CN116205748A - Intelligent Internet of things-based precise damage assessment method and device for cultivation insurance - Google Patents
Intelligent Internet of things-based precise damage assessment method and device for cultivation insurance Download PDFInfo
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Abstract
An intelligent Internet of things-based method and device for accurately assessing the damage of a cultivation insurance relate to the technical field of intelligent monitoring, and solve the technical problem of how to provide a method for accurately assessing the damage of the cultivation insurance, and the method comprises the following steps: quick snapshot is carried out on the damage assessment, and the size of the damage assessment is identified according to the snapshot result; identifying the physical ID and the unique identifier of the earmark of the damage assessment through the mobile terminal; comparing the tag physical ID and the unique identifier of the damage assessment standard with a livestock information base, if the livestock information base has a fence-entering livestock record with the tag physical ID and the unique identifier matched, continuing to assess damage, otherwise ending the damage assessment; collecting multi-angle image information and weight information of the damage assessment standard; submitting the multi-angle image information, the weight information and the size of the damage assessment to a server; the method combines the intelligent recognition technology of the intelligent camera and the intelligent perception traceability technology of the Internet of things of the ear tag, and achieves accurate damage assessment of the cultivation insurance.
Description
Technical Field
The invention relates to the technical field of intelligent monitoring.
Background
The farming industry is an important component in the development of agriculture. Along with the rapid development of the breeding industry, the scale of the breeding industry is continuously enlarged, epidemic diseases are frequent, meanwhile, extreme weather is increased, natural disasters frequently occur, and a larger risk is brought to the development of the breeding industry. The insurance of the breeding industry is taken as a great branch of agricultural insurance, is an important component part of an agricultural financial service system, is an important measure for supporting the development of the breeding industry by the state, and has important significance in helping vast breeding enterprises (farmers) to disperse and transfer risks, improving the risk resistance, promoting the stable and healthy development of the breeding industry, ensuring the stable supply of agricultural and animal products, maintaining the social stability and the like.
In order to establish a long-acting mechanism for guaranteeing stable development of live pig production, stabilize market supply, meet consumption requirements, increase farmers' receipts, the country continuously proposes to develop agricultural insurance greatly, support agricultural development, establish a sow-breeding insurance system, ensure that the government burden is 80% and the farmer (farm) burden is 20%, and bring the sow-breeding insurance into the range of central financial subsidy. And gradually expanding the premium subsidy range of the sow and cow breeding insurance, and expanding the premium subsidy range of the fattening pigs to the whole country. The national policy injects strong power into the insurance of the breeding industry and promotes the rapid development of the insurance of the breeding industry.
Since 2007, each insurance company responds positively to cooperate with developing a test point for the insurance of the farming industry, which is rapidly developed in the main livestock production area of the country. But the insurance development of the farming industry shows strong contrast while the annual acceleration of the domestic agricultural insurance is 36 percent. After undergoing the first two years of rapid development, the baoya premium is greatly withered in 2009, and the premium income is reduced by more than 30%; in 2010, the insurance of the farming industry further increases by about 22%; the method has the advantages that 2690 ten thousand sows can be bred in the whole industry in 2011, 157 ten thousand cows are bred, 6.5 hundred million cows are bred from home, 27 ten thousand mu of aquaculture water surface is bred, the risk protection is up to 700 hundred million yuan, and the method plays a positive role in serving rural economic and social development, guaranteeing agricultural production investment and the like. However, when the insurance business of the breeding industry is rapidly developed, the insurance reimbursement of the whole industry of the breeding industry in 2011 reaches 18 hundred million yuan, and continuous loss occurs in a plurality of dangerous operations such as sow, dairy cow and the like, so that the problems and contradictions in the insurance development of the breeding industry are prominent, and the method mainly comprises the following steps:
in a first aspect, the number of targets is difficult to verify. Firstly, the fluctuation of the short growing period of the live pigs is strong, the target number in the underwriting process is difficult to determine, and certain irrational property exists; secondly, for a large-scale farm, the farm is subjected to full-closed management, and outsiders cannot conveniently enter a production area to check the number of underwriting head by head; thirdly, under the influence of factors such as insufficient supervision of the breeding industry, unpublished data, market competition, rough management of the breeding industry and the like in individual areas, insurance companies cannot identify and distinguish animal groups which are naturally eliminated or are not in the range of insurance conditions in the production process of the breeding industry, the number of the insurance groups meeting the conditions cannot be truly determined, and a large hidden risk is born.
