CN204142639U - Be positioned at the crop disease and insect detection system on unmanned plane - Google Patents
Be positioned at the crop disease and insect detection system on unmanned plane Download PDFInfo
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- CN204142639U CN204142639U CN201420654484.7U CN201420654484U CN204142639U CN 204142639 U CN204142639 U CN 204142639U CN 201420654484 U CN201420654484 U CN 201420654484U CN 204142639 U CN204142639 U CN 204142639U
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Abstract
The utility model relates to a kind of crop disease and insect detection system be positioned on unmanned plane, comprise random access memory, high-definition camera, image processor and master controller, described high-definition camera is used for catching crop map picture, described image processor is connected with described high-definition camera, for carrying out image procossing to described crop map picture, to obtain the crop disease and insect type in described crop map picture, described master controller is connected respectively with described random access memory and described image processor, for described crop disease and insect type being stored in described random access memory.By the utility model, automatically can obtain the disease and pest type of field crops, to facilitate related agricultural administrative authority to call when unmanned plane makes a return voyage, thus make disease and pest prevention and control measure targetedly.
Description
Technical field
The utility model relates to disease and pest prevention and control field, particularly relates to a kind of crop disease and insect detection system be positioned on unmanned plane.
Background technology
In agricultural production process, the prevention and control of effective realization to disease and pest are the prerequisites ensureing agricultural foison, if plantation crop pest be distributed more widely, endanger heavier disease, the yield and quality of crop will be had a strong impact on, before the prevention and control to disease and pest, what first will do is the type judging disease and pest, if disease and pest type judges accurately, then disease and pest is easily effected a radical cure, and if disease and pest type judges inaccurate, then will waste a large amount of manpower and financial resources, delay the valuable treatment time.
Traditional pest diagnosis method is judged by visual inspection, and compare in conjunction with agricultural crops disease collection of illustrative plates, inefficiency, is difficult in time, finds exactly and Lesion.Although some crop pest expert systems of development and application in recent years serve some effects, but because it needs a large amount of disease data as the input of system, and the specific features of crop pest is very complicated, be difficult to realize accurate quantification, therefore have impact on the accuracy that expert system judges.Also have some agricultural management departments to adopt the mode of satellite remote sensing to carry out disease and pest detection, but this detection mode involve great expense.
Therefore, need a kind of new crop disease and insect detection system, cost performance is moderate, can adapt to the requirement of crop area of detection broadness and disease and pest Precise Diagnosis, related agricultural administrative authority is facilitated to manipulate flexibly, so that the later stage carries out crop disease and insect treatment with a definite target in view.
Utility model content
In order to solve the problem, the utility model provides a kind of crop disease and insect detection system be positioned on unmanned plane, use the platform of unmanned plane, dependence unmanned plane is flexible, the feature that area of detection is wide, disease and pest detection can be carried out flexibly to the region that any needs are monitored, adopt image recognition technology simultaneously, first the pre-service of disease geo-radar image is carried out, by the image that collects by after gray processing and medium filtering, carry out Iamge Segmentation, obtain scab image, the shape facility of crop scab in scab image is described with disease and pest feature subsequently, thus effectively identify disease and pest type.
According to one side of the present utility model, provide a kind of crop disease and insect detection system be positioned on unmanned plane, described detection system comprises random access memory, high-definition camera, image processor and master controller, described high-definition camera is used for catching crop map picture, described image processor is connected with described high-definition camera, for carrying out image procossing to described crop map picture, to obtain the crop disease and insect type in described crop map picture, described master controller is connected respectively with described random access memory and described image processor, for described crop disease and insect type is stored in described random access memory.
