CN112330335A - Tracing method and device in agricultural production process, storage medium and electronic equipment - Google Patents
Tracing method and device in agricultural production process, storage medium and electronic equipment Download PDFInfo
- Publication number
- CN112330335A CN112330335A CN201910695752.7A CN201910695752A CN112330335A CN 112330335 A CN112330335 A CN 112330335A CN 201910695752 A CN201910695752 A CN 201910695752A CN 112330335 A CN112330335 A CN 112330335A
- Authority
- CN
- China
- Prior art keywords
- farming
- behavior
- information
- monitoring image
- production process
- 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
- 238000000034 method Methods 0.000 title claims abstract description 131
- 230000008569 process Effects 0.000 title claims abstract description 70
- 238000012271 agricultural production Methods 0.000 title claims abstract description 57
- 238000003860 storage Methods 0.000 title claims abstract description 23
- 238000009313 farming Methods 0.000 claims abstract description 196
- 230000006399 behavior Effects 0.000 claims abstract description 182
- 238000012544 monitoring process Methods 0.000 claims abstract description 113
- 206010000117 Abnormal behaviour Diseases 0.000 claims description 16
- 230000002159 abnormal effect Effects 0.000 claims description 12
- 230000007246 mechanism Effects 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 4
- 230000009471 action Effects 0.000 abstract description 14
- 230000006855 networking Effects 0.000 abstract 1
- 238000005507 spraying Methods 0.000 description 15
- 238000009333 weeding Methods 0.000 description 15
- 238000012545 processing Methods 0.000 description 13
- 238000010586 diagram Methods 0.000 description 12
- 239000012773 agricultural material Substances 0.000 description 7
- 238000004519 manufacturing process Methods 0.000 description 7
- 230000000694 effects Effects 0.000 description 5
- 239000000575 pesticide Substances 0.000 description 4
- 239000000463 material Substances 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000001960 triggered effect Effects 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 239000003337 fertilizer Substances 0.000 description 2
- 238000010899 nucleation Methods 0.000 description 2
- 239000013307 optical fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000007921 spray Substances 0.000 description 2
- 239000005892 Deltamethrin Substances 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 229960002483 decamethrin Drugs 0.000 description 1
- OWZREIFADZCYQD-NSHGMRRFSA-N deltamethrin Chemical compound CC1(C)[C@@H](C=C(Br)Br)[C@H]1C(=O)O[C@H](C#N)C1=CC=CC(OC=2C=CC=CC=2)=C1 OWZREIFADZCYQD-NSHGMRRFSA-N 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000002917 insecticide Substances 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- -1 seeds Substances 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/018—Certifying business or products
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Animal Husbandry (AREA)
- Development Economics (AREA)
- Accounting & Taxation (AREA)
- Multimedia (AREA)
- Life Sciences & Earth Sciences (AREA)
- Agronomy & Crop Science (AREA)
- Finance (AREA)
- Marine Sciences & Fisheries (AREA)
- Mining & Mineral Resources (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Primary Health Care (AREA)
- Tourism & Hospitality (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The utility model relates to the technical field of the thing networking, provide a traceability method in the agricultural production process, traceability device, computer storage medium, electronic equipment in the agricultural production process, wherein, traceability method in the agricultural production process includes: acquiring farming behaviors contained in a monitoring image and acquiring monitoring time corresponding to the monitoring image; if the farming behavior meets a preset traceability rule, judging whether a target farming behavior corresponding to the monitoring time exists in farming record information; and if the target farming behavior exists, judging the farming behavior as normal behavior information. The tracing method in the agricultural production process can solve the technical problem that in the prior art, only the monitoring image can be displayed to related users, but whether the agricultural action is illegal or not cannot be determined, and the tracing in the agricultural production process is realized.
Description
Technical Field
The present disclosure relates to the field of internet of things technology, and in particular, to a method and an apparatus for tracing a source in an agricultural production process, a computer storage medium, and an electronic device.
Background
With the development of economy and the continuous improvement of national living standard, people's attention to food health is gradually increased, and therefore, it is necessary to trace back the agricultural production process (production control of forward, reverse or non-directional tracing of products). The tracing is a core system of farm business, on one hand, the normalized production and processing process of agricultural products can be realized through tracing, and on the other hand, the visibility of users to the agricultural production process can be realized through tracing, so that the purpose of making agricultural products credible is achieved.
At present, the generation of the tracing data mainly has two forms, one is a farming record entered through an information system, such as: seeding record, fertilizing record, and the like, and the other is image and video information collected by video equipment. In the related method, the two tracing data are generally displayed to related users so as to realize the tracing control of the agricultural production process. However, since the farming behavior is not tied to the farming mission, it cannot be determined whether the collected farming behavior is illegal.
