Representation of Plant Structure using XML and Its Application to Cultivation Management

Saki Saito, Kanami Yuyama, Masahisa Ishii, Victor Huang, Hiroaki Nishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages125-131
Number of pages7
ISBN (Electronic)9781728189567
DOIs
Publication statusPublished - 2020 Sep
Event25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020 - Vienna, Austria
Duration: 2020 Sep 82020 Sep 11

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume2020-September
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Conference

Conference25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020
CountryAustria
CityVienna
Period20/9/820/9/11

Keywords

  • cultivation management
  • image analysis
  • plant structure representation
  • smart agriculture
  • XML

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Computer Science Applications

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