CN106899683A - A kind of family based on big data and image recognition conserves the APP of kaffir lily - Google Patents
A kind of family based on big data and image recognition conserves the APP of kaffir lily Download PDFInfo
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- CN106899683A CN106899683A CN201710147910.6A CN201710147910A CN106899683A CN 106899683 A CN106899683 A CN 106899683A CN 201710147910 A CN201710147910 A CN 201710147910A CN 106899683 A CN106899683 A CN 106899683A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/38—Creation or generation of source code for implementing user interfaces
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
- G06V20/36—Indoor scenes
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/52—Network services specially adapted for the location of the user terminal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
- H04M1/72457—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to geographic location
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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Abstract
The invention discloses the APP that a kind of family based on big data and image recognition conserves kaffir lily, it is characterized in that the cauline leaf for scanning kaffir lily with camera after User logs in APP spends position, to cloud server, it is kaffir lily and its growing state and pest and disease damage situation that cloud server uses image recognition technology sentence section to go out the sample to the automatic image datas and geographic location data is activation by kaffir lily sample of APP;The data similar to the close growing state in sample geographical position are transferred in kaffir lily large database concept again to compare, so as to draw the maintenance process for the sample kaffir lily and push on APP.Through the above way, the present invention can allow the user for not possessing kaffir lily maintenance knowledge completely that the simple operations for sweeping are swept using APP, it is analyzed rapidly and accurately to the kaffir lily growing state transplanted, instructs user to take the measure of the scientific and reasonable prevention and control of plant diseases, pest control Yu routine servicing.
Description
Technical field
The present invention relates to big data and field of image recognition, more particularly to a kind of family based on big data Yu image recognition
Front yard conserves the APP of kaffir lily.
Background technology
With the raising that city dweller is required domestic environment, the user of family plant kaffir lily is more and more, but by
Lack professional knowledge, and main purpose mostly to enjoy the enjoyment that kaffir lily brings life in the crowd of floriculture at home, rather than
The agricultural knowledge that to study those for city dweller and very strange, and Urban population rhythm of life is fast, study does not feel emerging originally
The time and efforts of the agricultural knowledge of interest is few, but kaffir lily is a kind of relatively enervated flower variety, conserves improper being subject to
The injury of pest and disease damage, when the kaffir lily of oneself plantation occurs pest and disease damage, it tends to be difficult to which with the naked eye the experience with oneself is told
The type of pest and disease damage is suited the remedy to the case so as to be difficult to find that correct method, and traditional way is that internet opinion is uploaded to after taking pictures
Altar, seeks help other people, but this method slowly effect, and when running into online friend each sticks to his own version or argument, user is difficult to differentiate and takes correct
Measure, causes the pest and disease damage that kaffir lily is suffered to be delayed treatment, the consequence for causing undergrowth even dead, and a kind of based on big
Data use big data and image recognition technology with the APP of the family maintenance kaffir lily of image recognition, have provided the user cloud meter
The help of calculation, can allow the user for being ignorant of kaffir lily maintenance knowledge completely also most timely can implement science to sample kaffir lily
Maintenance measure.
The content of the invention
Gentleman is conserved the present invention solves the technical problem of a kind of family based on big data and image recognition is provided
Blue APP, can allow the user for not possessing kaffir lily maintenance knowledge completely to scan transplanted kaffir lily by mobile phone camera
Cauline leaf flower position can just reach the rapid day for precisely recognizing kaffir lily institute illness insect pest type and prophylactico-therapeutic measures and kaffir lily
Normal maintenance process, instructs user to carry out the maintenance of kaffir lily.
In order to solve the above technical problems, one aspect of the present invention is:A kind of big data that is based on is provided with figure
As the family of identification conserves the APP of kaffir lily, comprise the following steps:
Step one:The smart mobile phone hardware that high-definition camera will be carried is carried and a kind of supported with the family of image recognition based on big data
The APP of kaffir lily is protected, by APP using being connected with image identification system with high in the clouds big data, smart mobile phone APP nodes is built, often
One APP node on behalf, one APP user;
Step 2:When User logs in APP is applied, APP automatically passes the APP application messages of user geographical position, traveling mode
It is sent to the big data analysis system in high in the clouds;
Step 3:User opens APP Built-in Images identification function, and scans the stem of kaffir lily respectively with smart mobile phone camera
Leaf site and flower position, APP sends prompt tone after scanning successfully, and the pictorial information that will be scanned is transmitted to high in the clouds image
Discriminance analysis system;
Step 4:High in the clouds image recognition analysis system according at the user obtain several kaffir lily samples pictures, through artificial intelligence
Can image identification system pick out the flowers for kaffir lily, and information identification in stem, leaf, flower samples pictures goes out the sample
Whether this kaffir lily suffers from the species and degree of pest and disease damage and ill insect pest;
Step 5:The big data analysis system in high in the clouds combines the positional information and current temporal information of the user, excavates this
The landform of user position, landforms, climatic information, and combine the species of the sample plant that high in the clouds image identification system is provided
With ill insect pest information, the maintenance of the science under automatic search and the kaffir lily planting location and growing state under similar environment
Method and pest management method;
Step 6:The science that the kaffir lily of the sample that high in the clouds big data analysis system obtains cloud computing should take is correct
Maintenance process is transferred to the smart mobile phone APP of the user, and mobile phone A PP is anti-by the screen and loudspeaker of smart mobile phone by final result
Feed the user;
Step 7:User takes corresponding maintenance measure according to the answer that APP applications are given to the kaffir lily, in certain day
After number, the result whether kaffir lily growing state is effectively improved is fed back to APP by user;
Step 8:APP sends to high in the clouds big data analysis system the feedback of user, and such as sample obtains effective Feedback,
Then by its typing large database concept, help is provided for the user for after;Such as the sample obtains negative feedback, then require user again
It is secondary that stem, leaf, the scanned picture data of flower of the kaffir lily are provided, and large database concept is labeled, repeat step step 4
To step 8, untill stopping feedback when the positive feedback or user that user is obtained in step 8 are in step 7.
