Feasibility study of plant health monitoring

Davit Hovhannisyan; Kareem Khalifeh; Peng Fei; Ahmed Eltawil; Fadi Kurdahi

doi:10.1109/ISCAS.2019.8702569

Feasibility study of plant health monitoring

Davit Hovhannisyan, Kareem Khalifeh, Peng Fei, Ahmed Eltawil, Fadi Kurdahi

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

1 Scopus citations

Abstract

Continuous monitoring of crop is an essential task of agricultural practices for detection of diseases or pests, precision irrigation and fertilization. The state of the art monitoring and imaging systems use aerial imaging to obtain visual feedback and multi-spectral imagery to determine crop growth factors. The main idea is that the features can be automatically calculated and assessed after pre-processing the images. After pre-processing, then the parameters can be computed using image processing techniques. For example, key leaf function traits leaf life span, leaf mass per area can be calculated. Our findings indicate that plant health assessment could be moved from lab and expensive monitoring tools to ubiquitous silicon technology based cost effect solutions without much loss of accuracy.

Original language	English (US)
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781728103976
DOIs	https://doi.org/10.1109/ISCAS.2019.8702569
State	Published - Jan 1 2019
Externally published	Yes

UN SDGs

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

Access to Document

10.1109/ISCAS.2019.8702569

Cite this

@inproceedings{1a80a17eb1f14393a1a2847f39ae15e3,

title = "Feasibility study of plant health monitoring",

abstract = "Continuous monitoring of crop is an essential task of agricultural practices for detection of diseases or pests, precision irrigation and fertilization. The state of the art monitoring and imaging systems use aerial imaging to obtain visual feedback and multi-spectral imagery to determine crop growth factors. The main idea is that the features can be automatically calculated and assessed after pre-processing the images. After pre-processing, then the parameters can be computed using image processing techniques. For example, key leaf function traits leaf life span, leaf mass per area can be calculated. Our findings indicate that plant health assessment could be moved from lab and expensive monitoring tools to ubiquitous silicon technology based cost effect solutions without much loss of accuracy.",

author = "Davit Hovhannisyan and Kareem Khalifeh and Peng Fei and Ahmed Eltawil and Fadi Kurdahi",

note = "Generated from Scopus record by KAUST IRTS on 2019-11-20",

year = "2019",

month = jan,

day = "1",

doi = "10.1109/ISCAS.2019.8702569",

language = "English (US)",

isbn = "9781728103976",

booktitle = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

TY - GEN

T1 - Feasibility study of plant health monitoring

AU - Hovhannisyan, Davit

AU - Khalifeh, Kareem

AU - Fei, Peng

AU - Eltawil, Ahmed

AU - Kurdahi, Fadi

N1 - Generated from Scopus record by KAUST IRTS on 2019-11-20

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Continuous monitoring of crop is an essential task of agricultural practices for detection of diseases or pests, precision irrigation and fertilization. The state of the art monitoring and imaging systems use aerial imaging to obtain visual feedback and multi-spectral imagery to determine crop growth factors. The main idea is that the features can be automatically calculated and assessed after pre-processing the images. After pre-processing, then the parameters can be computed using image processing techniques. For example, key leaf function traits leaf life span, leaf mass per area can be calculated. Our findings indicate that plant health assessment could be moved from lab and expensive monitoring tools to ubiquitous silicon technology based cost effect solutions without much loss of accuracy.

AB - Continuous monitoring of crop is an essential task of agricultural practices for detection of diseases or pests, precision irrigation and fertilization. The state of the art monitoring and imaging systems use aerial imaging to obtain visual feedback and multi-spectral imagery to determine crop growth factors. The main idea is that the features can be automatically calculated and assessed after pre-processing the images. After pre-processing, then the parameters can be computed using image processing techniques. For example, key leaf function traits leaf life span, leaf mass per area can be calculated. Our findings indicate that plant health assessment could be moved from lab and expensive monitoring tools to ubiquitous silicon technology based cost effect solutions without much loss of accuracy.

UR - https://ieeexplore.ieee.org/document/8702569/

UR - http://www.scopus.com/inward/record.url?scp=85066785154&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2019.8702569

DO - 10.1109/ISCAS.2019.8702569

M3 - Conference contribution

SN - 9781728103976

BT - Proceedings - IEEE International Symposium on Circuits and Systems

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Feasibility study of plant health monitoring

Abstract

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this