In the second aspect, the management risk and the policy risk are difficult to control. Most domestic farmers are educated limitedly, knowledge is deficient, technology is weak, management is not in place, mortality is high, underwriting risk is high, and insurance companies bear larger policy risk.
In a third aspect, ethical risk is difficult to control. The policy-based agricultural insurance moral risk occurs not only on the part of the insured and insured, but also on the part of government agencies that assist the insurer in managing and managing the agricultural insurance business.
In order to solve the problems, the livestock carrying ear tag in the prior art is a fundamental means for livestock epidemic prevention and information collection, and the full coverage of the livestock carrying ear tag is required. However, the middle ear tag can be replaced, so that the basic information of insurance work cannot be completely and accurately reflected, the insurance claim generates a moral risk, and the benefits of farmers and insurance companies are not guaranteed finally. Because of the field closed management, insurance company personnel cannot conveniently enter a production area to verify the number of the targets, so that the problems of inaccurate verification of the number of the targets and untimely processing of each event in the processes of underwriting, damage assessment and claim settlement are caused, and the problems that the insurance targets of the aquaculture are subjected to cheating protection by using a plurality of cheating protection means in the claim settlement stage, such as repeated report of the same target, false report of the target and the like are solved.
Therefore, how to provide a method and a system for accurately determining damage of cultivation insurance becomes a technical problem to be solved in the field.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method and a system for accurately assessing the damage of the cultivation insurance based on the intelligent Internet of things.
Based on the same inventive concept, the invention has four independent technical schemes:
1. an intelligent Internet of things-based precise damage assessment method for cultivation insurance comprises the following steps:
quick snapshot is carried out on the damage assessment, and the size of the damage assessment is identified according to the snapshot result;
identifying the physical ID and the unique identifier of the earmark of the damage assessment through the mobile terminal;
comparing the tag physical ID and the unique identifier of the damage assessment standard with a livestock information base, if the livestock information base has a fence-entering livestock record with the tag physical ID and the unique identifier matched, continuing to assess damage, otherwise ending the damage assessment;
collecting multi-angle image information and weight information of the damage assessment standard;
and submitting the multi-angle image information, the weight information and the size of the damage assessment to a server.
Further, the damage assessment scale is placed in the damage assessment system, the damage assessment system comprises an intelligent camera and a damage assessment scene, the intelligent camera is arranged above the damage assessment scene, the damage assessment scene is a plane with a boundary line, a weighing instrument is arranged in a closed area surrounded by the boundary line, a line segment forming the boundary line is of a preset length, and a width mark is arranged on the boundary line and used for measuring the size of the damage assessment scale.
Further, the livestock information base is established when the livestock is in the fence before the insurance, and the establishment of the livestock information base comprises the following steps:
generating a time stamp ID as a unique identifier by using a blockchain technology;
binding the physical ID of the tag of the livestock in the fence with the unique identifier in one-to-one two-way association, and inputting the tag into a livestock information base.
Further, the establishment of the livestock information base further comprises the following steps: acquiring basic information of the livestock in the fence through a mobile terminal, carrying out one-to-one association on the basic information and the physical ID of the ear tag, and inputting the basic information into a livestock information base; the basic information comprises an image, a column entering time, weight, gender, age and variety, wherein the image comprises a front livestock outline image, an upper livestock outline image, a lower livestock outline image and a rear livestock outline image.
Further, collecting multi-angle image information of the impairment target includes: dai Er, a front image of the livestock ear, a back image of the livestock ear, a front image of the outline of the damage assessment, an upper image of the outline of the damage assessment, a lower image of the outline of the damage assessment and a rear image of the outline of the damage assessment.
Further, after collecting the multi-angle image information and the weight information of the damage assessment, the method further comprises the following steps: and disassembling the ear tag of the damage calibration.
Further, the whole damage assessment process is carried out on the damage assessment scene video through the intelligent camera, and the method specifically comprises the following steps: before acquiring ear tag images of the damage assessment, starting video recording of the damage assessment scene, and recording video recording starting time; after the ear tag of the damage assessment mark is disassembled, finishing video recording of the damage assessment scene, and recording video recording finishing time;
and video data obtained by video recording is submitted to a server together with the multi-angle image information, the weight information and the size of the damage assessment.