More specifically, described in be arranged in crop disease and insect detection system on unmanned plane, described detection system also comprises, serial communication interface, is connected with described random access memory, for the storage content in described random access memory being read, flash card, scab upper limit gray threshold and scab lower limit gray threshold are prestored, also be previously stored with disease and pest property data base, described disease and pest property data base saves each disease and pest type and disease and pest feature corresponding to each disease and pest type, and described disease and pest feature comprises lesion area, scab minimum enclosed rectangle area and scab rectangular degree, wireless communication interface, for receiving the unmanned aerial vehicle (UAV) control instruction of remote agricultural management platform wireless transmission, described unmanned aerial vehicle (UAV) control instruction comprises take pictures height and GPS location of taking pictures, GPS locator, connects GPS navigation satellite, for receiving the current GPS location of described unmanned plane position, pressure-altitude sensor, comprise radio transmitter, radio receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described radio transmitter and described radio receiver, described radio transmitter launches radiowave earthward, described radio receiver receives the radiowave of ground return, described single-chip microcomputer calculates the present level of unmanned plane according to the launch time of described radio transmitter, the time of reception of described radio receiver and velocity of radio wave, and described velocity of radio wave is the light velocity, unmanned plane driving arrangement, for providing power for the flight of described unmanned plane, described image processor comprises gray proces unit, strengthen processing unit, filter processing unit, image segmentation unit and feature identification unit, described gray proces unit is connected to carry out gray proces to described crop map picture with described high-definition camera, obtain gray level image, described enhancing processing unit is connected to strengthen algorithm based on Wavelet image to described gray level image process with described gray proces unit, obtain and strengthen image, described filter processing unit be connected with described enhancing processing unit with based on median filtering algorithm to described enhancing image procossing, obtain filtering image, described image segmentation unit is connected respectively with described filter processing unit and described flash card, the pixel identification of gray-scale value in described filtering image between described scab upper limit gray threshold and described scab lower limit gray threshold is formed scab image, described feature identification unit is connected respectively with described image segmentation unit and described flash card, identify the disease and pest feature in described scab image, and the disease and pest feature of identification is searched the disease and pest type with the disease and pest characteristic matching identified in described disease and pest property data base, to export as described crop disease and insect type, described master controller, with described random access memory, described flash card, described wireless communication interface, described GPS locator, described pressure-altitude sensor, described unmanned plane driving arrangement, described high-definition camera is connected respectively with described image processor, to take pictures described in resolving to obtain to described unmanned aerial vehicle (UAV) control instruction height and described GPS location of taking pictures, and control described unmanned plane driving arrangement with drive described unmanned plane fly to described in take pictures height and described GPS location of taking pictures, described current GPS location and described present level consistent with described GPS location of taking pictures and described take pictures highly consistent time, start described high-definition camera and described image processor, and the crop disease and insect type corresponding stored described current GPS location and described image processor exported is in described random access memory, wherein, after described random access memory has stored described current GPS location and described crop disease and insect type, send to described master controller and be stored as function signal, described master controller sends detection by described wireless communication interface to described remote agricultural management platform and completes order after being stored as function signal described in receiving, so that described remote agricultural management platform continues to send unmanned aerial vehicle (UAV) control instruction to described wireless communication interface, described lesion area is the sum of all pixels in described scab image occupied by spot pattern, the sum of all pixels of described scab minimum enclosed rectangle occupied by the minimum rectangle of spot pattern in the described scab image of encirclement, described scab rectangular degree is the ratio of described lesion area and described scab minimum enclosed rectangle.
More specifically, described in be arranged in crop disease and insect detection system on unmanned plane, described detection system also comprises, light fixture, for providing floor light for the shooting of described high-definition camera.
More specifically, the described crop disease and insect detection system be arranged on unmanned plane, described light fixture comprises luminance sensor, for measuring the brightness data of described unmanned plane position, described light fixture controls the floor light for the shooting of described high-definition camera provides based on described brightness data.
More specifically, described in be arranged in crop disease and insect detection system on unmanned plane, the resolution of described high-definition camera is 1280 × 720.
More specifically, described in be arranged in crop disease and insect detection system on unmanned plane, described disease and pest feature also comprises scab geometric center of gravity and scab circularity.