In view of this, there is a need in the art to develop a new tracing method and apparatus in agricultural production process.
It is to be noted that the information disclosed in the background section above is only used to enhance understanding of the background of the present disclosure.
Disclosure of Invention
The purpose of the present disclosure is to provide a tracing method in an agricultural production process, a tracing device in an agricultural production process, a computer storage medium, and an electronic device, so as to avoid, at least to a certain extent, the defect that in the prior art, only a monitoring image can be displayed but whether an agricultural action is violated cannot be determined.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to a first aspect of the present disclosure, there is provided a tracing method in an agricultural production process, comprising: acquiring farming behaviors contained in a monitoring image and acquiring monitoring time corresponding to the monitoring image; if the farming behavior meets a preset traceability rule, judging whether a target farming behavior corresponding to the monitoring time exists in farming record information; and if the target farming behavior exists, judging the farming behavior as normal behavior information.
In an exemplary embodiment of the present disclosure, after determining the farming behavior as the normal behavior information, the method further includes: and combining the farming record information and the monitoring image to generate normal traceability information.
In an exemplary embodiment of the present disclosure, the method further comprises: and if the farming behavior does not exist in the farming record information, judging the farming behavior as abnormal behavior information.
In an exemplary embodiment of the present disclosure, after determining the farming behavior as abnormal behavior information, the method further includes: and merging the abnormal behavior information and the monitoring image to generate abnormal tracing information.
In an exemplary embodiment of the present disclosure, the method further comprises: and triggering an alarm mechanism according to the abnormal tracing information.
In an exemplary embodiment of the present disclosure, the method further comprises: presetting a reference picture, and marking a reference farming behavior corresponding to the reference picture; when the monitoring image is obtained, obtaining the similarity between the monitoring image and the reference picture; and if the similarity meets a preset threshold value, judging that the farming behavior contained in the monitoring image is consistent with the reference farming behavior.
In an exemplary embodiment of the present disclosure, the method further comprises: acquiring type information corresponding to the farming behavior; and judging whether the farming behavior meets the preset traceability rule or not according to the type information.
According to a second aspect of the present disclosure, there is provided a tracing device in an agricultural production process, comprising: the acquisition module is used for acquiring the farming behavior contained in the monitoring image and acquiring the monitoring time corresponding to the monitoring image; the judging module is used for judging whether a target farming behavior corresponding to the monitoring time exists in farming record information or not if the farming behavior meets a preset traceability rule; and the judging module is used for judging the farming behavior as normal behavior information if the target farming behavior exists.
According to a third aspect of the present disclosure, there is provided a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the traceability method in the agricultural production process of the first aspect.
According to a fourth aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the tracing method in the agricultural production process according to the first aspect through executing the executable instructions.
According to the technical scheme, the traceability method in the agricultural production process, the traceability device in the agricultural production process, the computer storage medium and the electronic device in the exemplary embodiment of the disclosure have at least the following advantages and positive effects:
in the technical solutions provided by some embodiments of the present disclosure, on one hand, the farming behaviors included in the monitoring image are obtained, and the monitoring time corresponding to the monitoring image is obtained, so that all the farming behaviors in the agricultural production process can be obtained in real time, and the realization of standardized production and processing of agricultural products is facilitated. On the other hand, if the farming behavior meets the preset traceability rule, whether a target farming behavior corresponding to the monitoring time exists in the farming record information is judged, and if the target farming behavior exists, the farming behavior is judged to be normal behavior information, so that the farming task plan formulated in the agricultural production process can be verified with the actually executed farming behavior, whether the farming behavior is illegal is determined, the technical problem that in the prior art, only the monitoring image can be displayed, but whether the farming behavior is illegal or not cannot be determined is solved, and the traceability of the agricultural production process is realized.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.
FIG. 1 shows a schematic flow diagram of a traceability method in an agricultural production process in an exemplary embodiment of the present disclosure;
FIG. 2 shows a schematic flow diagram of a traceability method in an agricultural production process in another exemplary embodiment of the present disclosure;
FIG. 3 is a schematic illustration of a display interface of a traceability method in an agricultural production process in an exemplary embodiment of the present disclosure;
FIG. 4 is a schematic illustration of a presentation interface of a traceability method in an agricultural production process in another exemplary embodiment of the present disclosure;
FIG. 5 is a schematic flow chart diagram illustrating an exemplary embodiment of a traceability method in an agricultural production process;
FIG. 6 is a schematic structural diagram of a tracing device in an agricultural production process according to an exemplary embodiment of the disclosure;
FIG. 7 shows a schematic diagram of a structure of a computer storage medium in an exemplary embodiment of the disclosure;
fig. 8 shows a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
The terms "a," "an," "the," and "said" are used in this specification to denote the presence of one or more elements/components/parts/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.; the terms "first" and "second", etc. are used merely as labels, and are not limiting on the number of their objects.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.
