TY - GEN
T1 - Representation of Plant Structure using XML and Its Application to Cultivation Management
AU - Saito, Saki
AU - Yuyama, Kanami
AU - Ishii, Masahisa
AU - Huang, Victor
AU - Nishi, Hiroaki
N1 - Funding Information:
This work was supported by JST CREST Grant Number JPMJCR19K1, MEXT/JSPS KAKENHI Grant (B) Number JP20H02301, and the commissioned research by National Institute of Information and Communications Technology (NICT, Grant Number 22004), JAPAN.
Funding Information:
ACKNOWLEDGMENT This work was supported by JST CREST Grant Number JPMJCR19K1, MEXT/JSPS KAKENHI Grant (B) Number JP20H02301, and the commissioned research by National Institute of Information and Communications Technology (NICT, Grant Number 22004), JAPAN.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - The agricultural population in Japan is aging and shrinking. Therefore, it is necessary to improve the efficiency of farm work. Additionally, it takes many years to learn the skills required for farming, which discourages many young people from joining the field. As a countermeasure to this problem, smart agriculture technology is gaining increasing attention. Smart agriculture is an approach to increasing the quantity and quality of crops by leveraging advanced technologies. In smart agriculture, a large amount of data are collected from various sensors and internet of things devices. As the use of information and communication technology in agriculture spreads, the demand for data sharing between different agricultural systems increases accordingly. However, electronic data exchange interfaces for agricultural data are not standardized. Therefore, in Japan, it has been recommended to unify data formats using extensible markup language (XML). In this study, we focused on data regarding crop growth states and developed a method for representing plant structure using XML. In the proposed method, branches and fruits are extracted from plant images and their connections are expressed using the hierarchical structure of XML. Compared to conventional management of crop growth states based on images, the proposed method significantly reduces data size. Furthermore, because XML elements can be easily searched and sorted using XPath and XQuery, the XML format makes data easy to utilize for many services. For example, by counting numbers of fruits, profits and work times can be predicted. Additionally, data regarding plant structure is useful for directing farmers or robots to harvest fruits. The proposed method contributes to improving productivity and helps inexperienced farmers.
AB - The agricultural population in Japan is aging and shrinking. Therefore, it is necessary to improve the efficiency of farm work. Additionally, it takes many years to learn the skills required for farming, which discourages many young people from joining the field. As a countermeasure to this problem, smart agriculture technology is gaining increasing attention. Smart agriculture is an approach to increasing the quantity and quality of crops by leveraging advanced technologies. In smart agriculture, a large amount of data are collected from various sensors and internet of things devices. As the use of information and communication technology in agriculture spreads, the demand for data sharing between different agricultural systems increases accordingly. However, electronic data exchange interfaces for agricultural data are not standardized. Therefore, in Japan, it has been recommended to unify data formats using extensible markup language (XML). In this study, we focused on data regarding crop growth states and developed a method for representing plant structure using XML. In the proposed method, branches and fruits are extracted from plant images and their connections are expressed using the hierarchical structure of XML. Compared to conventional management of crop growth states based on images, the proposed method significantly reduces data size. Furthermore, because XML elements can be easily searched and sorted using XPath and XQuery, the XML format makes data easy to utilize for many services. For example, by counting numbers of fruits, profits and work times can be predicted. Additionally, data regarding plant structure is useful for directing farmers or robots to harvest fruits. The proposed method contributes to improving productivity and helps inexperienced farmers.
KW - XML
KW - cultivation management
KW - image analysis
KW - plant structure representation
KW - smart agriculture
UR - http://www.scopus.com/inward/record.url?scp=85093365273&partnerID=8YFLogxK
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U2 - 10.1109/ETFA46521.2020.9212015
DO - 10.1109/ETFA46521.2020.9212015
M3 - Conference contribution
AN - SCOPUS:85093365273
T3 - IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
SP - 125
EP - 131
BT - Proceedings - 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020
Y2 - 8 September 2020 through 11 September 2020
ER -