More specifically, described in be arranged in crop disease and insect detection system on unmanned plane, described scab geometric center of gravity is the centre of form of spot pattern in described scab image.
More specifically, described in be arranged in crop disease and insect detection system on unmanned plane, described scab circularity is the similarity of spot pattern and standard circular in described scab image.
Accompanying drawing explanation
Below with reference to accompanying drawing, embodiment of the present utility model is described, wherein:
Fig. 1 is the block diagram being positioned at the crop disease and insect detection system on unmanned plane according to the utility model embodiment.
Fig. 2 is the block diagram being positioned at the pressure-altitude sensor of the crop disease and insect detection system on unmanned plane according to the utility model embodiment.
Embodiment
Below with reference to accompanying drawings the embodiment of the crop disease and insect detection system be positioned on unmanned plane of the present utility model is described in detail.
Disease and pest is disease and insect pest and claims, and often causes harmful effect to agricultural production.
Specific to disease, plant in the course of cultivation, be subject to infecting or the impact of unsuitable environmental condition of harmful organism, eubolism is interfered, a series of change and destruction is there is on from physiological function to institutional framework, so that present unusual pathology phenomenon in formalness, as withered, rotten, spot, mould powder, floral leaf etc., be referred to as disease.
Cause the reason that plant falls ill, comprise biodyne and abiotic factor.By the disease of biodyne caused by the invaded plants bodies such as fungi, bacterium, virus, be infectious, be called infectious disease or parasitic disease, the disease caused as the impacts such as drought, flood, severe cold, nutrient imbalance or damage physiological function by abiotic factor, there is no infectiousness, be called noninfectious disease or physiological disturbance.In infectious disease, the parasite of causing a disease is called causal organism, and wherein fungi, bacterium are often called pathogen.Host plant is called by the plant of infecting.The effect of causal organism is not only depended in the generation of infectious disease, and also has substantial connection with host's physiological status and external environmental condition, is the result of causal organism, host plant and environmental baseline triple interaction.
Specific to insect pest, the animal species of harm medicinal plant is a lot, wherein mainly insect, has mite class, snail, muroid etc. in addition.Though have in insect and much belong to insect, also there is beneficial insect, beneficial insect should be protected, breeds and be utilized.Therefore, understanding insect, research insect, grasps insect and occurs and Fluctuation, and for pest control, protective plant obtains good quality and high output, significant.
Various insect due to feeding habits different with foraging pattern, mouthpart is not identical yet, mainly contains biting mouthparts and sucking mouth parts.Pests with chewing mouthparts, as beetle, locust and moth butterfly class larva etc.They take food food, and harm root, stem, leaf, flower, fruit and seed, vegetables, cause mechanical injuries, as incised, hole, fractureing, bore moth stem stalk, cut off root etc.Sucking pest, as aphid, Chinese toon silk worm, leafhopper and mite class etc.They thrust plant tissue with needle-like mouthpart to suck foodstuff, make that plant presents atrophy, wrinkle leaf, leaf roll, withered spot, growing point come off, insect gall (being formed by saliva stimulates) etc.In addition, siphoning mouthparts (as moth butterfly class), paper suction mouthpart (as fly class), biting sucking mouthparts (as honeybee) is also had.
The crop scab that different disease and pests is formed, shape is different in appearance, can be used to the basis of characterization carrying out disease and pest type.
The crop disease and insect detection system be positioned on unmanned plane of the present utility model, under the remote wireless controlled of related agricultural administrative authority, can arrive the field that any needs detect flexibly, simultaneously image recognition technology quote the accuracy that ensure that disease and pest identification.
Fig. 1 is the block diagram being positioned at the crop disease and insect detection system on unmanned plane according to the utility model embodiment, as shown in Figure 1, described detection system comprises random access memory 3, high-definition camera 1, image processor 2 and master controller 4, described high-definition camera 1 is for catching crop map picture, described image processor 2 is connected with described high-definition camera 1, for carrying out image procossing to described crop map picture, to obtain the crop disease and insect type in described crop map picture, described master controller 4 and described random access memory 3, described image processor 2 is connected respectively with described high-definition camera 1, for described crop disease and insect type is stored in described random access memory 3.
