Research on plant disease diagnosis technology based on OpenCV technology

Jinmeng Zhang; Renlong Zhang; Tao Hong; Michel Kadoch; Mohamed Cheriet; Xianzhi Lu; Kaijun Guo

doi:10.1109/BMSB49480.2020.9379921

Research on plant disease diagnosis technology based on OpenCV technology

Jinmeng Zhang
, Renlong Zhang
, Tao Hong
, Michel Kadoch
, Mohamed Cheriet
, Xianzhi Lu
, Kaijun Guo

School of Electronic and Information Engineering

Beijing University of Agriculture
Yunnan Innovation Institute·BUAA
École de technologie supérieure
Chongqing College of Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Plant diseases are one of the principal factors that affect the normal growth of plants throughout the growth process. In order to solve this problem that affects the healthy growth of plants, it is proposed to use effective methods to diagnose and treat plant diseases to ensure the normal growth of plants. Many existing diagnostic technologies have certain defects, and in order to effectively solve the shortcomings of this type of plant disease diagnosis technology, a new information method of plant disease and insect disease and disease diagnosis based on the Internet of Things sensor network technology and OpenCV technology is proposed. Through accurate detection of plant growth status and intelligent processing of plant disease images, more accurate diagnosis results are obtained. This method can effectively improve work efficiency and achieve full utilization of resources.

Original language	English
Title of host publication	15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020
Publisher	IEEE Computer Society
ISBN (Electronic)	9781728157849
DOIs	https://doi.org/10.1109/BMSB49480.2020.9379921
State	Published - 27 Oct 2020
Event	15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020 - Paris, France Duration: 27 Oct 2020 → 29 Oct 2020

Publication series

Name	IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB
Volume	2020-October
ISSN (Print)	2155-5044
ISSN (Electronic)	2155-5052

Conference

Conference	15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020
Country/Territory	France
City	Paris
Period	27/10/20 → 29/10/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Internet of Things
OpenCV
Plant Disease
Unmanned Aerial VehicleSmart Farm

Access to Document

10.1109/BMSB49480.2020.9379921

Cite this

Zhang, J., Zhang, R., Hong, T., Kadoch, M., Cheriet, M., Lu, X., & Guo, K. (2020). Research on plant disease diagnosis technology based on OpenCV technology. In 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020 Article 9379921 (IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB; Vol. 2020-October). IEEE Computer Society. https://doi.org/10.1109/BMSB49480.2020.9379921

@inproceedings{ad97853a0235474eaf1182efe4ea4bc9,

title = "Research on plant disease diagnosis technology based on OpenCV technology",

abstract = "Plant diseases are one of the principal factors that affect the normal growth of plants throughout the growth process. In order to solve this problem that affects the healthy growth of plants, it is proposed to use effective methods to diagnose and treat plant diseases to ensure the normal growth of plants. Many existing diagnostic technologies have certain defects, and in order to effectively solve the shortcomings of this type of plant disease diagnosis technology, a new information method of plant disease and insect disease and disease diagnosis based on the Internet of Things sensor network technology and OpenCV technology is proposed. Through accurate detection of plant growth status and intelligent processing of plant disease images, more accurate diagnosis results are obtained. This method can effectively improve work efficiency and achieve full utilization of resources.",

keywords = "Internet of Things, OpenCV, Plant Disease, Unmanned Aerial VehicleSmart Farm",

author = "Jinmeng Zhang and Renlong Zhang and Tao Hong and Michel Kadoch and Mohamed Cheriet and Xianzhi Lu and Kaijun Guo",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020 ; Conference date: 27-10-2020 Through 29-10-2020",

year = "2020",

month = oct,

day = "27",

doi = "10.1109/BMSB49480.2020.9379921",

language = "英语",

series = "IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB",

publisher = "IEEE Computer Society",

booktitle = "15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020",

address = "美国",

}

Zhang, J, Zhang, R, Hong, T, Kadoch, M, Cheriet, M, Lu, X & Guo, K 2020, Research on plant disease diagnosis technology based on OpenCV technology. in 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020., 9379921, IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB, vol. 2020-October, IEEE Computer Society, 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020, Paris, France, 27/10/20. https://doi.org/10.1109/BMSB49480.2020.9379921

Research on plant disease diagnosis technology based on OpenCV technology. / Zhang, Jinmeng; Zhang, Renlong; Hong, Tao et al.
15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020. IEEE Computer Society, 2020. 9379921 (IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB; Vol. 2020-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Research on plant disease diagnosis technology based on OpenCV technology

AU - Zhang, Jinmeng

AU - Zhang, Renlong

AU - Hong, Tao

AU - Kadoch, Michel

AU - Cheriet, Mohamed

AU - Lu, Xianzhi

AU - Guo, Kaijun

PY - 2020/10/27

Y1 - 2020/10/27

N2 - Plant diseases are one of the principal factors that affect the normal growth of plants throughout the growth process. In order to solve this problem that affects the healthy growth of plants, it is proposed to use effective methods to diagnose and treat plant diseases to ensure the normal growth of plants. Many existing diagnostic technologies have certain defects, and in order to effectively solve the shortcomings of this type of plant disease diagnosis technology, a new information method of plant disease and insect disease and disease diagnosis based on the Internet of Things sensor network technology and OpenCV technology is proposed. Through accurate detection of plant growth status and intelligent processing of plant disease images, more accurate diagnosis results are obtained. This method can effectively improve work efficiency and achieve full utilization of resources.

AB - Plant diseases are one of the principal factors that affect the normal growth of plants throughout the growth process. In order to solve this problem that affects the healthy growth of plants, it is proposed to use effective methods to diagnose and treat plant diseases to ensure the normal growth of plants. Many existing diagnostic technologies have certain defects, and in order to effectively solve the shortcomings of this type of plant disease diagnosis technology, a new information method of plant disease and insect disease and disease diagnosis based on the Internet of Things sensor network technology and OpenCV technology is proposed. Through accurate detection of plant growth status and intelligent processing of plant disease images, more accurate diagnosis results are obtained. This method can effectively improve work efficiency and achieve full utilization of resources.

KW - Internet of Things

KW - OpenCV

KW - Plant Disease

KW - Unmanned Aerial VehicleSmart Farm

UR - https://www.scopus.com/pages/publications/85103451574

U2 - 10.1109/BMSB49480.2020.9379921

DO - 10.1109/BMSB49480.2020.9379921

M3 - 会议稿件

AN - SCOPUS:85103451574

T3 - IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB

BT - 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020

PB - IEEE Computer Society

T2 - 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020

Y2 - 27 October 2020 through 29 October 2020

ER -

Zhang J, Zhang R, Hong T, Kadoch M, Cheriet M, Lu X et al. Research on plant disease diagnosis technology based on OpenCV technology. In 15th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2020. IEEE Computer Society. 2020. 9379921. (IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB). doi: 10.1109/BMSB49480.2020.9379921

Research on plant disease diagnosis technology based on OpenCV technology

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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