At present, a tracing method in a related agricultural production process only respectively displays agricultural records and images and video information acquired by video equipment, which are input through an information system, to related users, however, as agricultural behaviors are not bound with agricultural tasks, whether the acquired agricultural behaviors are illegal or not cannot be determined, that is, whether the acquired agricultural behaviors are normal or not cannot be determined. Therefore, the traceability method in the agricultural production process in the prior art needs to be improved.
In the embodiment of the disclosure, a traceability method in an agricultural production process is provided first, which can be applied to a relevant traceability system of a farm, and overcomes the defect that the traceability method in the agricultural production process provided in the prior art can only display a monitoring image but cannot determine whether an agricultural action violates a rule at least to a certain extent.
Fig. 1 shows a flow chart of a traceability method in an agricultural production process in an exemplary embodiment of the present disclosure, an execution subject of the traceability method in the agricultural production process may be a server for tracing the agricultural production process.
Referring to fig. 1, a traceability method in an agricultural production process according to one embodiment of the present disclosure comprises the following steps:
step S110, acquiring farming behaviors contained in a monitoring image and acquiring monitoring time corresponding to the monitoring image;
step S120, if the farming behavior meets a preset traceability rule, judging whether a target farming behavior corresponding to the monitoring time exists in farming record information;
and step S130, if the target farming behavior exists, judging the farming behavior as normal behavior information.
In the technical scheme provided by the embodiment shown in fig. 1, on one hand, the farming behaviors contained in the monitoring image and the monitoring time corresponding to the monitoring image are obtained, so that all the farming behaviors in the agricultural production process can be obtained in real time, and the standardized production and processing of agricultural products are facilitated. On the other hand, if the farming behavior meets the preset traceability rule, whether a target farming behavior corresponding to the monitoring time exists in the farming record information is judged, and if the target farming behavior exists, the farming behavior is judged to be normal behavior information, so that the farming task plan formulated in the agricultural production process can be verified with the actually executed farming behavior, whether the farming behavior is illegal is determined, the technical problem that in the prior art, only the monitoring image can be displayed, but whether the farming behavior is illegal or not cannot be determined is solved, and the traceability of the agricultural production process is realized.
The following describes the specific implementation of each step in fig. 1 in detail:
in step S110, a farming behavior included in the monitoring image is obtained, and a monitoring time corresponding to the monitoring image is obtained.
In an exemplary embodiment of the present disclosure, the farming behavior included in the monitoring image may be acquired, and the monitoring time corresponding to the monitoring image may be acquired.
In an exemplary embodiment of the present disclosure, the monitoring image is each frame of picture, video, etc. monitored by the monitoring device (camera, lens). The monitoring time is the time for acquiring the monitoring image. All agricultural behaviors implemented in the growth process of agricultural products can be acquired in real time through the monitoring images, and the standardized production and processing in the agricultural production process are facilitated.
In exemplary embodiments of the present disclosure, a farming activity, i.e., an agricultural activity related to the planting or growth process of an agricultural product, such as: seeding, weeding, fertilizing, spraying and the like.
In an exemplary embodiment of the present disclosure, fig. 2 schematically illustrates a flowchart of a tracing method in an agricultural production process in another exemplary embodiment of the present disclosure, and specifically illustrates a flowchart of how to determine the farming behavior contained in the monitoring image, and the step S110 is explained below with reference to fig. 2.
In step S201, a reference picture is preset, and a reference farming behavior corresponding to the reference picture is marked.
In an exemplary embodiment of the present disclosure, a reference picture may be preset, and a reference farming behavior corresponding to the reference picture may be marked.
In an exemplary embodiment of the present disclosure, the reference pictures are multiple pictures including reference farming activities, and each reference picture corresponds to a specific reference farming activity. For example, the reference farming behavior may be a pesticide spray, and the reference picture may be a picture of the relevant farming staff when the pesticide spray is implemented. The reference farming behavior can also be weeding, and the reference picture can be a picture of related farming personnel when weeding is carried out.
In the exemplary embodiment of the present disclosure, by setting the reference picture and the reference farming behavior, the recognition speed of the farming behavior contained in the subsequent recognition monitoring image can be increased, and the recognition efficiency can be improved.
In step S202, when the monitoring image is acquired, the similarity between the monitoring image and the reference picture is acquired.
In an exemplary embodiment of the present disclosure, when the monitoring image is acquired, a similarity between the monitoring image and the reference picture may be acquired.
