CN115761482A - Wisdom agricultural environment monitoring system based on 5G technique - Google Patents
Wisdom agricultural environment monitoring system based on 5G technique Download PDFInfo
- Publication number
- CN115761482A CN115761482A CN202211356639.4A CN202211356639A CN115761482A CN 115761482 A CN115761482 A CN 115761482A CN 202211356639 A CN202211356639 A CN 202211356639A CN 115761482 A CN115761482 A CN 115761482A
- Authority
- CN
- China
- Prior art keywords
- module
- crops
- insect
- pests
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 56
- 238000000034 method Methods 0.000 title abstract description 12
- 241000607479 Yersinia pestis Species 0.000 claims abstract description 111
- 241000238631 Hexapoda Species 0.000 claims abstract description 87
- 238000012545 processing Methods 0.000 claims abstract description 37
- 238000004891 communication Methods 0.000 claims abstract description 31
- 238000007664 blowing Methods 0.000 claims abstract description 25
- 239000000575 pesticide Substances 0.000 claims abstract description 22
- 238000005507 spraying Methods 0.000 claims abstract description 19
- 238000005516 engineering process Methods 0.000 claims abstract description 15
- 230000009286 beneficial effect Effects 0.000 claims description 22
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 20
- 239000002689 soil Substances 0.000 claims description 19
- 230000005484 gravity Effects 0.000 claims description 13
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 10
- 239000001569 carbon dioxide Substances 0.000 claims description 10
- 238000003860 storage Methods 0.000 claims description 9
- 238000005303 weighing Methods 0.000 claims description 8
- 239000007921 spray Substances 0.000 claims description 6
- 238000003062 neural network model Methods 0.000 claims description 5
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000013480 data collection Methods 0.000 claims 1
- 230000008569 process Effects 0.000 abstract description 2
- 230000009545 invasion Effects 0.000 abstract 1
- 230000007613 environmental effect Effects 0.000 description 7
- 239000003814 drug Substances 0.000 description 6
- 238000005286 illumination Methods 0.000 description 6
- 238000012271 agricultural production Methods 0.000 description 5
- 230000000877 morphologic effect Effects 0.000 description 3
- 238000003916 acid precipitation Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 235000015097 nutrients Nutrition 0.000 description 2
- 229910001220 stainless steel Inorganic materials 0.000 description 2
- 239000010935 stainless steel Substances 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000004888 barrier function Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 230000005389 magnetism Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 238000004171 remote diagnosis Methods 0.000 description 1
- 230000001846 repelling effect Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
- Y02A40/25—Greenhouse technology, e.g. cooling systems therefor
Landscapes
- Catching Or Destruction (AREA)
Abstract
The invention relates to the field of agricultural environment monitoring, and particularly discloses a 5G technology-based intelligent agricultural environment monitoring system which comprises an environment monitoring module, a 5G communication module, an image processing module, a data processing module, an insect recognition module, a controller module, a pesticide spraying module, a blowing module and an alarm module, wherein the environment monitoring module is used for monitoring the growing environment around crops, the 5G communication module is used for respectively sending monitored environment image information and data information to the image processing module and the data processing module for processing, the insect recognition module is used for carrying out recognition judgment according to the processed image information and sending the information to the controller module for controlling blowing and pesticide spraying, and the data processing module is used for judging the processed data information and sending the information to the controller module for controlling alarm. The technical scheme of the invention is used for solving the problem that crops are subjected to pest invasion in the growth process and actively intervening pests.
Description
Technical Field
This scheme belongs to agricultural environmental monitoring field, concretely relates to wisdom agricultural environmental monitoring system based on 5G technique.
Background
Wisdom agriculture is to use internet of things to traditional agriculture, and the agricultural production is controlled through mobile platform or computer platform to application sensor and software, makes traditional agriculture more have "wisdom". In addition to accurate sensing, control and decision management, the intelligent agriculture also comprises contents in aspects of agricultural electronic commerce, food source tracing and anti-counterfeiting, agricultural leisure travel, agricultural information service and the like in a broad sense; the intelligent agriculture is to fully apply modern information technology achievements, integrate and apply computer and network technology, internet of things technology, audio and video technology, 3S technology, wireless communication technology and expert intelligence and knowledge, and realize intelligent management such as visual remote diagnosis, remote control, catastrophe early warning and the like of the agriculture; wisdom agriculture is the advanced stage of agricultural production, integrates emerging internet, mobile internet, cloud computing and internet of things technology, realizes intelligent perception, intelligent early warning, intelligent decision, intelligent analysis and expert online guidance of agricultural production environment by means of various sensing nodes (environment temperature and humidity, soil moisture, carbon dioxide, images and the like) and wireless communication networks deployed on agricultural production sites, and provides accurate planting, visual management and intelligent decision for agricultural production.
