A Cloud-Based Decision Support System to Support Decisions in Sow Farms

Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt

Standard

A Cloud-Based Decision Support System to Support Decisions in Sow Farms. / Mateo, Jordi; Florensa, Dídac; Pagès-Bernaus, Adela; Plà-Aragonès, Lluís M.; Solsona, Francesc; Kristensen, Anders R.

IoT-based Intelligent Modelling for Environmental and Ecological Engineering: IoT Next Generation EcoAgro Systems. Springer, 2021. s. 233-256 (Lecture Notes on Data Engineering and Communications Technologies, Bind 67).

Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt

Harvard

Mateo, J, Florensa, D, Pagès-Bernaus, A, Plà-Aragonès, LM, Solsona, F & Kristensen, AR 2021, A Cloud-Based Decision Support System to Support Decisions in Sow Farms. i IoT-based Intelligent Modelling for Environmental and Ecological Engineering: IoT Next Generation EcoAgro Systems. Springer, Lecture Notes on Data Engineering and Communications Technologies, bind 67, s. 233-256. https://doi.org/10.1007/978-3-030-71172-6_10

APA

Mateo, J., Florensa, D., Pagès-Bernaus, A., Plà-Aragonès, L. M., Solsona, F., & Kristensen, A. R. (2021). A Cloud-Based Decision Support System to Support Decisions in Sow Farms. I IoT-based Intelligent Modelling for Environmental and Ecological Engineering: IoT Next Generation EcoAgro Systems (s. 233-256). Springer. Lecture Notes on Data Engineering and Communications Technologies Bind 67 https://doi.org/10.1007/978-3-030-71172-6_10

Vancouver

Mateo J, Florensa D, Pagès-Bernaus A, Plà-Aragonès LM, Solsona F, Kristensen AR. A Cloud-Based Decision Support System to Support Decisions in Sow Farms. I IoT-based Intelligent Modelling for Environmental and Ecological Engineering: IoT Next Generation EcoAgro Systems. Springer. 2021. s. 233-256. (Lecture Notes on Data Engineering and Communications Technologies, Bind 67). https://doi.org/10.1007/978-3-030-71172-6_10

Author

Mateo, Jordi ; Florensa, Dídac ; Pagès-Bernaus, Adela ; Plà-Aragonès, Lluís M. ; Solsona, Francesc ; Kristensen, Anders R. / A Cloud-Based Decision Support System to Support Decisions in Sow Farms. IoT-based Intelligent Modelling for Environmental and Ecological Engineering: IoT Next Generation EcoAgro Systems. Springer, 2021. s. 233-256 (Lecture Notes on Data Engineering and Communications Technologies, Bind 67).

Bibtex

@inbook{b9758e9f6d394e4eb5d2a51db7eda63d,
title = "A Cloud-Based Decision Support System to Support Decisions in Sow Farms",
abstract = "In the pig farming industrial sector, innovation is a crucial factor in maintaining competitiveness. On the research side, there exists a large body of models and decision analysis tools that too often do not reach the end-user. In this chapter, we propose a software-as-a-service based on a cloud-based Decision Support System architecture that should overcome the main adoption barriers spotted in the literature. The service proposed takes advantage of existing herd management models feed with historical farm data and economic parameters recorded by the most popular farm management software used by pig companies. The approach includes a sow farm model and offers a set of analytic tools to help farmers in making better strategic, tactical and operational decisions based on their own data. This chapter highlights the advantages of optimization and simulation models hosted in a cloud computing platform to deliver a service of knowledge discovering and data analytics to sow farms. The success in adoption depends on the added value and usability through software integration with current management tools used by pig producers. Preliminary results show that the proposed service helps pig managers to make better supervision of sows and to obtain the competitive advantages of using complex mathematical models in a practical, flexible and transparent way.",
author = "Jordi Mateo and D{\'i}dac Florensa and Adela Pag{\`e}s-Bernaus and Pl{\`a}-Aragon{\`e}s, {Llu{\'i}s M.} and Francesc Solsona and Kristensen, {Anders R.}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.",
year = "2021",
doi = "10.1007/978-3-030-71172-6_10",
language = "English",
isbn = "978-3-030-71171-9",
series = "Lecture Notes on Data Engineering and Communications Technologies",
publisher = "Springer",
pages = "233--256",
booktitle = "IoT-based Intelligent Modelling for Environmental and Ecological Engineering",
address = "Switzerland",

}

RIS

TY - CHAP

T1 - A Cloud-Based Decision Support System to Support Decisions in Sow Farms

AU - Mateo, Jordi

AU - Florensa, Dídac

AU - Pagès-Bernaus, Adela

AU - Plà-Aragonès, Lluís M.

AU - Solsona, Francesc

AU - Kristensen, Anders R.

N1 - Publisher Copyright: © 2021, Springer Nature Switzerland AG.

PY - 2021

Y1 - 2021

N2 - In the pig farming industrial sector, innovation is a crucial factor in maintaining competitiveness. On the research side, there exists a large body of models and decision analysis tools that too often do not reach the end-user. In this chapter, we propose a software-as-a-service based on a cloud-based Decision Support System architecture that should overcome the main adoption barriers spotted in the literature. The service proposed takes advantage of existing herd management models feed with historical farm data and economic parameters recorded by the most popular farm management software used by pig companies. The approach includes a sow farm model and offers a set of analytic tools to help farmers in making better strategic, tactical and operational decisions based on their own data. This chapter highlights the advantages of optimization and simulation models hosted in a cloud computing platform to deliver a service of knowledge discovering and data analytics to sow farms. The success in adoption depends on the added value and usability through software integration with current management tools used by pig producers. Preliminary results show that the proposed service helps pig managers to make better supervision of sows and to obtain the competitive advantages of using complex mathematical models in a practical, flexible and transparent way.

AB - In the pig farming industrial sector, innovation is a crucial factor in maintaining competitiveness. On the research side, there exists a large body of models and decision analysis tools that too often do not reach the end-user. In this chapter, we propose a software-as-a-service based on a cloud-based Decision Support System architecture that should overcome the main adoption barriers spotted in the literature. The service proposed takes advantage of existing herd management models feed with historical farm data and economic parameters recorded by the most popular farm management software used by pig companies. The approach includes a sow farm model and offers a set of analytic tools to help farmers in making better strategic, tactical and operational decisions based on their own data. This chapter highlights the advantages of optimization and simulation models hosted in a cloud computing platform to deliver a service of knowledge discovering and data analytics to sow farms. The success in adoption depends on the added value and usability through software integration with current management tools used by pig producers. Preliminary results show that the proposed service helps pig managers to make better supervision of sows and to obtain the competitive advantages of using complex mathematical models in a practical, flexible and transparent way.

U2 - 10.1007/978-3-030-71172-6_10

DO - 10.1007/978-3-030-71172-6_10

M3 - Book chapter

AN - SCOPUS:85107390167

SN - 978-3-030-71171-9

T3 - Lecture Notes on Data Engineering and Communications Technologies

SP - 233

EP - 256

BT - IoT-based Intelligent Modelling for Environmental and Ecological Engineering

PB - Springer

ER -

ID: 272125033