In an exemplary embodiment of the disclosure, for example, the monitoring image may be compared with the plurality of reference pictures, for example: and comparing the action similarity of the people contained in the image, the similarity of the used agricultural resources and the like to determine the similarity of the monitoring image and the reference image.
In step S203, if the similarity satisfies a preset threshold, it is determined that the farming behavior included in the monitored image is consistent with the reference farming behavior.
In an exemplary embodiment of the present disclosure, if the similarity satisfies a preset threshold, it may be determined that the farming behavior included in the monitored image is consistent with the reference farming behavior.
In an exemplary embodiment of the present disclosure, for example, a reference picture corresponding to a similarity greater than a preset threshold (e.g., 95%) may be used as an identification result of the monitored image, and further, a reference farming behavior corresponding to the reference picture may be identified as a farming behavior included in the monitored image. For example, the reference picture corresponding to the acquired similarity with the largest value may be used as the recognition result of the monitored image, and further, the reference farming behavior corresponding to the reference picture may be recognized as the farming behavior included in the monitored image. It should be noted that, the specific implementation method of the preset threshold may be set according to the actual situation, and belongs to the protection scope of the present disclosure.
In an exemplary embodiment of the present disclosure, for example, the farming behavior included in the monitoring image may be weeding behavior, and the corresponding monitoring time may be 2015, 9, 20, 7 pm: 40. for example, the farming behavior included in the monitoring image may be a spraying behavior, and the corresponding monitoring time may be 2015, 9, 21, 7 pm: 40.
with reference to fig. 1, in step S120, if the farming behavior meets the preset traceability rule, it is determined whether a target farming behavior corresponding to the monitoring time exists in the farming record information.
In an exemplary embodiment of the disclosure, after the farming behavior is obtained, it may be determined whether the farming behavior meets a preset traceability rule, and if it is determined that the farming behavior meets the preset traceability rule, it may be determined whether a target farming behavior corresponding to the monitoring time exists in the farming record information.
In an exemplary embodiment of the present disclosure, type information corresponding to the farming behavior may be obtained, and then, whether the farming behavior meets the preset traceability rule is determined according to the type information.
In an exemplary embodiment of the disclosure, the preset traceability rule is to determine whether the farming behavior is a farming behavior that needs to be traced, and for example, if the user focuses on paying attention to whether the agricultural product is a green food, the preset traceability rule may be to determine whether the type information corresponding to the farming behavior is a pesticide spraying type or a fertilizer application type. If the user focuses on paying attention to whether the agricultural products are pollution-free food or not, the preset traceability rule can be used for judging whether the type information corresponding to the agricultural action is a spraying type or a weeding type. It should be noted that, the specific traceability rule can be set according to the actual situation, and belongs to the protection scope of the present disclosure.
In the exemplary embodiment of the disclosure, by acquiring the farming behaviors meeting the preset traceability rule, the farming behavior types and the implementation times closely related to the growth process of the agricultural products can be screened out, the technical problems of manpower and material resource waste and low efficiency caused by manual checking and checking are avoided, and the working efficiency of related workers is improved.
In an exemplary embodiment of the disclosure, referring to the related explanations of the above steps, for example, if a user focuses on whether an agricultural product is a pollution-free food or not, and a preset traceability rule is to determine whether type information corresponding to the farming behavior is a spraying type or a weeding type, the type information corresponding to the weeding behavior may be the weeding type, and the type information corresponding to the spraying behavior may be the spraying type, that is, both the weeding behavior and the spraying behavior satisfy the preset traceability rule. Then, further, it can be determined whether there is a target farming behavior corresponding to the monitoring time in the farming record information.
In an exemplary embodiment of the present disclosure, the above-mentioned farming record information may be information manually entered by a relevant farming staff before or after performing a farming action. For example, the relevant farm personnel may obtain the farm tasks to be executed from the farm task plan (for example, weeding is performed at 7 pm-9 pm on 9/20/2015, and spraying is performed at 7 pm-9 am on 21/2015), and further, the relevant farm personnel may execute the corresponding farm tasks according to the farm tasks, and before starting execution or after completion of execution, the farm record information may be recorded and generated. Illustratively, the farming record information may be: "operator: liu Kun; the operation time is as follows: 9/20/2015 at 7 pm: 40; the operation time is as follows: 16 h; the use of agricultural materials (agricultural materials are abbreviated as agricultural materials, and generally refer to material data and material conditions used for changing and influencing working objects in the agricultural production process, such as agricultural transportation machinery, production and processing machinery, pesticides, seeds, fertilizers, agricultural films and the like): a tractor; agricultural material quantity: 3. "farm record information may also be: "operator: zhang III; the operation time is as follows: 9/21/2015, 7 am: 40; agricultural materials: the insecticide "deltamethrin", 500ML x 3. "
In an exemplary embodiment of the present disclosure, the target farming behavior is farming behavior existing in the farming record information, which is the same farming behavior as the monitoring time of the farming behavior. Referring to step S203 and the related explanations of the above steps, it can be seen that the monitoring time corresponding to the weeding behavior is 2015, 9, 20, 7 pm: 40, and 7 pm on 9/20/2015: 40, there is farming record information corresponding to the target farming behavior (weeding behavior).