The Chinese patent of the invention discloses (with the publication number of CN 215217665U) an intelligent agricultural environment monitoring system based on a 5G technology, which comprises an agricultural environment monitoring module, a crop growth monitoring module, a decision system, a fertilizing and irrigating device and a 5G communication module, wherein the agricultural environment monitoring module, the crop growth monitoring module and the fertilizing and irrigating device are all in communication connection with the decision system through the 5G communication module. This scheme monitors the agricultural environment through setting up agricultural environment monitoring module, monitors the growth condition of crops through crops growth monitoring module simultaneously to all transmit decision-making system through 5G communication module, the decision-making system of being convenient for combines the testing result of agricultural environment monitoring module and crops growth monitoring module to make the judgement to the generation condition of crops, and warn, thereby be convenient for people timely understanding the growth condition of crops, so that make corresponding decision-making.
However, the agricultural environment monitoring module and the crop growth monitoring module cannot intervene in the growth environment of crops actively, so that the crops can grow better, and only the growth condition of the crops can be passively monitored. When a large number of pests exist in the growing environment where crops are located, people are reminded to deinsectize only by monitoring and warning, a large amount of time and labor cost can be consumed, and the growth of the crops cannot be guaranteed within a certain time.
Disclosure of Invention
This scheme provides an wisdom agricultural environment monitoring system based on 5G technique for solve crops and face the problem that the pest infringed at the growth in-process, intervene the pest voluntarily, thereby promote the better growth of crops.
In order to achieve the purpose, the scheme provides a 5G technology-based intelligent agricultural environment monitoring system which comprises an environment monitoring module, a 5G communication module, an image processing module, a data processing module, an insect recognition module, a controller module, a medicine spraying module, a blowing module and an alarm module;
the environment monitoring module is used for monitoring the growing environment around crops, and comprises a growing environment image acquisition unit and a growing environment data acquisition unit, the growing environment image acquisition unit is used for acquiring image information of the growing environment of the crops, the growing environment data acquisition unit is used for acquiring data information of the growing environment of the crops, and the image information and the data information are respectively sent to the image processing module and the data processing module through the 5G communication module in a wireless transmission mode;
the image processing module is used for acquiring an insect region in the crop growth environment image information, slicing the insect region to obtain an insect picture, and transmitting the insect picture to the insect identification module through the 5G communication module;
the insect recognition module is used for acquiring insect form information on the insect picture after receiving the insect picture, then inputting the insect form information on the insect picture into a pre-trained neural network model, judging the probability of pests and beneficial pests to obtain the probability information of the pests in the crop growth environment, and sending the probability information of the pests to the controller module through the 5G communication module;
the controller module presets a probability threshold value of pests on crops, when the probability of the pests received by the controller module and sent by the pest identification module is larger than the set probability threshold value, the controller module firstly controls the pesticide spraying module to spray pesticide on the crops, and then controls the blowing module to blow the crops after the pesticide spraying is finished; when the pest probability received by the controller module and sent by the pest identification module is smaller than a set probability threshold value, the blowing module is controlled to blow crops;
the data processing module is used for processing after acquiring data information of the crop growth environment, generating a first data signal and sending the first data signal to the controller module through the 5G communication module when the acquired data information of the crop growth environment is larger than the preset data threshold, and controlling the alarm module to give an alarm after the controller module receives the first data signal;
the alarm module is used for giving an alarm after receiving the instruction of the controller module.
The basic principle of the scheme is as follows: when crops are growing, the environment monitoring module monitors the growing environment around the crops in real time. Firstly, a growing environment image acquisition unit and a growing environment data acquisition unit in the environment monitoring module can respectively acquire image information and data information of a crop growing environment and respectively send the acquired information to an image processing module and a data processing module through a 5G communication module.