Then, more specific description is carried out to the structure of the crop disease and insect detection system be positioned on unmanned plane of the present utility model.
Described detection system also comprises, serial communication interface, is connected with described random access memory 3, for the storage content in described random access memory 3 being read.
Described detection system also comprises, flash card, scab upper limit gray threshold and scab lower limit gray threshold are prestored, also be previously stored with disease and pest property data base, described disease and pest property data base saves each disease and pest type and disease and pest feature corresponding to each disease and pest type, and described disease and pest feature comprises lesion area, scab minimum enclosed rectangle area and scab rectangular degree.
Described detection system also comprises, wireless communication interface, and for receiving the unmanned aerial vehicle (UAV) control instruction of remote agricultural management platform wireless transmission, described unmanned aerial vehicle (UAV) control instruction comprises take pictures height and GPS location of taking pictures.
Described detection system also comprises, GPS locator, connects GPS navigation satellite, for receiving the current GPS location of described unmanned plane position.
With reference to shown in Fig. 2, described detection system also comprises, pressure-altitude sensor, pressure-altitude sensor comprises radio transmitter 5, radio receiver 6 and single-chip microcomputer 7, described single-chip microcomputer 7 is connected respectively with described radio transmitter 5 and described radio receiver 6, described radio transmitter 5 launches radiowave earthward, described radio receiver 6 receives the radiowave of ground return, described single-chip microcomputer 7 is according to the launch time of described radio transmitter 5, the time of reception of described radio receiver 6 and velocity of radio wave calculate the present level of unmanned plane, described velocity of radio wave is the light velocity.
Described detection system also comprises, unmanned plane driving arrangement, for providing power for the flight of described unmanned plane.
Described image processor 2 comprises gray proces unit, strengthen processing unit, filter processing unit, image segmentation unit and feature identification unit, described gray proces unit is connected to carry out gray proces to described crop map picture with described high-definition camera 1, obtain gray level image, described enhancing processing unit is connected to strengthen algorithm based on Wavelet image to described gray level image process with described gray proces unit, obtain and strengthen image, described filter processing unit be connected with described enhancing processing unit with based on median filtering algorithm to described enhancing image procossing, obtain filtering image, described image segmentation unit is connected respectively with described filter processing unit and described flash card, the pixel identification of gray-scale value in described filtering image between described scab upper limit gray threshold and described scab lower limit gray threshold is formed scab image, described feature identification unit is connected respectively with described image segmentation unit and described flash card, identify the disease and pest feature in described scab image, and the disease and pest feature of identification is searched the disease and pest type with the disease and pest characteristic matching identified in described disease and pest property data base, to export as described crop disease and insect type.
Described master controller 4, with described random access memory 3, described flash card, described wireless communication interface, described GPS locator, described pressure-altitude sensor, described unmanned plane driving arrangement, described high-definition camera 1 is connected respectively with described image processor 2, to take pictures described in resolving to obtain to described unmanned aerial vehicle (UAV) control instruction height and described GPS location of taking pictures, and control described unmanned plane driving arrangement with drive described unmanned plane fly to described in take pictures height and described GPS location of taking pictures, described current GPS location and described present level consistent with described GPS location of taking pictures and described take pictures highly consistent time, start described high-definition camera 1 and described image processor 2, and the crop disease and insect type corresponding stored described current GPS location and described image processor 2 exported is in described random access memory 3.
Wherein, after described random access memory 3 has stored described current GPS location and described crop disease and insect type, send to described master controller 4 and be stored as function signal, described master controller 4 sends detection by described wireless communication interface to described remote agricultural management platform and completes order after being stored as function signal described in receiving, so that described remote agricultural management platform continues to send unmanned aerial vehicle (UAV) control instruction to described wireless communication interface; Described lesion area is the sum of all pixels in described scab image occupied by spot pattern, the sum of all pixels of described scab minimum enclosed rectangle occupied by the minimum rectangle of spot pattern in the described scab image of encirclement, described scab rectangular degree is the ratio of described lesion area and described scab minimum enclosed rectangle.
Wherein, described detection system can also comprise, light fixture, for providing floor light for the shooting of described high-definition camera 1, described light fixture can comprise luminance sensor, for measuring the brightness data of described unmanned plane position, described light fixture controls the floor light for the shooting of described high-definition camera 1 provides based on described brightness data, the resolution of described high-definition camera 1 is chosen as 1280 × 720, described disease and pest feature also comprises scab geometric center of gravity and scab circularity, described scab geometric center of gravity is the centre of form of spot pattern in described scab image, described scab circularity is the similarity of spot pattern and standard circular in described scab image.
In addition, median filtering method is a kind of nonlinear smoothing technology, the gray-scale value of each pixel is set to the intermediate value of all pixel gray-scale values in this some neighborhood window by him, medium filtering is can the nonlinear signal processing technology of effective restraint speckle based on a kind of of sequencing statistical theory, the ultimate principle of medium filtering is that the Mesophyticum of each point value in a neighborhood of this point of value of any in digital picture or Serial No. is replaced, allow the actual value that the pixel value of surrounding is close, thus eliminate isolated noise spot.Median filtering method is very effective to elimination salt-pepper noise; in the phase analysis disposal route of optical measurement stripe pattern, have special role, but effect is little in fringe center analytical approach, medium filtering is in image procossing; being usually used in Protect edge information information, is the method for classical smooth noise.
In addition, flash memory (Flash Memory) is the storer of a kind of long-life non-volatile (still can keep stored data message under powering-off state), it is not that block size is generally 256KB to 20MB in units of single byte but in units of fixing block that data are deleted.Flash memory is the mutation of Electrical Erasable ROM (read-only memory) (EEPROM), flash memory and EEPROM can carry out deleting and rewrite in byte-level unlike, EEPROM instead of whole chip erasable, and most of chip of flash memory needs block to wipe.Still can preserve data due to during its power-off, flash memory is usually used to preserve configuration information, as preservation data etc. in BIOS (base program), the PDA (personal digital assistant), digital camera of computer.Flash memory is a kind of nonvolatile memory, i.e. power-off data also can not be lost.
Adopt the crop disease and insect detection system be positioned on unmanned plane of the present utility model,, monitoring underaction, technical matters that precision not high or not for existing crop disease and insect detection system cost performance, by detection system is arranged on unmanned plane, use the controllability of unmanned plane, the feature of low-latitude flying, the region of any needs monitoring can be appeared at, simultaneously the quoting of image recognition technology and wireless communication technology, ensures the accuracy of disease and pest feature identification and the validity of data transmission.
Be understandable that, although the utility model with preferred embodiment disclose as above, but above-described embodiment and be not used to limit the utility model.For any those of ordinary skill in the art, do not departing under technical solutions of the utility model ambit, the technology contents of above-mentioned announcement all can be utilized to make many possible variations and modification to technical solutions of the utility model, or be revised as the Equivalent embodiments of equivalent variations.Therefore, every content not departing from technical solutions of the utility model, according to technical spirit of the present utility model to any simple modification made for any of the above embodiments, equivalent variations and modification, all still belongs in the scope of technical solutions of the utility model protection.
Claims (8)
1. one kind is positioned at the crop disease and insect detection system on unmanned plane, it is characterized in that, described detection system comprises random access memory, high-definition camera, image processor and master controller, described high-definition camera is used for catching crop map picture, described image processor is connected with described high-definition camera, for carrying out image procossing to described crop map picture, to obtain the crop disease and insect type in described crop map picture, described master controller is connected respectively with described random access memory and described image processor, for described crop disease and insect type is stored in described random access memory.
2. be positioned at the crop disease and insect detection system on unmanned plane as claimed in claim 1, it is characterized in that, described detection system also comprises:
Serial communication interface, is connected with described random access memory, for the storage content in described random access memory being read;
Flash card, scab upper limit gray threshold and scab lower limit gray threshold are prestored, also be previously stored with disease and pest property data base, described disease and pest property data base saves each disease and pest type and disease and pest feature corresponding to each disease and pest type, and described disease and pest feature comprises lesion area, scab minimum enclosed rectangle area and scab rectangular degree;
Wireless communication interface, for receiving the unmanned aerial vehicle (UAV) control instruction of remote agricultural management platform wireless transmission, described unmanned aerial vehicle (UAV) control instruction comprises take pictures height and GPS location of taking pictures;
GPS locator, connects GPS navigation satellite, for receiving the current GPS location of described unmanned plane position;
Pressure-altitude sensor, comprise radio transmitter, radio receiver and single-chip microcomputer, described single-chip microcomputer is connected respectively with described radio transmitter and described radio receiver, described radio transmitter launches radiowave earthward, described radio receiver receives the radiowave of ground return, described single-chip microcomputer calculates the present level of unmanned plane according to the launch time of described radio transmitter, the time of reception of described radio receiver and velocity of radio wave, and described velocity of radio wave is the light velocity;
Unmanned plane driving arrangement, for providing power for the flight of described unmanned plane;
Described image processor comprises gray proces unit, strengthen processing unit, filter processing unit, image segmentation unit and feature identification unit, described gray proces unit is connected to carry out gray proces to described crop map picture with described high-definition camera, obtain gray level image, described enhancing processing unit is connected to strengthen algorithm based on Wavelet image to described gray level image process with described gray proces unit, obtain and strengthen image, described filter processing unit be connected with described enhancing processing unit with based on median filtering algorithm to described enhancing image procossing, obtain filtering image, described image segmentation unit is connected respectively with described filter processing unit and described flash card, the pixel identification of gray-scale value in described filtering image between described scab upper limit gray threshold and described scab lower limit gray threshold is formed scab image, described feature identification unit is connected respectively with described image segmentation unit and described flash card, identify the disease and pest feature in described scab image, and the disease and pest feature of identification is searched the disease and pest type with the disease and pest characteristic matching identified in described disease and pest property data base, to export as described crop disease and insect type,
Described master controller, with described random access memory, described flash card, described wireless communication interface, described GPS locator, described pressure-altitude sensor, described unmanned plane driving arrangement, described high-definition camera is connected respectively with described image processor, to take pictures described in resolving to obtain to described unmanned aerial vehicle (UAV) control instruction height and described GPS location of taking pictures, and control described unmanned plane driving arrangement with drive described unmanned plane fly to described in take pictures height and described GPS location of taking pictures, described current GPS location and described present level consistent with described GPS location of taking pictures and described take pictures highly consistent time, start described high-definition camera and described image processor, and the crop disease and insect type corresponding stored described current GPS location and described image processor exported is in described random access memory,
Wherein, after described random access memory has stored described current GPS location and described crop disease and insect type, send to described master controller and be stored as function signal, described master controller sends detection by described wireless communication interface to described remote agricultural management platform and completes order after being stored as function signal described in receiving, so that described remote agricultural management platform continues to send unmanned aerial vehicle (UAV) control instruction to described wireless communication interface;
Wherein, described lesion area is the sum of all pixels in described scab image occupied by spot pattern, the sum of all pixels of described scab minimum enclosed rectangle occupied by the minimum rectangle of spot pattern in the described scab image of encirclement, described scab rectangular degree is the ratio of described lesion area and described scab minimum enclosed rectangle.
3. be positioned at the crop disease and insect detection system on unmanned plane as claimed in claim 2, it is characterized in that, described detection system also comprises:
Light fixture, for providing floor light for the shooting of described high-definition camera.
4. be positioned at the crop disease and insect detection system on unmanned plane as claimed in claim 3, it is characterized in that:
Described light fixture comprises luminance sensor, and for measuring the brightness data of described unmanned plane position, described light fixture controls the floor light for the shooting of described high-definition camera provides based on described brightness data.