In an exemplary embodiment of the present disclosure, with continuing reference to step S203 and the related explanation of the above steps, it can be seen that the monitoring time corresponding to the spraying behavior is 2015, 9, 21, 7 pm: 40, and the farming record information is recorded in the region of 7 am on 9/21/2015: the spraying action was performed 40, so that, in 2015, 9, 21 pm, 7: 40, there is no agricultural record information corresponding to the target agricultural action (spraying action).
In the exemplary embodiment of the disclosure, after it is determined that the farming behavior meets the preset traceability rule, whether a target farming behavior corresponding to the monitoring time exists in the farming record information is judged, and whether the farming behavior is the farming behavior conforming to the preset farming task can be determined, so that the technical problem that in the prior art, only a monitoring image can be displayed, but whether the farming behavior is illegal or not can not be determined can be solved, and the verification of the farming task plan formulated in the agricultural production process and the actually executed farming behavior is realized.
In step S130, if the target farming behavior exists, the farming behavior is determined as normal behavior information.
In an exemplary embodiment of the present disclosure, if the target farming behavior exists in the farming record information, the farming behavior may be determined as normal behavior information. For example, referring to the related explanation of step S120, the weeding behavior can be determined as the normal behavior information. Furthermore, the farming record information and the monitoring image can be merged to generate normal traceability information. And normal traceability information is information recorded in the agricultural task plan without illegal agricultural product growth process. For example, referring to fig. 3, fig. 3 schematically shows a display interface schematic diagram of a traceability method in an agricultural production process in an exemplary embodiment of the present disclosure, and specifically shows a display interface schematic diagram that after the weeding behavior is determined as normal behavior information, the farming record information and the monitoring image are merged to generate normal traceability information, and then the normal traceability information is displayed to a relevant user. Referring to fig. 3, "farm data", i.e., the farm record information, includes: "weeding; the operator: liu Kun; the operation time is as follows: 9/2015, 20/7: 40 pm; the operation time is as follows: 16 h; using agricultural materials: a tractor; agricultural material quantity: 3. "farm snapshot" is the monitoring image described above.
In this disclosed example embodiment, through merging above-mentioned farming record information and above-mentioned monitoring image and generating normal information of tracing to the source, can realize integrality and the uniformity of tracing to the source for the user can clearly and directly perceived when carrying out agricultural product tracing to know detailed information such as concrete operation person, operating time of every farming action, can also know the number of times of execution of each farming action according to the monitoring image, thereby, can realize that the user is visible to the agricultural production process, improve the credibility to agricultural product, guarantee that the user is relieved to eat, the purchase of reassuring.
In an exemplary embodiment of the present disclosure, if the target farming behavior does not exist in the farming record information, the farming behavior may be determined as abnormal behavior information. For example, referring to the related explanation of step S120, the spraying behavior may be determined as abnormal behavior information. Furthermore, the abnormal behavior information and the monitoring image can be merged to generate abnormal tracing information. The abnormal tracing information is not in the agricultural mission plan, and the illegal agricultural product growth process record information, such as: a spraying action not within the farming mission plan, or a fertilizing action not within the farming mission plan, etc. Furthermore, an alarm mechanism can be triggered according to the abnormal tracing information, and illustratively, an alarm ring or an alarm voice prompt can be started. Specifically, referring to fig. 4, fig. 4 schematically shows a display interface schematic diagram of a tracing method in an agricultural production process in another exemplary embodiment of the present disclosure, and specifically shows a display interface schematic diagram that after the spraying behavior is determined as abnormal behavior information, the abnormal behavior information is merged with the monitoring image, abnormal tracing information is generated, an alarm mechanism is triggered, and then the abnormal tracing information is displayed to a relevant user. Referring to fig. 4, the alarm time is: 9/2015, 21/7: 40pm, the abnormal behavior information, namely the suspected farming behavior, and the monitoring video, namely the farm snapshot. The reason for the alarm can also be displayed on the display interface: there is no valid farming record information for this period of time. The method helps the user to intuitively and clearly know the reason of the alarm, so that the display information is more clear at a glance.