The image processing module receives the image information and then automatically acquires the insect region in the image information, the insect region is sliced to obtain an insect picture, and the insect picture is transmitted to the insect identification module through the 5G communication module again. After the insect picture is received by the insect recognition module, insect form information on the insect picture can be obtained, then the insect form information on the insect picture is input into a pre-trained neural network model, probability judgment of pests and beneficial pests is carried out, and probability information of the pests in the crop growth environment is obtained.
And then the probability information of the pests is sent to the controller module through the 5G communication module, and the controller module is used for identifying and judging so as to make a decision. The probability threshold value of pest on the crops is predetermine to the controller module, and the pest probability that receives insect identification module and send when the controller module is greater than the probability threshold value of settlement, just control earlier and spout the medicine module and spout the medicine to crops, and the pest that is located on crops will die after being spouted the medicine water, and the module of blowing is controlled again and is blown crops after spouting the medicine and accomplish for the pest corpse is got rid of from crops. When the controller module receives that the pest probability sent by the pest identification module is smaller than a set probability threshold value, the blowing module is controlled to blow crops. Wind power can temporarily disperse part of pests from crops, so that the crops are protected, and beneficial pests can be prevented from being removed.
The data processing module can preset a data threshold value, and after the data processing module receives the data information, further judgment can be made according to the set data threshold value. The obtained data information of the crop growth environment is larger than a preset data threshold value, a generated data signal is sent to the controller module through the 5G communication module, and after the controller module receives the data signal, the alarm module is controlled to give an alarm, so that people are reminded of paying attention to growth change of crops.
The beneficial effect of this scheme: compared with the prior art, the scheme has the advantages that the high-speed transmission of information can be realized by the aid of the 5G communication module, real-time environment monitoring can be performed on crops conveniently, the environment monitoring module can perform environment monitoring on the crops (namely, alarming is performed by collecting data information beside the crops), accordingly, people are reminded of paying attention to growth changes of the crops, the crops can be actively made to intervene measures when the crops are damaged by pests, and better growth of the crops is protected better.
The image acquisition can know the insect situation around the crops in real time, when the insects on the crops are probably pests, the pests are killed by spraying the pesticide, and the corpses of the pests on the crops are removed in a blowing mode, so that the crops can be protected from being damaged by the pests; when the insect on crops is the beneficial insect with high probability, directly blow away it through blowing, can protect the beneficial insect on the one hand for it helps crops to grow, and on the other hand blows and also can blow away latent pest on the crops, makes crops not receive the infringement of pest in the short time.
The traditional environment monitoring only realizes the function of monitoring the environment around crops and reminds people of paying attention to the growth change of the crops, thereby carrying out corresponding treatment. Although this method can remind people to take measures for treating crops according to different environmental conditions, when people are far away from the crops, pests cannot be killed immediately, so that the crops are prevented from being damaged. For example: when a large amount of pests exist on crops, people have no time to spray pesticides, the crops can be gnawed by the pests, and if the crops are sprayed with the pesticides in advance, a large amount of beneficial pests cannot stay on the crops, so that the growth of the crops can become slow. If people can reach the crops in time for artificial deinsectization, because beneficial insects and pests are gathered on the crops, part of beneficial insects can be damaged while killing the pests, and the growth of the crops is not convenient. Consequently, this scheme can realize intelligent deinsectization according to the insect condition on the crops, intervenes crops voluntarily, clears away the pest promptly, drives beneficial worm to promote the better growth of crops.
Further, the growth environment data acquisition unit comprises sensors for monitoring carbon dioxide, light, noise, wind speed, air temperature, soil temperature and soil PH.
Has the advantages that: can monitor other carbon dioxide of crops, illumination, noise, wind speed, air temperature, soil temperature and soil pH value, come the auxiliary alarm module according to carbon dioxide concentration, illumination intensity, noise decibel, wind speed size, air temperature size, soil temperature size and soil pH value size of difference and report to the police, remind people to pay close attention to the growth situation of crops.
