Digital twin prototypes for supporting automated integration testing of smart farming applications
Digital twin prototypes for supporting automated integration testing of smart farming applications
Industry 4.0 marks a major technological shift, revolutionizing manufacturing with increased efficiency, productivity, and sustainability. This transformation is paralleled in agriculture through smart farming, employing similar advanced technologies to enhance agricultural practices. Both fields demonstrate a symmetry in their technological approaches. Recent advancements in software engineering and the digital twin paradigm are addressing the challenge of creating embedded software systems for these technologies. Digital twins allow full development of software systems before physical prototypes are made, exemplifying a cost-effective method for Industry 4.0 software development. Our digital twin prototype approach mirrors software operations within a virtual environment, integrating all sensor interfaces to ensure accuracy between emulated and real hardware. In essence, the digital twin prototype acts as a prototype of its physical counterpart, effectively substituting it for automated testing of physical twin software. This paper discusses a case study applying this approach to smart farming, specifically enhancing silage production. We also provide a lab study for independent replication of this approach. The source code for a digital twin prototype of a PiCar-X by SunFounder is available open-source on GitHub, illustrating how digital twins can bridge the gap between virtual simulations and physical operations, highlighting the symmetry between physical and digital twins.
agricultural machinery, automated testing, continuous integration, digital twin prototypes, smart farming
Barbie, Alexander
c567ce7d-cf04-472a-a203-00070f06f97e
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Hansen, Malte
24fe48bd-9286-4118-8eb8-b70aa34b041d
12 February 2024
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)
Digital twin prototypes for supporting automated integration testing of smart farming applications.
Symmetry, 16 (2), [221].
(doi:10.3390/sym16020221).
Abstract
Industry 4.0 marks a major technological shift, revolutionizing manufacturing with increased efficiency, productivity, and sustainability. This transformation is paralleled in agriculture through smart farming, employing similar advanced technologies to enhance agricultural practices. Both fields demonstrate a symmetry in their technological approaches. Recent advancements in software engineering and the digital twin paradigm are addressing the challenge of creating embedded software systems for these technologies. Digital twins allow full development of software systems before physical prototypes are made, exemplifying a cost-effective method for Industry 4.0 software development. Our digital twin prototype approach mirrors software operations within a virtual environment, integrating all sensor interfaces to ensure accuracy between emulated and real hardware. In essence, the digital twin prototype acts as a prototype of its physical counterpart, effectively substituting it for automated testing of physical twin software. This paper discusses a case study applying this approach to smart farming, specifically enhancing silage production. We also provide a lab study for independent replication of this approach. The source code for a digital twin prototype of a PiCar-X by SunFounder is available open-source on GitHub, illustrating how digital twins can bridge the gap between virtual simulations and physical operations, highlighting the symmetry between physical and digital twins.
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symmetry-16-00221-v2
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More information
Accepted/In Press date: 4 February 2024
e-pub ahead of print date: 12 February 2024
Published date: 12 February 2024
Keywords:
agricultural machinery, automated testing, continuous integration, digital twin prototypes, smart farming
Identifiers
Local EPrints ID: 488801
URI: http://eprints.soton.ac.uk/id/eprint/488801
ISSN: 2073-8994
PURE UUID: 4a794737-1682-4cf6-aa2c-d753da14c2fe
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Date deposited: 05 Apr 2024 16:44
Last modified: 20 Jun 2024 02:06
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Author:
Alexander Barbie
Author:
Wilhelm Hasselbring
Author:
Malte Hansen
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