2. Accurate loss device of deciding of breed insurance based on intelligence thing networking includes:
the snapshot module is used for rapidly taking a snapshot of the damage assessment, and identifying the size of the damage assessment according to the snapshot result;
the ID identification module is used for identifying the physical ID and the unique identification of the earmark of the damage calibration standard through the mobile terminal;
the ID comparison module is used for comparing the tag physical ID and the unique identifier of the damage assessment with the livestock information base, if the livestock information base has a fence-entering livestock record with the tag physical ID and the unique identifier matched, continuing the damage assessment, otherwise, ending the damage assessment;
the acquisition module is used for acquiring multi-angle image information and weight information of the damage assessment;
and the damage assessment module is used for submitting the multi-angle image information, the weight information and the size of the damage assessment to a server.
3. A computer readable storage medium storing a computer program which when executed by a processor implements the method described above.
4. An electronic device comprises a processor and a storage device, wherein a plurality of instructions are stored in the storage device, and the processor is used for reading the plurality of instructions in the storage device and executing the method.
The invention provides an intelligent Internet of things-based cultivation insurance accurate damage assessment method, an intelligent Internet of things-based cultivation insurance accurate damage assessment device and electronic equipment, which at least comprise the following beneficial effects:
(1) The intelligent recognition technology of the intelligent camera and the intelligent perception traceability technology of the internet of things of the ear tag are combined, so that the problems that the verification of the number of the targets is inaccurate and each event is not timely processed in the process of underwriting, damage assessment and claim settlement due to the fact that personnel of an insurance company cannot enter a production area to verify the number of the targets conveniently due to closed management of a field area are solved, and the cost of manpower and material resources time and the like of the insurance company and farmers can be reduced through the full-automatic flow of on-line underwriting, damage assessment and claim settlement;
(2) According to the invention, through a whole-course video recording means, the behavior of replacing the damage target object or detaching the same ear tag and putting the same ear tag on different livestock for repeated reporting is avoided, the damage target object is photographed at multiple angles, more comprehensive information acquisition is carried out on the damage target object, so that the damage target object is avoided being replaced, and the problem that the insurance target of the aquaculture is cheated and protected by using various cheating and protecting means in the claim settling stage, such as repeated reporting, false reporting and the like, of the same target object is solved.
Drawings
FIG. 1 is a flow chart of an embodiment of an intelligent Internet of things-based method for accurately assessing the damage of a cultivation insurance;
fig. 2 is a schematic structural diagram of an embodiment of a damage assessment system in the method for accurately assessing damage of cultivation insurance based on the intelligent internet of things provided by the invention;
fig. 3 is a flowchart of an application scenario of the cultivation insurance accurate damage assessment method based on the intelligent internet of things.
Reference numerals: 1-intelligent camera, 2-damage scene, 3-boundary line, 4-weighing instrument.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
Embodiment one:
referring to fig. 1, in some embodiments, a method for accurately assessing the damage of a cultivation insurance based on intelligent internet of things is provided, including:
s1, rapidly capturing an index mark, and identifying the size of the index mark according to a capturing result;
s2, identifying the physical ID and the unique identification of the earmark of the damage calibration standard through the mobile terminal;
s3, comparing the physical ID of the earmark of the damage assessment mark with the unique identification with a livestock information base, if the livestock information base has a fence-entering livestock record with the matched physical ID of the earmark and the unique identification, continuing the damage assessment, otherwise, ending the damage assessment;
s4, collecting multi-angle image information and weight information of the damage assessment standard;
and S5, submitting the multi-angle image information, the weight information and the size of the damage scale to a server.
In the process of damage assessment, the damage assessment standard is placed in a damage assessment system. Referring to fig. 2, the damage assessment system comprises an intelligent camera 1 and a damage assessment scene 2, wherein the intelligent camera 1 is arranged above the damage assessment scene 2, the damage assessment scene 2 is a plane with a boundary line 3, a weighing instrument 4 is arranged in a closed area surrounded by the boundary line 3, a line segment forming the boundary line 3 is a preset length, and a width mark is arranged on the boundary line 3 and used for measuring the size of the damage assessment.
As a preferred embodiment, the boundary line is a square with a side length of 3 m.
Optionally, in step S1, the intelligent camera 1 above the damage assessment scene 2 is adopted to perform quick snapshot, after a person withdraws from the damage assessment scene, the damage assessment button is clicked at the mobile terminal to trigger the damage assessment process, and the intelligent camera above automatically captures and quickly identifies the length and width of the damage assessment object.