Further, still be equipped with the collection module that is used for collecting the pest on the direction of blowing of module of blowing, be equipped with weighing sensor on the collection module, weighing sensor is used for measuring the pest weight of collecting to give the controller module with gravity signal transmission, discernment judgement after the controller module received gravity signal, the controller module still presets the gravity threshold value, just emptys the pest of collecting the module with control and collect by crops when the controller module discerns that gravity signal is greater than and presets the threshold value.
Has the advantages that: the collection module can realize unified collection of the corpses of the pests, so that on one hand, the cost of artificially collecting the corpses of the pests can be reduced, and on the other hand, the corpses of the pests are collected together, so that birds can be lured to bite the corpses of the pests in the future. When the birds bite the corpses of the pests, the birds can deinsectize the pests for the second time, and the deinsectization efficiency is greatly improved. When the weight of the pest corpse collected in the collecting module exceeds a set threshold value, the controller module controls the collecting module to dump the pest corpse beside crops, and the pest corpse can be used as a nutrient of the crops to help the crops to grow better.
Further, the pest quantity counting module is used for counting the pest quantity collected by the collecting module.
Has the beneficial effects that: the pest quantity counting module can count the pest quantity collected by the collecting module, so that the pest distribution condition beside crops can be known, and the pest killing area and frequency can be increased when the pests are excessive.
Further, the shape information of the insect includes the size, shape and color of the insect.
Has the beneficial effects that: the size, shape and color of the insects on the crops can assist the insect identification module to judge whether the insects are pests more accurately, so that accurate removal is realized.
The crop growth environment data acquisition unit is used for acquiring the image information of the crop growth environment and acquiring the data information of the crop growth environment.
Has the advantages that: the storage module can store the collected data so as to facilitate later analysis and verification.
Further, the controller module is configured to control the alarm module to send an alarm if the first data signal is received again at a time interval after the first data signal is received.
Has the advantages that: the method can prevent the environmental data beside the crops from temporarily rising (for example, the PH value beside the crops rises due to partial acid rain) due to partial reasons, thereby giving an alarm, influencing the decision judgment of people and being not beneficial to the treatment and growth of the crops.
Drawings
FIG. 1 is a logic diagram of an embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
the embodiment is basically as shown in the attached figure 1:
the utility model provides a wisdom agricultural environmental monitoring system based on 5G technique, includes environmental monitoring module, 5G communication module, image processing module, data processing module, insect identification module, controller module, spouts medicine module, bloies module and alarm module.
The environment monitoring module is used for monitoring the growth environment around the crops, and the environment monitoring module includes growth environment image acquisition unit and growth environment data acquisition unit, and growth environment image acquisition unit chooses for use wireless 360 degrees cameras, and this wireless 360 degrees camera setting is by the crops to be connected with 5G communication network, can shoot the image of crops, real-time monitoring. The growth environment data acquisition unit is used for acquiring data information of a crop growth environment, the growth environment data acquisition unit comprises a sensor for monitoring carbon dioxide, illumination, noise, wind speed, air temperature, soil temperature and soil pH value and a sensor for monitoring other environment quantities, specifically, a carbon dioxide transmitter of a Ministry of building, an RS485 analog quantity illuminance tester, a Sayboo RS485 industrial-grade noise sensor, a Shunkda TR-8D soil temperature and humidity recorder and a precise smooth soil pH sensor can be adopted, the sensor can monitor carbon dioxide beside crops, illumination, noise, wind speed, air temperature, soil temperature and soil pH value, the sensor can assist an alarm module to alarm according to different carbon dioxide concentrations, illumination intensity, noise decibels, wind speed, air temperature, soil temperature and soil pH value, and people are reminded to pay attention to the growth condition of the crops. The crop growth environment data acquisition unit is used for acquiring the image information of the crop growth environment and the data information of the crop growth environment. The storage module stores the images and the data information in a cloud storage mode, the cloud storage is safer than the local storage, and once the camera adopting the local storage is lost, the storage card inserted into the machine body is lost, cannot be found back, and also has the danger of privacy disclosure.
The obtained image information and the obtained data information are respectively sent to an image processing module and a data processing module through a 5G network, the image processing module obtains an insect region (namely an activity region of an insect on the crop) in the image information of the crop growth environment, the insect region is sliced to obtain an insect picture, and then the insect picture is transmitted to an insect recognition module through the 5G network again.