Further, APP is using the same monarch that the same place place of the positional information of user and scanning input is transplanted
Sub blue stem, leaf, the pictorial information of three key positions is spent to be transferred to cloud server, the image identification system of cloud server
Mass data in database is compared with the sample data information, the entitled kaffir lily of the plant and its pest and disease damage letter is drawn
Breath;The big data analysis system in high in the clouds by the category information combining position information of the sample and large database concept with same disease
The characteristics for the treatment of method of the kaffir lily of insect pest combines plantation area, after comparing, show that the sample kaffir lily is optimal
Maintenance solution, and the program is transferred to user mobile phone.
Further, APP is given the user after sample kaffir lily most preferably conserves solution, possesses user to kaffir lily exhibition
The feedback function after embodiment, and the feedback by information and check and correction are opened, contributes to the large data center database in high in the clouds
It is abundant with update, be allowed to the self-teaching function of possessing machine while analyze data, allow cloud computing result with user
Increasing for sample size and it is more accurate.
The beneficial effects of the invention are as follows:The geographical location information and kaffir lily cauline leaf flower that the present invention is sent by user shine
Piece information, the kaffir lily database information planted with each department of magnanimity on cloud computing server using image recognition technology is entered
Row is compared, and draws the prevention and control of plant diseases, pest control and maintenance measure for user's kaffir lily growing state, and will by APP of the invention
Result feeds back to user mobile phone, is run into during solving the problems, such as user maintenance kaffir lily, reduces user learning gentleman
The work of orchid maintenance relevant knowledge, makes the life of user more fine.
Brief description of the drawings
Fig. 1 is a kind of control flow chart of the APP of the family maintenance kaffir lily based on big data and image recognition of the present invention.
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
As shown in figure 1, be the APP that a kind of family based on big data and image recognition conserves kaffir lily, including following step
Suddenly:
Step one:The smart mobile phone hardware that high-definition camera will be carried is carried and a kind of supported with the family of image recognition based on big data
The APP of kaffir lily is protected, by APP using being connected with image identification system with high in the clouds big data, smart mobile phone APP nodes is built, often
One APP node on behalf, one APP user;
Step 2:When User logs in APP is applied, APP automatically passes the APP application messages of user geographical position, traveling mode
It is sent to the big data analysis system in high in the clouds;
Step 3:User opens APP Built-in Images identification function, and scans the stem of kaffir lily respectively with smart mobile phone camera
Leaf site and flower position, APP sends prompt tone after scanning successfully, and the pictorial information that will be scanned is transmitted to high in the clouds image
Discriminance analysis system;
Step 4:High in the clouds image recognition analysis system according at the user obtain several kaffir lily samples pictures, through artificial intelligence
Can image identification system pick out the flowers for kaffir lily, and information identification in stem, leaf, flower samples pictures goes out the sample
Whether this kaffir lily suffers from the species and degree of pest and disease damage and ill insect pest;
Step 5:The big data analysis system in high in the clouds combines the positional information and current temporal information of the user, excavates this
The landform of user position, landforms, climatic information, and combine the species of the sample plant that high in the clouds image identification system is provided
With ill insect pest information, the maintenance of the science under automatic search and the kaffir lily planting location and growing state under similar environment
Method and pest management method;
Step 6:The science that the kaffir lily of the sample that high in the clouds big data analysis system obtains cloud computing should take is correct
Maintenance process is transferred to the smart mobile phone APP of the user, and mobile phone A PP is anti-by the screen and loudspeaker of smart mobile phone by final result
Feed the user;
Step 7:User takes corresponding maintenance measure according to the answer that APP applications are given to the kaffir lily, in certain day
After number, the result whether kaffir lily growing state is effectively improved is fed back to APP by user;
Step 8:APP sends to high in the clouds big data analysis system the feedback of user, and such as sample obtains effective Feedback,
Then by its typing large database concept, help is provided for the user for after;Such as the sample obtains negative feedback, then require user again
It is secondary that stem, leaf, the scanned picture data of flower of the kaffir lily are provided, and large database concept is labeled, repeat step step 4
To step 8, untill stopping feedback when the positive feedback or user that user is obtained in step 8 are in step 7.