In the exemplary embodiment of the disclosure, the abnormal behavior information is combined with the monitoring image to generate the abnormal tracing information, so that the illegal agricultural behavior of the agricultural product in the growth process can be detected, the technical problem that in the prior art, only the monitoring image can be displayed, but whether the agricultural behavior is illegal or not cannot be determined is solved, and the tracing of the agricultural production process is realized. Furthermore, an alarm mechanism is triggered according to the abnormal traceability information, the illegal farming behavior can be stopped in time, the adverse effect of the illegal farming behavior on the growth process of the agricultural products is avoided, and the standardized production and processing process of the agricultural products is realized.
In an exemplary embodiment of the present disclosure, fig. 5 schematically illustrates an overall flow chart of a traceability method in an agricultural production process in an exemplary embodiment of the present disclosure, and a specific implementation manner is explained below with reference to fig. 5.
In step S501, a monitoring event (monitoring image and monitoring time) is acquired;
in step S502, it is determined whether the farming behavior type included in the monitoring image satisfies a preset traceability rule;
in step S5031, if yes (meeting a preset traceability rule), determining whether there is farming record information corresponding to the monitoring time;
in step S5032, if not (the preset tracing rule is not satisfied), exiting;
in step S5041, if yes (there is farming record information corresponding to the monitoring time), determining the farming behavior as normal behavior information;
in step S5042, generating normal traceability information according to the monitoring image and the farming record information;
in step S5051, if not (there is no agricultural record information corresponding to the monitoring time), the agricultural behavior is determined as abnormal behavior determination information;
in step S5052, anomaly tracing information is generated according to the monitoring image and the anomaly behavior information.
The present disclosure also provides a source tracing device in an agricultural production process, and fig. 6 shows a schematic structural diagram of the source tracing device in the agricultural production process in an exemplary embodiment of the present disclosure; as shown in fig. 6, the traceability device 600 in the agricultural production process can include an obtaining module 601, a determining module 602, and a determining module 603. Wherein:
the obtaining module 601 is configured to obtain a farming behavior included in the monitoring image and obtain a monitoring time corresponding to the monitoring image.
In an exemplary embodiment of the disclosure, the obtaining module is configured to obtain a farming behavior included in the monitoring image and obtain a monitoring time corresponding to the monitoring image.
In an exemplary embodiment of the present disclosure, the obtaining module is configured to preset a reference picture, and mark a reference farming behavior corresponding to the reference picture; when the monitoring image is obtained, obtaining the similarity between the monitoring image and a reference picture; and if the similarity meets a preset threshold, judging that the farming behavior contained in the monitoring image is consistent with the reference farming behavior.
The determining module 602 is configured to determine whether a target farming behavior corresponding to the monitoring time exists in the farming record information if the farming behavior meets a preset traceability rule.
In an exemplary embodiment of the disclosure, the determining module is configured to determine whether a target farming behavior corresponding to the monitoring time exists in the farming record information if the farming behavior meets a preset traceability rule.
In an exemplary embodiment of the disclosure, the determining module is configured to obtain type information corresponding to the farming behavior; and judging whether the farming behavior meets a preset traceability rule or not according to the type information.
A determining module 603, configured to determine the target farming behavior as normal behavior information if the target farming behavior exists.
In an exemplary embodiment of the disclosure, the determination module is configured to combine the farming record information and the monitoring image to generate normal traceability information.
In an exemplary embodiment of the disclosure, the determining module is configured to determine the farming behavior as the abnormal behavior information if the farming behavior does not exist in the farming record information.
In an exemplary embodiment of the disclosure, the determining module is configured to combine the abnormal behavior information with the monitoring image to generate the abnormal tracing information.
In an exemplary embodiment of the present disclosure, the determining module is configured to trigger an alarm mechanism according to the above-mentioned anomaly tracing information.
The specific details of each module in the tracing device in the agricultural production process have been described in detail in the corresponding tracing method in the agricultural production process, and therefore are not described herein again.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer storage medium capable of implementing the above method. On which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure described in the "exemplary methods" section above of this specification, when the program product is run on the terminal device.
Referring to fig. 7, a program product 700 for implementing the above method according to an embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 800 according to this embodiment of the disclosure is described below with reference to fig. 8. The electronic device 800 shown in fig. 8 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present disclosure.
As shown in fig. 8, electronic device 800 is in the form of a general purpose computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, and a bus 830 that couples the various system components including the memory unit 820 and the processing unit 810.
Wherein the storage unit stores program code that is executable by the processing unit 810 to cause the processing unit 810 to perform steps according to various exemplary embodiments of the present disclosure as described in the "exemplary methods" section above in this specification. For example, the processing unit 810 may perform the following as shown in fig. 1: step S110, acquiring farming behaviors contained in a monitoring image and acquiring monitoring time corresponding to the monitoring image; step S120, if the farming behavior meets a preset traceability rule, judging whether a target farming behavior corresponding to the monitoring time exists in farming record information; and step S130, if the target farming behavior exists, judging the farming behavior as normal behavior information.