After the insect picture is received by the insect recognition module, a morphological target feature extraction method is adopted, insect morphological information on the insect picture is obtained to form an overall outline of the insect, the insect morphological information comprises the size, the shape and the color of the insect and other features capable of distinguishing pests and beneficial insects in other embodiments, and the pests and the beneficial insects have partial differences in size, shape and color, so that the features can assist the insect recognition module in more accurately judging whether the insect is a pest or not, and accurate removal is achieved. The acquired insect form information is input into a pre-trained neural network model, probability judgment of pests and beneficial pests is carried out, probability information (expressed in percentage) of the pests in the crop growth environment is obtained, and the probability information of the pests is sent to a controller module through a 5G communication module.
The probability threshold value of pests on crops is preset to be 70% by the controller module, when the probability of the pests sent by the pest identification module received by the controller module is larger than the set 70%, the pesticide spraying module is powered on to spray pesticide on the crops, and the air blowing module is powered on to blow the crops after pesticide spraying is finished; when the probability that the pest received by the controller module and sent by the pest identification module is less than 70% of the set probability, the controller module directly energizes the blowing module to blow air to the direction of the insects on the crops. The pesticide spraying module and the air blowing module are arranged beside crops, the pesticide spraying module can select an electric spraying pot, pesticide liquid is filled in the spraying pot in advance, and after the controller module sends an instruction to electrify the electric spraying pot, the electric spraying pot automatically sprays pesticide for the crops to kill pests on the crops. The blowing module can be a daily fan, the fan blades of the fan can be 50cm, and the air blown by the fan can meet the requirement of repelling pests. When the controller module sends an instruction to electrify the fan, the fan blows air to crops, and when pests occur, the fan blows the pest corpses to the blowing module to collect the pests in a centralized manner; when beneficial insects are encountered, the wind blown by the fan can disperse the beneficial insects, so that the beneficial insects can survive, can continuously assist the growth of crops later, and can also disperse part of potential pests beside the crops to prevent the crops from being continuously damaged by the pests.
The data processing module presets a data threshold value for acquiring data information of a crop growth environment and then processing the data information, the preset threshold value can be set to be 300-400 PPM in carbon dioxide content, the illumination intensity is 10000-30000LX, the wind speed is 0.0-7.9 m/s, the air temperature is 0-40 ℃, and the PH value of soil is 2.5-9.0, when the acquired data information of the crop growth environment is larger than the preset data threshold value, a first data signal is generated and sent to the controller module through the 5G communication module, and the controller module is used for controlling the alarm module to give an alarm after receiving the first data signal again at intervals. The method can prevent the short-term rise of environmental data beside crops (for example, the pH value beside the crops is raised due to partial acid rain) caused by partial reasons, thereby alarming, influencing the decision judgment of people and being not beneficial to the treatment and growth of the crops.
The alarm module is used for giving an alarm after receiving the instruction of the controller module. The warning module selects LTD-1101J magnetic attraction rotating warning lamp, the warning lamp is welded on the collecting module, when the number of the pests on the pest sticking plate reaches a certain value, the controller module energizes the LTD-1101J magnetic attraction rotating warning lamp to send out warning, and meanwhile, light can flicker. LTD-1101J magnetism is inhaled rotatory warning light and is inhaled and send out the police dispatch newspaper and can help dispersing some pest on the one hand, and on the other hand can remind people in time to pay close attention to the growth state of crops, carries out artifical deinsectization when necessary, comes the growth of better assurance crops.
Still be equipped with the collection module that is used for collecting the pest on the module of blowing's the direction of blowing, the disc that collection module adopted stainless steel material to make, stainless steel have characteristics such as corrosion-resistant, high temperature resistant, can be so that adapt to the growing environment of different crops. The upper surface of the collecting module is disc-shaped, and necking openings are sequentially formed from the upper end to the lower end. An opening and a closed cover are arranged on the necking end, the opening and the closed cover are designed to be circular, and the opening is hinged with the closed cover. The hinge joint is simple in structure compared with other connection modes, and the closing cover can be conveniently opened. The collecting module is also provided with ase:Sub>A weighing sensor, the weighing sensor can be an SQB-A weighing sensor, the SQB-A weighing sensor is used for measuring the weight of the collected pests and transmitting gravity signals to the controller module, and the controller module identifies and judges after receiving the gravity signals. The controller module also presets a gravity threshold value, the gravity threshold value is 1000g, and when the controller module recognizes that the gravity signal value is larger than 1000g, the controller module opens the closing cover on the collection module, so that the pest corpses fall to the soil of crops from the opening of the collection module. The corpse of the pests can be used as a nutrient for crops, and helps the crops to grow better.
