Pattern Mining and Classification Techniques for Agriculture and Crop Simulation

Javier Rozas-Acurio; Sergio Zavaleta-Salazar; Willy Ugarte

doi:10.1007/978-3-031-20319-0_33

Pattern Mining and Classification Techniques for Agriculture and Crop Simulation

Javier Rozas-Acurio
, Sergio Zavaleta-Salazar
, Willy Ugarte

Faculty of Engineering

Universidad Peruana de Ciencias Aplicadas

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

Abstract

Research shows that data analysis and artificial intelligence applied to agriculture in Peru can help manage crop production and mitigate monetary losses. This work presents SmartAgro, a system based on pattern mining and classification techniques that takes information from multiple sources related to the agricultural process to extract knowledge and produce recommendations about the crop growth process. The problem we seek to mitigate with our system is the economic losses generated in Peruvian agriculture caused by poor crop planning. Our results show a high accuracy in regards to type of crop recommendation, and a knowledge base useful for agricultural planning.

Original language	English
Title of host publication	Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers
Editors	Teresa Guarda, Filipe Portela, Maria Fernanda Augusto
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	444-458
Number of pages	15
ISBN (Print)	9783031203183
DOIs	https://doi.org/10.1007/978-3-031-20319-0_33
State	Published - 2022
Event	2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022 - Santiago de Compostela, Spain Duration: 12 Sep 2022 → 15 Sep 2022

Publication series

Name	Communications in Computer and Information Science
Volume	1675 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022
Country/Territory	Spain
City	Santiago de Compostela
Period	12/09/22 → 15/09/22

Keywords

Agriculture
Classification
Crop simulation
Pattern mining

Access to Document

10.1007/978-3-031-20319-0_33

Cite this

Rozas-Acurio, J., Zavaleta-Salazar, S., & Ugarte, W. (2022). Pattern Mining and Classification Techniques for Agriculture and Crop Simulation. In T. Guarda, F. Portela, & M. F. Augusto (Eds.), Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers (pp. 444-458). (Communications in Computer and Information Science; Vol. 1675 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-20319-0_33

Rozas-Acurio, Javier ; Zavaleta-Salazar, Sergio ; Ugarte, Willy. / Pattern Mining and Classification Techniques for Agriculture and Crop Simulation. Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers. editor / Teresa Guarda ; Filipe Portela ; Maria Fernanda Augusto. Springer Science and Business Media Deutschland GmbH, 2022. pp. 444-458 (Communications in Computer and Information Science).

@inproceedings{f8ce0ede05344780bf880b0415a4c412,

title = "Pattern Mining and Classification Techniques for Agriculture and Crop Simulation",

abstract = "Research shows that data analysis and artificial intelligence applied to agriculture in Peru can help manage crop production and mitigate monetary losses. This work presents SmartAgro, a system based on pattern mining and classification techniques that takes information from multiple sources related to the agricultural process to extract knowledge and produce recommendations about the crop growth process. The problem we seek to mitigate with our system is the economic losses generated in Peruvian agriculture caused by poor crop planning. Our results show a high accuracy in regards to type of crop recommendation, and a knowledge base useful for agricultural planning.",

keywords = "Agriculture, Classification, Crop simulation, Pattern mining",

author = "Javier Rozas-Acurio and Sergio Zavaleta-Salazar and Willy Ugarte",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022 ; Conference date: 12-09-2022 Through 15-09-2022",

year = "2022",

doi = "10.1007/978-3-031-20319-0\_33",

language = "Ingl{\'e}s",

isbn = "9783031203183",

series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "444--458",

editor = "Teresa Guarda and Filipe Portela and Augusto, \{Maria Fernanda\}",

booktitle = "Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers",

}

Rozas-Acurio, J, Zavaleta-Salazar, S & Ugarte, W 2022, Pattern Mining and Classification Techniques for Agriculture and Crop Simulation. in T Guarda, F Portela & MF Augusto (eds), Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers. Communications in Computer and Information Science, vol. 1675 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 444-458, 2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022, Santiago de Compostela, Spain, 12/09/22. https://doi.org/10.1007/978-3-031-20319-0_33

Pattern Mining and Classification Techniques for Agriculture and Crop Simulation. / Rozas-Acurio, Javier; Zavaleta-Salazar, Sergio; Ugarte, Willy.
Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers. ed. / Teresa Guarda; Filipe Portela; Maria Fernanda Augusto. Springer Science and Business Media Deutschland GmbH, 2022. p. 444-458 (Communications in Computer and Information Science; Vol. 1675 CCIS).

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

TY - GEN

T1 - Pattern Mining and Classification Techniques for Agriculture and Crop Simulation

AU - Rozas-Acurio, Javier

AU - Zavaleta-Salazar, Sergio

AU - Ugarte, Willy

PY - 2022

Y1 - 2022

N2 - Research shows that data analysis and artificial intelligence applied to agriculture in Peru can help manage crop production and mitigate monetary losses. This work presents SmartAgro, a system based on pattern mining and classification techniques that takes information from multiple sources related to the agricultural process to extract knowledge and produce recommendations about the crop growth process. The problem we seek to mitigate with our system is the economic losses generated in Peruvian agriculture caused by poor crop planning. Our results show a high accuracy in regards to type of crop recommendation, and a knowledge base useful for agricultural planning.

AB - Research shows that data analysis and artificial intelligence applied to agriculture in Peru can help manage crop production and mitigate monetary losses. This work presents SmartAgro, a system based on pattern mining and classification techniques that takes information from multiple sources related to the agricultural process to extract knowledge and produce recommendations about the crop growth process. The problem we seek to mitigate with our system is the economic losses generated in Peruvian agriculture caused by poor crop planning. Our results show a high accuracy in regards to type of crop recommendation, and a knowledge base useful for agricultural planning.

KW - Agriculture

KW - Classification

KW - Crop simulation

KW - Pattern mining

UR - https://www.scopus.com/pages/publications/85144203108

U2 - 10.1007/978-3-031-20319-0_33

DO - 10.1007/978-3-031-20319-0_33

M3 - Contribución a la conferencia

AN - SCOPUS:85144203108

SN - 9783031203183

T3 - Communications in Computer and Information Science

SP - 444

EP - 458

BT - Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers

A2 - Guarda, Teresa

A2 - Portela, Filipe

A2 - Augusto, Maria Fernanda

PB - Springer Science and Business Media Deutschland GmbH

T2 - 2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022

Y2 - 12 September 2022 through 15 September 2022

ER -

Rozas-Acurio J, Zavaleta-Salazar S, Ugarte W. Pattern Mining and Classification Techniques for Agriculture and Crop Simulation. In Guarda T, Portela F, Augusto MF, editors, Advanced Research in Technologies, Information, Innovation and Sustainability - Second International Conference, ARTIIS 2022, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2022. p. 444-458. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-20319-0_33