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Enabling automated integration testing of smart farming applications via digital twin prototypes

Enabling automated integration testing of smart farming applications via digital twin prototypes
Enabling automated integration testing of smart farming applications via digital twin prototypes

Industry 4.0 represents a major technological shift that has the potential to transform the manufacturing industry, making it more efficient, productive, and sustainable. Smart farming is a concept that involves the use of advanced technologies to improve the efficiency and sustainability of agricultural practices. Industry 4.0 and smart farming are closely related, as many of the technologies used in smart farming are also used in Industry 4.0. Digital twins have the potential for cost-effective software development of such applications.With our Digital Twin Prototype approach, all sensor interfaces are integrated into the development process, and their inputs and outputs of the emulated hardware match those of the real hardware. The emulators respond to the same commands and return identically formatted data packages as their real counterparts, making the Digital Twin Prototype a valid source of a digital shadow, i.e. the Digital Twin Prototype is a prototype of the physical twin and can replace it for automated testing of the digital twin software. In this paper, we present a case study for employing our Digital Twin Prototype approach to automated testing of software for improving the making of silage with a smart farming application.Besides automated testing with continuous integration, we also discuss continuous deployment of modular Docker containers in this context.

Agricultural Machinery, Automated Testing, Continuous Integration, Digital Twin Prototypes, Smart Farming
IEEE
Barbie, Alexander
c567ce7d-cf04-472a-a203-00070f06f97e
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Hansen, Malte
24fe48bd-9286-4118-8eb8-b70aa34b041d
Barbie, Alexander
c567ce7d-cf04-472a-a203-00070f06f97e
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Hansen, Malte
24fe48bd-9286-4118-8eb8-b70aa34b041d

Barbie, Alexander, Hasselbring, Wilhelm and Hansen, Malte (2024) Enabling automated integration testing of smart farming applications via digital twin prototypes. In 2023 IEEE Smart World Congress (SWC). IEEE. 8 pp . (doi:10.1109/SWC57546.2023.10449240).

Record type: Conference or Workshop Item (Paper)

Abstract

Industry 4.0 represents a major technological shift that has the potential to transform the manufacturing industry, making it more efficient, productive, and sustainable. Smart farming is a concept that involves the use of advanced technologies to improve the efficiency and sustainability of agricultural practices. Industry 4.0 and smart farming are closely related, as many of the technologies used in smart farming are also used in Industry 4.0. Digital twins have the potential for cost-effective software development of such applications.With our Digital Twin Prototype approach, all sensor interfaces are integrated into the development process, and their inputs and outputs of the emulated hardware match those of the real hardware. The emulators respond to the same commands and return identically formatted data packages as their real counterparts, making the Digital Twin Prototype a valid source of a digital shadow, i.e. the Digital Twin Prototype is a prototype of the physical twin and can replace it for automated testing of the digital twin software. In this paper, we present a case study for employing our Digital Twin Prototype approach to automated testing of software for improving the making of silage with a smart farming application.Besides automated testing with continuous integration, we also discuss continuous deployment of modular Docker containers in this context.

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More information

e-pub ahead of print date: 1 March 2024
Venue - Dates: 9th IEEE Smart World Congress, SWC 2023, , Portsmouth, United Kingdom, 2023-08-28 - 2023-08-31
Keywords: Agricultural Machinery, Automated Testing, Continuous Integration, Digital Twin Prototypes, Smart Farming

Identifiers

Local EPrints ID: 488772
URI: http://eprints.soton.ac.uk/id/eprint/488772
PURE UUID: 24a84a6c-0786-4b01-89d3-aa31eaf645fd
ORCID for Wilhelm Hasselbring: ORCID iD orcid.org/0000-0001-6625-4335

Catalogue record

Date deposited: 05 Apr 2024 16:38
Last modified: 10 Apr 2024 02:15

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Contributors

Author: Alexander Barbie
Author: Wilhelm Hasselbring ORCID iD
Author: Malte Hansen

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