The specific using process is as follows: when crops are growing, the environment monitoring module monitors the growing environment around the crops in real time. Firstly, a growing environment image acquisition unit and a growing environment data acquisition unit in the environment monitoring module can respectively acquire image information and data information of a crop growing environment and respectively send the acquired information to an image processing module and a data processing module through a 5G communication module.
The image processing module receives the image information and then automatically acquires the insect region in the image information, the insect region is sliced to obtain an insect picture, and the insect picture is transmitted to the insect identification module through the 5G communication module again. After the insect picture is received by the insect recognition module, insect form information on the insect picture can be obtained, then the insect form information on the insect picture is input into a pre-trained neural network model, probability judgment of pests and beneficial pests is carried out, and probability information of the pests in the crop growth environment is obtained.
And then the probability information of the pests is sent to the controller module through the 5G communication module, and the controller module is used for identifying and judging so as to make a decision. The controller module presets a probability threshold value of pests on crops, when the probability of the pests received by the controller module and sent by the pest identification module is larger than the set probability threshold value, the pesticide spraying module is controlled to spray pesticide on the crops, and after the pesticide spraying is finished, the blowing module is controlled to blow the crops; when the controller module receives that the pest probability sent by the pest identification module is smaller than the set probability threshold value, the blowing module is controlled to blow crops, and pests beside the crops can be killed.
The data processing module can preset a data threshold value, and after the data processing module receives the data information, further judgment can be made according to the set data threshold value. The obtained data information of the crop growth environment is larger than a preset data threshold value, a first data signal is generated and sent to the controller module through the 5G communication module, and after the controller module receives the first data signal, the alarm module is controlled to give an alarm, so that people are reminded of paying attention to growth changes of crops.
The above are merely examples of the present invention, and the present invention is not limited to the field related to this embodiment, and the common general knowledge of the known specific structures and characteristics in the schemes is not described herein too much, and those skilled in the art can know all the common technical knowledge in the technical field before the application date or the priority date, can know all the prior art in this field, and have the ability to apply the conventional experimental means before this date, and those skilled in the art can combine their own ability to perfect and implement the scheme, and some typical known structures or known methods should not become barriers to the implementation of the present invention by those skilled in the art in light of the teaching provided in the present application. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several variations and modifications can be made, which should also be considered as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the utility of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (7)
1. An intelligent agricultural environment monitoring system based on a 5G technology is characterized by comprising an environment monitoring module, a 5G communication module, an image processing module, a data processing module, an insect identification module, a controller module, a pesticide spraying module, a blowing module and an alarm module;
the environment monitoring module is used for monitoring the growing environment around crops, the environment monitoring module comprises a growing environment image acquisition unit and a growing environment data acquisition unit, the growing environment image acquisition unit is used for acquiring image information of the growing environment of the crops, the growing environment data acquisition unit is used for acquiring data information of the growing environment of the crops, and the image information and the data information are respectively sent to the image processing module and the data processing module through the 5G communication module in a wireless transmission mode;
the image processing module is used for acquiring an insect region in the crop growth environment image information, slicing the insect region to obtain an insect picture, and transmitting the insect picture to the insect identification module through the 5G communication module;
the insect recognition module is used for acquiring insect form information on the insect picture after receiving the insect picture, then inputting the insect form information on the insect picture into a pre-trained neural network model, judging the probability of pests and beneficial pests to obtain the probability information of the pests in the crop growth environment, and sending the probability information of the pests to the controller module through the 5G communication module;
the controller module is preset with a probability threshold value of pests on crops, when the probability of the pests received by the controller module and sent by the pest identification module is larger than the set probability threshold value, the pesticide spraying module is controlled to spray pesticide on the crops, and after the pesticide spraying is finished, the blowing module is controlled to blow the crops; when the controller module receives that the pest probability sent by the pest identification module is smaller than a set probability threshold value, the blowing module is controlled to blow crops;
the data processing module is used for presetting a data threshold value for acquiring data information of the crop growing environment and then processing the data information, when the acquired data information of the crop growing environment is larger than the preset data threshold value, a generated data signal is sent to the controller module through the 5G communication module, and the controller module controls the alarm module to give an alarm after receiving the data signal;
the alarm module is used for sending out an alarm after receiving the instruction of the controller module.
