Summary of Potential and Exploitation of Big Data and AI in Bioeconomy

Caj Södergård

Research output: Chapter in Book/Report/Conference proceedingChapter or book articleScientificpeer-review

Abstract

In this final chapter, we summarize the DataBio learnings about how to exploit big data and AI in bioeconomy. The development platform for the software used in the 27 pilots was a central tool. The Enterprise Architecture model Archimate laid a solid basis for the complex software in the pilots. Handling data from sensors and earth observation were shown in numerous pilots. Genomic data from crop species allows us to significantly speed up plant breeding by predicting plant properties in-silico. Data integration is crucial and we show how linked data enables searches over multiple datasets. Real-time processing of events provides insights for fast decision-making, for example about ship engine conditions. We show how sensitive bioeconomy data can be analysed in a privacy-preserving way. The agriculture pilots show with clear numbers the impact of big data and AI on precision agriculture, insurance and subsidies control. In forestry, DataBio developed several big data tools for forest monitoring. In fishery, we demonstrate how to reduce maintenance cost and time as well as fuel consumption in the operation of fishing vessels as well as how to accurately predict fish catches. The chapter ends with perspectives on earth observation, machine learning, data sharing and crowdsourcing.
Original languageEnglish
Title of host publicationBig Data in Bioeconomy
Subtitle of host publicationResults from the European DataBio Project
EditorsCaj Södergård, Tomas Mildorf, Ephrem Habyarimana, Arne J. Berre, Jose A. Fernandes, Christian Zinke-Wehlmann
PublisherSpringer
Chapter32
Pages417-423
ISBN (Electronic)978-3-030-71069-9
ISBN (Print)978-3-030-71068-2
DOIs
Publication statusPublished - 14 Aug 2021
MoE publication typeA3 Part of a book or another research book

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