Household Chimonanthus praecox maintenance APP based on big data and image recognition

Abstract

The invention discloses a household Chimonanthus praecox maintenance APP based on big data and image recognition. The APP is characterized in that after a user logs in the APP, stem, leaf and flower parts of Chimonanthus praecox are scanned through a camera; the APP automatically sends image data and geographical location data of a Cymbidium goeringii sample to a cloud server; the cloud server judges that the sample is the Chimonanthus praecox and judges the growth condition and the disease and pest condition of the Chimonanthus praecox through adoption of an image recognition technology; data of the Chimonanthus praecox of which geographical location is near to that of the sample and growth condition is similar to that of the sample is called from a Chimonanthus praecox big database for comparison, a maintenance method for the sample Chimonanthus praecox is obtained and the method is pushed to the APP. Through application of the mode, according to the APP, a user without any Chimonanthus praecox maintenance knowledge is enabled to analyze the growth condition of the planted Chimonanthus praecox rapidly and precisely through simple scan operation with the help of the APP, and the user is instructed to take scientific and reasonable disease and pest control 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 home maintenance of wintersweet 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 wintersweet at home. However, most of the people who grow flowers at home lack professional knowledge, and the main purpose is to enjoy the fun of life brought by wintersweet, rather than to study those who are interested in wintersweet. Agricultural knowledge is not very familiar to urban residents, and urban people live in a fast pace, so they have less time and energy to learn agricultural knowledge that they are not interested in. Injury, when the wintersweet planted by oneself suffers from diseases and insect pests, it is often difficult to distinguish the type of diseases and insect pests with the naked eye and rely on one's own experience, so i...

AI Technical Summary

Problems solved by technology

[0002] With the improvement of urban residents' requirements for the home environment, more and more users plant wintersweet at home. However, most of the people who grow flowers at home lack professional knowledge, and the main purpose is to enjoy the fun of life brought by wintersweet, rather than to study those who are interested in wintersweet. Agricultural knowledge is not very familiar to urban residents, and urban people live in a fast pace, so they have less time and energy to learn agricultural knowledge that they are not interested in. Injury, when the wintersweet planted by oneself suffers from diseases and insect pests, it is often difficult to distinguish the type of diseases and insect pests with the naked eye and rely 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 kind of The method is slow to take effect, and when netizens disagree, it is difficult for users to distinguish and take correct measures, resulting in delayed treatment of diseases and insect pests suffered by wintersweet, resulting in poor growth and even death. However, a method based on big data and image recognition The APP of family maintenance of wintersweet adopts big data and image recognition technology to provide users with the help of cloud computing, so that users who have no knowledge of wintersweet maintenance can implement scientific maintenance measures on samples of wintersweet in the most timely manner

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