an early warning precondition exists in the target crop according to the early warning model; if the early warning precondition exists in the target crop, analyzing whether various types of environmental data in the environmental detection data meet the early warning precondition; the method comprises the following steps: when one item of environmental data is abnormal and whether early warning is needed to be determined, analyzing whether the state of the environmental data influenced by the abnormal environmental data meets the conditions set in the precondition of the environmental data; if various environmental data in the environmental detection data meet the early warning precondition, judging an early warning state, and starting a corresponding warning device to give an early warning prompt; the environmental data are changed in stages, and the execution time of the early warning model is divided into 1 or more different time periods in the whole day.
6. The intelligent early warning system for environment according to claim 5, wherein the environment detection device comprises a light sensor, a carbon dioxide concentration sensor and a temperature sensor.
7. The intelligent early warning system for environment according to claim 5, wherein the alarm device comprises at least one of a voice alarm, an audible and visual alarm and a short message module.
8. The environmental intelligent warning system according to claim 5, further comprising: and the image recognition device is connected with the control terminal and is used for recognizing the type and the growth stage of the target crop.
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| CN102411388B (en) * | 2011-09-05 | 2013-03-20 | 西北农林科技大学 | System and method for precisely controlling carbon dioxide concentration in greenhouse |
| CN104007748A (en) * | 2014-06-23 | 2014-08-27 | 中央民族大学 | Control method and system for greenhouse |
| CN105700595A (en) * | 2016-03-15 | 2016-06-22 | 深圳市前海博森生物科技有限公司 | Plant factory environment monitoring system and method thereof based on Android platform |
| CN106645155A (en) * | 2016-12-29 | 2017-05-10 | 深圳前海弘稼科技有限公司 | Method and device for monitoring plant growth status based on greenhouse environment |
| CN107844089A (en) * | 2017-10-31 | 2018-03-27 | 深圳春沐源控股有限公司 | A kind of method, system and Cultivate administration system for planting early warning |
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