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

Jordi Mateo*, Dídac Florensa, Adela Pagès-Bernaus, Lluís M. Plà-Aragonès, Francesc Solsona, Anders R. Kristensen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

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.

Original languageEnglish
Title of host publicationIoT-based Intelligent Modelling for Environmental and Ecological Engineering : IoT Next Generation EcoAgro Systems
Number of pages24
PublisherSpringer
Publication date2021
Pages233-256
ISBN (Print)978-3-030-71171-9
ISBN (Electronic)978-3-030-71172-6
DOIs
Publication statusPublished - 2021
SeriesLecture Notes on Data Engineering and Communications Technologies
Volume67
ISSN2367-4512

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© 2021, Springer Nature Switzerland AG.

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