2. The intelligent agricultural environment monitoring system of claim 1, wherein the growth environment data acquisition unit comprises sensors for monitoring carbon dioxide, light, noise, wind speed, air temperature, soil temperature and soil PH.
3. The intelligent agricultural environment monitoring system based on 5G technology as claimed in claim 1, wherein a collecting module for collecting pests is further disposed in the blowing direction of the blowing module, a weighing sensor is disposed on the collecting module, the weighing sensor is used for measuring the weight of the collected pests and transmitting gravity signals to the controller module, the controller module performs identification and judgment after receiving the gravity signals, the controller module further presets a gravity threshold, and when the controller module identifies that the gravity signals are greater than the preset threshold, the controller module controls the collecting module to dump the collected pests to the side of crops.
4. The intelligent agricultural environment monitoring system based on 5G technology according to claim 1, further comprising a pest number counting module, wherein the pest number counting module is used for counting the number of the pests collected by the collecting module.
5. The intelligent agricultural environment monitoring system based on 5G technology according to claim 1, wherein the shape information of the insects includes the size, shape and color of the insects.
6. The intelligent agricultural environment monitoring system based on 5G technology as claimed in claim 1, further comprising a storage module, wherein the storage module is used for storing the image information of the crop growth environment collected by the growth environment image collection unit and the data information of the crop growth environment collected by the growth environment data collection unit.
7. The intelligent agricultural environment monitoring system of claim 1, wherein the controller module is configured to control the alarm module to issue an alarm when the first data signal is received again after a certain time interval after the first data signal is received.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211356639.4A CN115761482A (en) | 2022-11-01 | 2022-11-01 | Wisdom agricultural environment monitoring system based on 5G technique |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211356639.4A CN115761482A (en) | 2022-11-01 | 2022-11-01 | Wisdom agricultural environment monitoring system based on 5G technique |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115761482A true CN115761482A (en) | 2023-03-07 |
Family
ID=85355065
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211356639.4A Pending CN115761482A (en) | 2022-11-01 | 2022-11-01 | Wisdom agricultural environment monitoring system based on 5G technique |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115761482A (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104635694A (en) * | 2015-01-08 | 2015-05-20 | 沈阳远大智能高科农业有限公司 | Intelligent agricultural early warning system |
| WO2016045002A1 (en) * | 2014-09-24 | 2016-03-31 | 上海星让实业有限公司 | Smart imaging system and insect-trapping apparatus provided with same |
| CN206275018U (en) * | 2016-11-04 | 2017-06-27 | 广东茂益园林有限公司 | A kind of forestry insect-killing device with automatic clearing function |
| CN206821771U (en) * | 2017-05-16 | 2018-01-02 | 陈丽 | A kind of forestry insect-catching equipment |
| CN206821770U (en) * | 2017-04-07 | 2018-01-02 | 诸暨市东珍生态农业有限公司 | A kind of agricultural insecticidal device |
| CN207023000U (en) * | 2017-07-31 | 2018-02-23 | 成都天骋科讯科技有限公司 | Insect infestation monitoring warning system |
| CN109035057A (en) * | 2018-09-30 | 2018-12-18 | 田东县文设芒果专业合作社 | Mango insect pest intelligent monitor system with sightseeing corridor |
| CN113110207A (en) * | 2021-04-28 | 2021-07-13 | 佛山一本农业科技有限公司 | Insect pest remote monitoring method and system based on sensor of Internet of things and storage medium |
| CN215217665U (en) * | 2021-05-23 | 2021-12-17 | 企铭欣(厦门)信息科技有限公司 | Wisdom agricultural environment monitoring system based on 5G technique |
| CN114972843A (en) * | 2022-04-26 | 2022-08-30 | 黑龙江省农业科学院农业遥感与信息研究所 | Agricultural pest diagnosis and early warning system based on big data |