Optionally, in step S2, when the physical ID and the unique identifier of the ear tag are identified by the mobile terminal, NFC identification is adopted.
Optionally, the livestock information base mentioned in step S3 is established before the application. The livestock information base is established when the livestock is in the fence before the insurance application, and the establishment of the livestock information base comprises the following steps:
s31, generating a time stamp ID by using a block chain technology;
s32, binding the physical IDs of the earmarks of the livestock in the fence with the IDs of the time stamps in a one-to-one two-way association manner, and inputting the physical IDs into a livestock information base;
s33, acquiring basic information of the livestock in the fence through the mobile terminal, correlating the basic information with the physical ID of the ear tag, and inputting the basic information into a livestock information base.
Before the label insuring stage, the physical ID of the ear label and the timestamp ID generated by using the block chain technology are bound in a one-to-one two-way association mode and put in storage, and then the livestock are marked with double ID ear labels. When the intelligent terminal is used for identifying the earmark, the physical ID can be identified, and the unique identifier of the timestamp ID can also be identified. Most of livestock are similar in growth and indistinct in naked eyes, the identity of the livestock is determined by adopting a blockchain technology, and the time stamp generated by the blockchain technology can ensure that each time stamp ID is a unique identifier, so that the uniqueness of each livestock in a livestock information base is ensured.
When livestock enter the fence, basic livestock information is collected through the mobile terminal and is associated with the ear tag information to be put in storage. The method comprises the steps that basic information of livestock books is collected through a mobile terminal, wherein the basic information comprises the time, weight, sex, age, variety and photo of the livestock, and the photo comprises four angles of photo: front of the animal profile, above the animal profile, below the animal profile, and behind the animal profile. And recording the number of the columns and the image information by an intelligent camera above the column entering channel when the livestock enter the columns. The step is to determine the information when entering the column through information acquisition, so that the later information is convenient to review.
Optionally, the basic information includes an image, a time of entry, a weight, a sex, an age, and a variety, and the image includes an image before the outline of the livestock, an image above the outline of the livestock, an image below the outline of the livestock, and an image behind the outline of the livestock.
Optionally, in step S3, if the livestock information base does not have the matching check ID of the in-fence livestock record with the matched tag physical ID and the unique identifier, an early warning is sent, and the damage assessment is ended.
And simultaneously matching the physical ID of the tag with the unique identifier in the livestock information base, and continuing to evaluate the damage only when the column entry record of the simultaneous matching of the physical ID of the tag with the unique identifier exists in the livestock information base. Through the step of double checking and matching of the physical ID of the earmark and the unique identification of the time stamp ID, the guarantee of more uniqueness is provided, the condition of midway earmark replacement can be effectively avoided, more accurate damage assessment is realized, and the risk of an insurance company is reduced.
As a preferred implementation mode, before acquiring the image of the damage assessment, starting video recording of the damage assessment scene through an intelligent camera above and recording video recording starting time; and after the ear tag of the damage assessment mark is disassembled, finishing video recording of the damage assessment scene and recording video recording finishing time. And video data obtained by video recording is submitted to a server together with the multi-angle image information, the weight information and the size of the damage assessment.
It should be noted that, under the condition that the time for identifying the physical ID and the unique identifier of the earmark of the damage target by the mobile terminal is effectively recorded, whether the ID identification time is between the video recording start time and the video recording end time can be judged, so that the obtained physical ID and the unique identifier result of the earmark obtained by NFC identification are really the data obtained in the damage determination process, the possibility of replacing the target is further avoided, and more accurate damage determination is realized.
After video recording is started, the situation that the damage assessment personnel leave the damage assessment scene halfway is ensured by video recording, damage assessment objects are not replaced, the specific process of the damage assessment personnel for collecting multi-angle object image information can be monitored, and the replacement of the object is prevented from being falsified; and after the damage assessment is finished, confirming that the ear tag is dismantled, deleting relevant data from the livestock information base, and avoiding repeated report of the same tag.
In step S4, collecting multi-angle image information of the impairment target includes: dai Er a front image of the livestock ear, a back image of the livestock ear wearing the ear tag, a front image of the livestock outline, an upper image of the livestock outline, a lower image of the livestock outline, and a rear image of the livestock outline.
It should be noted that, no matter when the livestock enters the fence or when the image information is collected in damage assessment, the livestock is collected with a plurality of angle outline images, so that the target images are collected more comprehensively, the incomplete information caused by single shooting angle is avoided, the livestock is not found to change, and thus the cheating protection actions such as multiple reporting of the same target are avoided.
Step S4, after collecting the multi-angle image information and the weight information of the damage assessment, the method further comprises the following steps: and disassembling the ear tag of the damage assessment. This step avoids fraudulent conduct of multiple reports of the same target.
In step S5, the collected multi-angle image information, weight information and the size of the damage assessment scale are submitted to a server, and video data obtained by video recording of the intelligent camera above the damage assessment scene is automatically returned and archived to form a report.
After forming the report of the damage assessment standard, the damage assessment process is finished and enters an auditing stage. After receiving the report information from the server, the auditing personnel compares the livestock in-fence information with the multi-angle image information, the weight information and the size information provided in the report, meanwhile, the auditing personnel refer to the video data to avoid falsification, and the auditing conclusion is obtained by comparing and checking. Specifically, it can be clearly seen from video data when a damage person scans and identifies physical ID and unique identification of the object ear tag through the NFC of the intelligent terminal, and the physical ID and unique identification are compared with the acquisition time of the ID, so that the authenticity of the ID is ensured; after the damage assessment is started, the video is recorded to ensure that damage assessment personnel do not leave the damage assessment scene halfway and do not replace damage assessment objects, and the specific process of the damage assessment personnel for collecting multi-angle object image information can be monitored, so that the replacement of the objects is avoided; and after the damage assessment is finished, confirming that the ear tag is dismantled, deleting relevant data from the livestock information base, and avoiding repeated report of the same tag.
Referring to fig. 3, in a specific application scenario, the whole process includes several stages of ear tag data writing, target risk emergence, damaged target information acquisition, information auditing and damage assessment result acquisition, wherein the target risk emergence and damaged target information acquisition are divided into 6 steps:
firstly, preparing damage assessment: when the target is at risk, the damage assessment target is moved into the damage assessment scene, the personnel withdraw from the damage assessment scene, the intelligent camera is arranged above the damage assessment scene, the damage assessment scene below can be shot, the scene comprises a boundary line with 3m x 3m square, the boundary line is provided with an obvious width mark, and a weighing instrument is arranged on the ground, as shown in fig. 2. The boundary line and the weighing instrument can determine the information of the body length, the body weight and the like.
Secondly, starting to evaluate the loss: after the personnel withdraw from the damage assessment scene, the damage assessment button is clicked at the mobile terminal to trigger the damage assessment flow, and the intelligent camera above automatically captures images, so that the length and width of the damage assessment object can be rapidly identified.
Thirdly, starting video recording: and recording the damage assessment flow in the whole process, and recording the starting time and the ending time.
Fourth, target identification: after video recording is started, a damage assessment person does not obtain a damage assessment scene before damage assessment is finished, a mobile terminal is used for identifying that the livestock earmark NFC is provided with a physical ID and a unique identifier of the target, whether the physical ID and the unique identifier of the target are matched is checked, when the unique identifier of the livestock is empty or is not matched with database information, early warning is sent out, damage assessment is finished, and otherwise, the damage assessment process is continued.
Fifthly, information acquisition: and after the identification of the ID and the unique identification of the target, photographing the damage calibration target, wherein the damage calibration target comprises a Dai Er target livestock ear front photo, a target livestock ear back photo, a livestock outline front photo, a livestock outline upper photo, a livestock outline lower photo, a livestock outline rear photo and the like, and after photographing is completed, writing necessary information such as the weight, the age and the like of the target in the mobile terminal.
Sixth, the earmark is taken down: and after the information acquisition is completed, the ear tag is disassembled.
And at the moment, the loss assessment information acquisition is completed, data is submitted to a server, the loss assessment flow is completed, and the video above the loss assessment scene is automatically returned and filed to form a report. After the damaged mark forms the report, the audit stage is carried out, after the audit personnel receives the report information, the target column entering information is obtained through the livestock information base, and then the multi-angle image information of the damage mark collected in the report and the video above the damage mark are compared and checked to obtain the audit conclusion, so that insurance claims are settled.
Embodiment two:
in some embodiments, a precise damage assessment device for cultivation insurance based on intelligent internet of things is provided, comprising:
the snapshot module is used for rapidly taking a snapshot of the damage assessment, and identifying the size of the damage assessment according to the snapshot result;
the ID identification module is used for identifying the physical ID and the unique identification of the earmark of the damage calibration standard through the mobile terminal;
the ID comparison module is used for comparing the tag physical ID and the unique identifier of the damage assessment with the livestock information base, if the livestock information base has a fence-entering livestock record with the tag physical ID and the unique identifier matched, continuing the damage assessment, otherwise, ending the damage assessment;
the acquisition module is used for acquiring multi-angle image information and weight information of the damage assessment;
and the damage assessment module is used for submitting the multi-angle image information, the weight information and the size of the damage assessment to a server.
Specifically, in the damage assessment process, the damage assessment mark is placed in the damage assessment system, the damage assessment system comprises an intelligent camera and a damage assessment scene, the intelligent camera is arranged above the damage assessment scene, the damage assessment scene is a plane with a boundary line, a weighing instrument is arranged in a closed area surrounded by the boundary line, a line segment forming the boundary line is of a preset length, and a width mark is arranged on the boundary line and used for measuring the size of the damage assessment mark.
In the ID comparison module, the livestock information base is established when the livestock is in the fence before the insurance, and the establishment of the livestock information base comprises the following steps:
generating a time stamp ID as a unique identifier by using a blockchain technology;
binding the physical ID of the tag of the livestock in the fence with the unique identifier in one-to-one two-way association, and inputting the tag into a livestock information base.
In some embodiments, the establishment of the livestock information base further comprises the steps of: acquiring basic information of the livestock in the fence through a mobile terminal, carrying out one-to-one association on the basic information and the physical ID of the ear tag, and inputting the basic information into a livestock information base; the basic information comprises an image, a column entering time, weight, gender, age and variety, wherein the image comprises a front livestock outline image, an upper livestock outline image, a lower livestock outline image and a rear livestock outline image.
The acquisition module is also used for acquiring the multi-angle image information of the damage assessment, and the acquisition module comprises: dai Er a front image of the livestock ear, a back image of the livestock ear wearing the ear tag, a front image of the livestock outline, an upper image of the livestock outline, a lower image of the livestock outline, and a rear image of the livestock outline.
In some embodiments, after collecting the multi-angle image information and the weight information of the damage scale, the method further includes the following steps: and disassembling the ear tag of the damage calibration.
In some embodiments, the damage assessment process records the damage assessment scene through the intelligent camera, and specifically includes: before acquiring ear tag images of the damage assessment, starting video recording of the damage assessment scene, and recording video recording starting time; after the ear tag of the damage assessment mark is disassembled, finishing video recording of the damage assessment scene, and recording video recording finishing time;
and video data obtained by video recording is submitted to a server together with the multi-angle image information, the weight information and the size of the damage assessment.
Embodiment III:
a computer readable storage medium storing a computer program which when executed by a processor implements the method described above.
Embodiment four:
an electronic device comprising a processor and a storage device, wherein a plurality of instructions are stored in the storage device, and the processor is configured to read the plurality of instructions in the storage device and execute the method.
According to the method and the device for accurately assessing the damage of the cultivation insurance based on the intelligent Internet of things, the intelligent identification technology of the intelligent camera and the intelligent perception traceability technology of the Internet of things of the ear tag are combined, so that the problems that the quantity of the targets is inaccurate due to the fact that personnel of an insurance company cannot conveniently enter a production area to verify the quantity of the targets, and all events are not timely processed in the processes of underwriting, assessing and claiming are solved, and the cost of manpower and material resources time and the like of the insurance company and farmers can be reduced through the full-automatic processes of on-line underwriting, assessing and claiming; through the means of whole-course video recording, avoid replacing the thing of the damage mark or with the action of taking out the case of putting same ear tag on different livestock many times, shoot the damage mark through the multi-angle, thereby carry out more comprehensive information acquisition to the damage mark and avoid replacing the thing of the damage mark, solved the industry insurance mark and used a great deal of cheating the protection means to carry out cheating protection action in the claim stage, for example same target carry out the case of giving out many times, false report mark etc..
It should be appreciated that the above-described integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer-readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by instructing related hardware by a computer program, where the computer program may be stored in a computer readable storage medium, and the computer program may implement the steps of each method embodiment described above when executed by a processor. The computer program comprises computer program code, and the computer program code can be in a source code form, an object code form, an executable file or some intermediate form and the like. The computer readable medium may include: any entity or device capable of carrying the computer program code described above, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. The content of the computer readable storage medium can be appropriately increased or decreased according to the requirements of the legislation and the patent practice in the jurisdiction.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/device embodiments described above are merely illustrative, e.g., the division of modules or elements described above is merely a logical functional division, and may be implemented in other ways, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention. It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. An intelligent Internet of things-based cultivation insurance accurate damage assessment method is characterized by comprising the following steps:
quick snapshot is carried out on the damage assessment, and the size of the damage assessment is identified according to the snapshot result;
identifying the physical ID and the unique identifier of the earmark of the damage assessment through the mobile terminal;
comparing the physical ID of the earmark of the damage assessment with the unique identifier with a livestock information base, if the livestock information base has a fence-entering livestock record with the physical ID of the earmark and the unique identifier matched, continuing the damage assessment, otherwise ending the damage assessment;
collecting multi-angle image information and weight information of the damage assessment standard;
and submitting the multi-angle image information, the weight information and the size of the damage assessment to a server.
2. The method according to claim 1, wherein the damage assessment is placed in a damage assessment system, the damage assessment system comprises an intelligent camera and a damage assessment scene, the intelligent camera is arranged above the damage assessment scene, the damage assessment scene is a plane with a boundary line, a weighing instrument is arranged in a closed area surrounded by the boundary line, a line segment forming the boundary line is a preset length, and a width mark is arranged on the boundary line and used for measuring the size of the damage assessment.
3. The method of claim 1, wherein the livestock information base is established at the time of the livestock being placed in the rail prior to the application, the establishment of the livestock information base comprising the steps of:
generating a time stamp ID as a unique identifier by using a blockchain technology;
binding the physical ID of the tag of the livestock in the fence with the unique identifier in one-to-one two-way association, and inputting the tag into a livestock information base.
4. A method according to claim 3, wherein the establishment of the livestock information base further comprises the steps of: acquiring basic information of the livestock in the fence through a mobile terminal, carrying out one-to-one association on the basic information and the physical ID of the ear tag, and inputting the basic information into a livestock information base; the basic information comprises an image, a column entering time, weight, gender, age and variety, wherein the image comprises a front livestock outline image, an upper livestock outline image, a lower livestock outline image and a rear livestock outline image.
5. The method of claim 1, wherein acquiring the multi-angle image information of the impairment scale comprises: dai Er, a front image of the livestock ear, a back image of the livestock ear, a front image of the outline of the damage assessment, an upper image of the outline of the damage assessment, a lower image of the outline of the damage assessment and a rear image of the outline of the damage assessment.
6. The method according to claim 2, further comprising the steps of, after collecting the multi-angle image information and the weight information of the impairment scale: and disassembling the ear tag of the damage calibration.
7. The method according to claim 6, wherein the damage scene is recorded through the intelligent camera in the whole damage process, specifically comprising: before acquiring ear tag images of the damage assessment, starting video recording of the damage assessment scene, and recording video recording starting time; after the ear tag of the damage assessment mark is disassembled, finishing video recording of the damage assessment scene, and recording video recording finishing time;
and video data obtained by video recording is submitted to a server together with the multi-angle image information, the weight information and the size of the damage assessment.
8. Accurate loss device of demarcating of breed insurance based on intelligence thing networking, its characterized in that includes:
the snapshot module is used for rapidly taking a snapshot of the damage assessment, and identifying the size of the damage assessment according to the snapshot result;
the ID identification module is used for identifying the physical ID and the unique identification of the earmark of the damage calibration standard through the mobile terminal;
the ID comparison module is used for comparing the tag physical ID and the unique identifier of the damage assessment with the livestock information base, if the livestock information base has a fence-entering livestock record with the tag physical ID and the unique identifier matched, continuing the damage assessment, otherwise, ending the damage assessment;
the acquisition module is used for acquiring multi-angle image information and weight information of the damage assessment;
and the damage assessment module is used for submitting the multi-angle image information, the weight information and the size of the damage assessment to a server.
9. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method according to claims 1-7.
10. An electronic device comprising a processor and a memory means, wherein a plurality of instructions are stored in the memory means, the processor being configured to read the plurality of instructions in the memory means and to perform the method of claims 1-7.
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