Claims (3)
1. a kind of family based on big data and image recognition conserves the APP of kaffir lily, it is characterised in that comprise the following steps:
Step one:The smart mobile phone hardware that high-definition camera will be carried is carried and a kind of supported with the family of image recognition based on big data
The APP of kaffir lily is protected, by APP using being connected with image identification system with high in the clouds big data, smart mobile phone APP nodes is built, often
One APP node on behalf, one APP user;
Step 2:When User logs in APP is applied, APP automatically passes the APP application messages of user geographical position, traveling mode
It is sent to the big data analysis system in high in the clouds;
Step 3:User opens APP Built-in Images identification function, and scans the stem of kaffir lily respectively with smart mobile phone camera
Leaf site and flower position, APP sends prompt tone after scanning successfully, and the pictorial information that will be scanned is transmitted to high in the clouds image
Discriminance analysis system;
Step 4:High in the clouds image recognition analysis system according at the user obtain several kaffir lily samples pictures, through artificial intelligence
Can image identification system pick out the flowers for kaffir lily, and information identification in stem, leaf, flower samples pictures goes out the sample
Whether this kaffir lily suffers from the species and degree of pest and disease damage and ill insect pest;
Step 5:The big data analysis system in high in the clouds combines the positional information and current temporal information of the user, excavates this
The landform of user position, landforms, climatic information, and combine the species of the sample plant that high in the clouds image identification system is provided
With ill insect pest information, the maintenance of the science under automatic search and the kaffir lily planting location and growing state under similar environment
Method and pest management method;
Step 6:The science that the kaffir lily of the sample that high in the clouds big data analysis system obtains cloud computing should take is correct
Maintenance process is transferred to the smart mobile phone APP of the user, and mobile phone A PP is anti-by the screen and loudspeaker of smart mobile phone by final result
Feed the user;
Step 7:User takes corresponding maintenance measure according to the answer that APP applications are given to the kaffir lily, in certain day
After number, the result whether kaffir lily growing state is effectively improved is fed back to APP by user;
Step 8:APP sends to high in the clouds big data analysis system the feedback of user, and such as sample obtains effective Feedback,
Then by its typing large database concept, help is provided for the user for after;Such as the sample obtains negative feedback, then require user again
It is secondary that stem, leaf, the scanned picture data of flower of the kaffir lily are provided, and large database concept is labeled, repeat step step 4
To step 8, untill stopping feedback when the positive feedback or user that user is obtained in step 8 are in step 7.
2. a kind of family based on big data and image recognition according to claim 1 conserves the APP of kaffir lily, its feature
It is:APP using by the stem of the same kaffir lily of the same place of the positional information of user and scanning input place plant, leaf,
The pictorial information of three key positions is spent to be transferred to cloud server, the image identification system of cloud server is by database
Mass data is compared with the sample data information, draws the entitled kaffir lily of the plant and its disease and insect information;The big number in high in the clouds
According to analysis system by the kaffir lily with same pest and disease damage in the category information combining position information of the sample and large database concept
Treating method combine plantation area the characteristics of, after comparing, draw the optimal maintenance solution party of the sample kaffir lily
Case, and the program is transferred to user mobile phone.
3. a kind of family based on big data and image recognition according to claim 1 conserves the APP of kaffir lily, its feature
It is:APP is given the user after sample kaffir lily most preferably conserves solution, is possessed after user launches embodiment to kaffir lily
Feedback function, and feedback by information and check and correction, contribute to high in the clouds large data center database it is abundant with update, make
The self-teaching function of possessing machine while analyze data, allow cloud computing result with increasing for user's sample size
It is more accurate.
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CN201710147910.6A CN106899683A (en) | 2017-03-14 | 2017-03-14 | A kind of family based on big data and image recognition conserves the APP of kaffir lily |
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116503391A (en) * | 2023-06-26 | 2023-07-28 | 中南大学 | Tunnel face rock mass joint crack identification method and identification device |
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US20130136312A1 (en) * | 2011-11-24 | 2013-05-30 | Shih-Mu TSENG | Method and system for recognizing plant diseases and recording medium |
CN104318108A (en) * | 2014-10-28 | 2015-01-28 | 刘芳 | Plant cultivation method and device |
CN105787446A (en) * | 2016-02-24 | 2016-07-20 | 上海劲牛信息技术有限公司 | Smart agricultural insect disease remote automatic diagnosis system |
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2017
- 2017-03-14 CN CN201710147910.6A patent/CN106899683A/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130136312A1 (en) * | 2011-11-24 | 2013-05-30 | Shih-Mu TSENG | Method and system for recognizing plant diseases and recording medium |
CN104318108A (en) * | 2014-10-28 | 2015-01-28 | 刘芳 | Plant cultivation method and device |
CN105787446A (en) * | 2016-02-24 | 2016-07-20 | 上海劲牛信息技术有限公司 | Smart agricultural insect disease remote automatic diagnosis system |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
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CN116503391A (en) * | 2023-06-26 | 2023-07-28 | 中南大学 | Tunnel face rock mass joint crack identification method and identification device |
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