| CN114954948A (en) * | 2022-05-27 | 2022-08-30 | 苏州农业职业技术学院 | Intelligent pesticide applying system for plant protection unmanned aerial vehicle and control method |
-
2022
- 2022-11-01 CN CN202211356639.4A patent/CN115761482A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016045002A1 (en) * | 2014-09-24 | 2016-03-31 | 上海星让实业有限公司 | Smart imaging system and insect-trapping apparatus provided with same |
| CN104635694A (en) * | 2015-01-08 | 2015-05-20 | 沈阳远大智能高科农业有限公司 | Intelligent agricultural early warning system |
| CN206275018U (en) * | 2016-11-04 | 2017-06-27 | 广东茂益园林有限公司 | A kind of forestry insect-killing device with automatic clearing function |
| CN206821770U (en) * | 2017-04-07 | 2018-01-02 | 诸暨市东珍生态农业有限公司 | A kind of agricultural insecticidal device |
| CN206821771U (en) * | 2017-05-16 | 2018-01-02 | 陈丽 | A kind of forestry insect-catching equipment |
| CN207023000U (en) * | 2017-07-31 | 2018-02-23 | 成都天骋科讯科技有限公司 | Insect infestation monitoring warning system |
| CN109035057A (en) * | 2018-09-30 | 2018-12-18 | 田东县文设芒果专业合作社 | Mango insect pest intelligent monitor system with sightseeing corridor |
| CN113110207A (en) * | 2021-04-28 | 2021-07-13 | 佛山一本农业科技有限公司 | Insect pest remote monitoring method and system based on sensor of Internet of things and storage medium |
| CN215217665U (en) * | 2021-05-23 | 2021-12-17 | 企铭欣(厦门)信息科技有限公司 | Wisdom agricultural environment monitoring system based on 5G technique |
| CN114972843A (en) * | 2022-04-26 | 2022-08-30 | 黑龙江省农业科学院农业遥感与信息研究所 | Agricultural pest diagnosis and early warning system based on big data |
| CN114954948A (en) * | 2022-05-27 | 2022-08-30 | 苏州农业职业技术学院 | Intelligent pesticide applying system for plant protection unmanned aerial vehicle and control method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113925039B (en) | Internet of things-based garden pest and disease intelligent protection system and prevention and control method | |
| CN107094595B (en) | Intelligent irrigation system with partitioned frame rails and control method thereof | |
| CN108614607B (en) | Agricultural production multi-factor management decision system based on instant monitoring data | |
| KR100923243B1 (en) | Automation farming system using feed fodder robot | |
| CN111488017A (en) | Wisdom agricultural management control system based on thing networking | |
| CN109145032A (en) | A kind of bee raising intelligent monitoring method and system | |
| CN108594775A (en) | A kind of agricultural big data information collection and processing system | |
| CN205390083U (en) | Intelligence plant diseases and insect pests monitoring and early warning system | |
| CN106871971A (en) | One plant growth management system | |
| CN110825139A (en) | Greenhouse intelligent management system based on Internet of things | |
| CN113080036A (en) | Intelligent irrigation control system | |
| CN116391690A (en) | Intelligent agricultural planting monitoring system based on big data of Internet of things | |
| CN114868504A (en) | Method and device for monitoring growth state of landscape plants | |
| TWM602798U (en) | Smart breeding management system | |
| CN205883318U (en) | Agricultural thing networking remote monitoring and control system | |
| CN115362811A (en) | Mountain crop intelligent cultivation system based on digital twinning | |
| CN107145177A (en) | Farmland intelligent monitor system | |
| CN113867243A (en) | Digital and intelligent landscaping and maintenance integrated management system | |
| Mathe et al. | A survey of agriculture applications utilizing raspberry pi | |
| CN206150259U (en) | Automatic trapper of insect | |
| CN110442174A (en) | A kind of automatic greenhouse cultivating system based on edge calculations Internet of Things | |
| CN114545799A (en) | Intelligent monitoring system for cattle raising | |
| CN214200207U (en) | Pest monitoring control device that lemon was planted | |
| CN107272620A (en) | A kind of method and device of the intelligent monitoring greenhouse based on Internet of Things | |
| CN115761482A (en) | Wisdom agricultural environment monitoring system based on 5G technique |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |