Big data and image recognition-based APP (application) for domestic cultivation of Rosa banksiae

Abstract

The invention discloses a big data and image recognition-based APP (application) for domestic cultivation of Rosa banksiae. The application is characterized in that: after logging in the APP, a user scans stem, leaf and flower portions of Rosa banksiae through using a camera, the APP automatically sends the picture data of a Rosa banksiae sample and the geographical location data of a geographical location where the Rosa banksiae is cultivated to a cloud server, the cloud server judges that the sample is Rosa banksiae and the growth, pest and disease situations of the Rosa banksiae through using image recognition technologies; and data about Rosa banksiae which is closed to the geographical location and has similar growth conditions with the Rosa banksiae sample are called from a Rosa banksiae database, so that a cultivation method for the Rosa banksiae sample can be obtained and is pushed to the APP. With the APP which is realized through the above manners adopted, a user with no Rosa banksiae cultivation knowledge can perform the simple operation of the scanning function of the APP, so that the APP can analyze the growth situation of the cultivated Rosa banksiae rapidly and accurately, and therefore, the user can be guided to take scientific and reasonable pest and disease control and prevention measures and daily maintenance measures.

Description

technical field [0001] The invention relates to the field of big data and image recognition, in particular to an APP for family maintenance of woody flowers based on big data and image recognition. Background technique [0002] With the improvement of urban residents' requirements for the home environment, more and more users plant woody flowers at home. However, most of the people who grow flowers at home lack professional knowledge, and the main purpose is to enjoy the fun brought by woody flowers, not research. The agricultural knowledge that is unfamiliar to urban residents, and the urban population has a fast pace of life, so they have little time and energy to learn agricultural knowledge that they are not interested in. In case of damage from diseases and insect pests, when the woody flowers planted by oneself suffer from diseases and insect pests, it is often difficult to distinguish the type of diseases and insect pests with the naked eye and based on one's own expe...

AI Technical Summary

Problems solved by technology

[0002] With the improvement of urban residents' requirements for the home environment, more and more users plant woody flowers at home. However, most of the people who grow flowers at home lack professional knowledge, and the main purpose is to enjoy the fun brought by woody flowers, not research. The agricultural knowledge that is unfamiliar to urban residents, and the urban population has a fast pace of life, so they have little time and energy to learn agricultural knowledge that they are not interested in. In case of damage from diseases and insect pests, when the woody flowers planted by oneself suffer from diseases and insect pests, it is often difficult to distinguish the type of diseases and insect pests with the naked eye and based on one's own experience, so it is difficult to find the correct method to prescribe the right medicine. The traditional method is to take pictures and upload them to Internet forums, asking others for help , but this method is slow to take effect, and it is difficult for users to distinguish and take correct measures when encountering netizens holding their own opinions, resulting in delayed treatment of diseases and insect pests suffered by Muxianghua, resulting in poor growth or even death. Big data and image recognition APP for family maintenance of woody flowers adopts big data and image recognition technology to provide users with cloud computing help, so that users who do not understand the maintenance knowledge of woody flowers can also carry out the most timely implementation of sample woody flowers Scientific Conservation Measures

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