The storage unit 820 may include readable media in the form of volatile memory units such as a random access memory unit (RAM)8201 and/or a cache memory unit 8202, and may further include a read only memory unit (ROM) 8203.
The storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 800 may also communicate with one or more external devices 1100 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 800 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 850. Also, the electronic device 800 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 860. As shown, the network adapter 860 communicates with the other modules of the electronic device 800 via the bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. A tracing method in an agricultural production process is characterized by comprising the following steps:
acquiring farming behaviors contained in a monitoring image and acquiring monitoring time corresponding to the monitoring image;
if the farming behavior meets a preset traceability rule, judging whether a target farming behavior corresponding to the monitoring time exists in farming record information;
and if the target farming behavior exists, judging the farming behavior as normal behavior information.
2. The method according to claim 1, wherein after determining the farming behavior as normal behavior information, the method further comprises:
and combining the farming record information and the monitoring image to generate normal traceability information.
3. The method of claim 1, further comprising:
and if the farming behavior does not exist in the farming record information, judging the farming behavior as abnormal behavior information.
4. The method according to claim 3, wherein after determining the farming behavior as abnormal behavior information, the method further comprises:
and merging the abnormal behavior information and the monitoring image to generate abnormal tracing information.
5. The method of claim 4, further comprising:
and triggering an alarm mechanism according to the abnormal tracing information.
6. The method according to any one of claims 1 to 4, further comprising:
presetting a reference picture, and marking a reference farming behavior corresponding to the reference picture;
when the monitoring image is obtained, obtaining the similarity between the monitoring image and the reference picture;
and if the similarity meets a preset threshold value, judging that the farming behavior contained in the monitoring image is consistent with the reference farming behavior.
7. The method of claim 6, further comprising:
acquiring type information corresponding to the farming behavior;
and judging whether the farming behavior meets the preset traceability rule or not according to the type information.
8. A device of tracing to source in agricultural production process which characterized in that includes:
the acquisition module is used for acquiring the farming behavior contained in the monitoring image and acquiring the monitoring time corresponding to the monitoring image;
the judging module is used for judging whether a target farming behavior corresponding to the monitoring time exists in farming record information or not if the farming behavior meets a preset traceability rule;
and the judging module is used for judging the farming behavior as normal behavior information if the target farming behavior exists.
9. A computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method of any one of claims 1 to 7.
10. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to execute the traceability method in the agricultural production process of any one of claims 1-7 through executing the executable instructions.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910695752.7A CN112330335A (en) | 2019-07-30 | 2019-07-30 | Tracing method and device in agricultural production process, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910695752.7A CN112330335A (en) | 2019-07-30 | 2019-07-30 | Tracing method and device in agricultural production process, storage medium and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112330335A true CN112330335A (en) | 2021-02-05 |
Family
ID=74319851
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910695752.7A Pending CN112330335A (en) | 2019-07-30 | 2019-07-30 | Tracing method and device in agricultural production process, storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112330335A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114066480A (en) * | 2021-11-08 | 2022-02-18 | 瀚云科技有限公司 | Method, device, system, equipment and storage medium for generating traceability information |
| CN116127168A (en) * | 2023-01-19 | 2023-05-16 | 重庆市农业科学院 | Crop growth real-time monitoring system and method based on Internet of things |
| CN116401417A (en) * | 2023-06-07 | 2023-07-07 | 深圳市中农网有限公司 | Hierarchical storage method based on massive agricultural product data |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011192022A (en) * | 2010-03-15 | 2011-09-29 | Japan Research Institute Ltd | Farm product monitoring method, farm product monitoring system, and farm product monitoring device |
| CN202650063U (en) * | 2011-12-12 | 2013-01-02 | 九州海原科技(北京)有限公司 | Agricultural production activity information tracing system |
| CN106339885A (en) * | 2016-08-31 | 2017-01-18 | 河南腾跃科技有限公司 | Agricultural product quality back-tracing method based on false-proof farm work information report |
| CN106454277A (en) * | 2016-11-30 | 2017-02-22 | 杭州联络互动信息科技股份有限公司 | Image analysis method and device for video monitoring |
| CN108681724A (en) * | 2018-05-25 | 2018-10-19 | 深圳春沐源控股有限公司 | Farming operations monitoring method and device |
| CN108830177A (en) * | 2018-05-25 | 2018-11-16 | 深圳春沐源控股有限公司 | Farming operations behavior checking method and device |
| CN109146130A (en) * | 2018-07-06 | 2019-01-04 | 河北溯源大数据信息技术有限公司 | Agricultural product customization is planted and whole process is traced to the source platform and method |
-
2019
- 2019-07-30 CN CN201910695752.7A patent/CN112330335A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011192022A (en) * | 2010-03-15 | 2011-09-29 | Japan Research Institute Ltd | Farm product monitoring method, farm product monitoring system, and farm product monitoring device |
| CN202650063U (en) * | 2011-12-12 | 2013-01-02 | 九州海原科技(北京)有限公司 | Agricultural production activity information tracing system |
| CN106339885A (en) * | 2016-08-31 | 2017-01-18 | 河南腾跃科技有限公司 | Agricultural product quality back-tracing method based on false-proof farm work information report |
| CN106454277A (en) * | 2016-11-30 | 2017-02-22 | 杭州联络互动信息科技股份有限公司 | Image analysis method and device for video monitoring |
| CN108681724A (en) * | 2018-05-25 | 2018-10-19 | 深圳春沐源控股有限公司 | Farming operations monitoring method and device |
| CN108830177A (en) * | 2018-05-25 | 2018-11-16 | 深圳春沐源控股有限公司 | Farming operations behavior checking method and device |
| CN109146130A (en) * | 2018-07-06 | 2019-01-04 | 河北溯源大数据信息技术有限公司 | Agricultural product customization is planted and whole process is traced to the source platform and method |
Non-Patent Citations (1)
| Title |
|---|
| 高扬: "如何经营合作社", 广东经济出版社, pages: 92 - 93 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114066480A (en) * | 2021-11-08 | 2022-02-18 | 瀚云科技有限公司 | Method, device, system, equipment and storage medium for generating traceability information |
| CN116127168A (en) * | 2023-01-19 | 2023-05-16 | 重庆市农业科学院 | Crop growth real-time monitoring system and method based on Internet of things |
| CN116127168B (en) * | 2023-01-19 | 2023-09-19 | 重庆市农业科学院 | Crop growth real-time monitoring system and method based on Internet of things |
| CN116401417A (en) * | 2023-06-07 | 2023-07-07 | 深圳市中农网有限公司 | Hierarchical storage method based on massive agricultural product data |
| CN116401417B (en) * | 2023-06-07 | 2023-09-05 | 深圳市中农网有限公司 | Hierarchical storage method based on massive agricultural product data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11347384B2 (en) | Horticultural care tracking, validation and verification | |
| CN112330335A (en) | Tracing method and device in agricultural production process, storage medium and electronic equipment | |
| US20230039566A1 (en) | Automated system and method for detection and remediation of anomalies in robotic process automation environment | |
| DE102020109670A1 (en) | METHOD AND DEVICE FOR CALLING UP A SECURITY FEATURE OF A DATA PROCESSING DEVICE DISPLAY AS A RESPONSE TO DETECTION OF A VIEWER ON THE BASIS OF DEPTH DATA | |
| US11188860B2 (en) | Injury risk factor identification, prediction, and mitigation | |
| CN110704873B (en) | Method and system for preventing sensitive data from being leaked | |
| US11797890B2 (en) | Performance manager to autonomously evaluate replacement algorithms | |
| CA3038966A1 (en) | Horticultural care tracking, validation and verification | |
| WO2018068036A1 (en) | Deriving farming operations from gps location data | |
| CN111726648A (en) | Method, device and equipment for detecting image data and computer readable storage medium | |
| CN113823396A (en) | Medical equipment management method and device, computer equipment and storage medium | |
| CN112465287B (en) | Improvement of farm cultivation quality | |
| US9158502B2 (en) | System and method for communicating between viewers of a hierarchical software design | |
| CN114422327B (en) | Alarm handling suggestion generation method, device and system and computer readable storage medium | |
| CN115273231A (en) | Information processing method, information processing apparatus, storage medium, and electronic device | |
| CN113808728A (en) | Medical equipment management method and device, computer equipment and storage medium | |
| US20130018910A1 (en) | Enterprise Intelligence ('EI') Reporting In An EI Framework | |
| CN109800124B (en) | CPU utilization monitoring method and device, electronic equipment and storage medium | |
| US20130018801A1 (en) | Enterprise Intelligence ('EI') Management In An EI Framework | |
| US20130019246A1 (en) | Managing A Collection Of Assemblies In An Enterprise Intelligence ('EI') Framework | |
| US20130018695A1 (en) | Enterprise Intelligence ('EI') Assembly Analysis In An EI Framework | |
| CN111736539B (en) | Monitoring data display method, device, system, server and storage medium | |
| CN114218453A (en) | Data display method, device and equipment and readable storage medium | |
| CN113377608A (en) | Method and device for alarming task abnormity, terminal equipment and storage medium | |
| Cheong et al. | Pestrapp mobile app: a trap setting application for real-time entomological field and laboratory study. |
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 |