5. be positioned at the crop disease and insect detection system on unmanned plane as claimed in claim 2, it is characterized in that:
The resolution of described high-definition camera is 1280 × 720.
6. be positioned at the crop disease and insect detection system on unmanned plane as claimed in claim 2, it is characterized in that:
Described disease and pest feature also comprises scab geometric center of gravity and scab circularity.
7. be positioned at the crop disease and insect detection system on unmanned plane as claimed in claim 6, it is characterized in that:
Described scab geometric center of gravity is the centre of form of spot pattern in described scab image.
8. be positioned at the crop disease and insect detection system on unmanned plane as claimed in claim 6, it is characterized in that:
Described scab circularity is the similarity of spot pattern and standard circular in described scab image.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104330410A (en) * | 2014-11-04 | 2015-02-04 | 无锡北斗星通信息科技有限公司 | Crop pest detection system positioned on unmanned aerial vehicle |
| CN104697501A (en) * | 2015-03-08 | 2015-06-10 | 无锡桑尼安科技有限公司 | Apple orchard yield measuring system |
| CN104807456A (en) * | 2015-04-29 | 2015-07-29 | 深圳市保千里电子有限公司 | Method for automatic return flight without GPS (global positioning system) signal |
| CN104996018A (en) * | 2015-07-29 | 2015-10-28 | 王驰 | Multi-purpose unmanned agricultural operation robot platform |
| CN106568777A (en) * | 2016-11-16 | 2017-04-19 | 王金鹏 | Pest and disease monitoring system |
| CN110077611A (en) * | 2019-04-24 | 2019-08-02 | 塔里木大学 | A kind of unmanned machine equipment monitoring cotton diseases and insect pests |
| US10577103B2 (en) | 2016-09-08 | 2020-03-03 | Walmart Apollo, Llc | Systems and methods for dispensing an insecticide via unmanned vehicles to defend a crop-containing area against pests |
| US11386361B2 (en) * | 2015-05-25 | 2022-07-12 | Agromentum Ltd. | Closed loop integrated pest management |
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2014
- 2014-11-04 CN CN201420654484.7U patent/CN204142639U/en not_active Withdrawn - After Issue
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104330410A (en) * | 2014-11-04 | 2015-02-04 | 无锡北斗星通信息科技有限公司 | Crop pest detection system positioned on unmanned aerial vehicle |
| CN104330410B (en) * | 2014-11-04 | 2015-11-25 | 南通宏大机电制造有限公司 | Be positioned at the crop disease and insect detection system on unmanned plane |
| CN104697501A (en) * | 2015-03-08 | 2015-06-10 | 无锡桑尼安科技有限公司 | Apple orchard yield measuring system |
| CN104807456A (en) * | 2015-04-29 | 2015-07-29 | 深圳市保千里电子有限公司 | Method for automatic return flight without GPS (global positioning system) signal |
| CN104807456B (en) * | 2015-04-29 | 2018-04-17 | 深圳市保千里电子有限公司 | A kind of method maked a return voyage automatically during GPS no signals |
| US11386361B2 (en) * | 2015-05-25 | 2022-07-12 | Agromentum Ltd. | Closed loop integrated pest management |
| CN104996018A (en) * | 2015-07-29 | 2015-10-28 | 王驰 | Multi-purpose unmanned agricultural operation robot platform |
| US10577103B2 (en) | 2016-09-08 | 2020-03-03 | Walmart Apollo, Llc | Systems and methods for dispensing an insecticide via unmanned vehicles to defend a crop-containing area against pests |
| CN106568777A (en) * | 2016-11-16 | 2017-04-19 | 王金鹏 | Pest and disease monitoring system |
| CN110077611A (en) * | 2019-04-24 | 2019-08-02 | 塔里木大学 | A kind of unmanned machine equipment monitoring cotton diseases and insect pests |
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