Digital twins in smart farming

Abstract Digital Twins are very promising to bring smart farming to new levels of farming productivity and sustainability. A Digital Twin is a digital equivalent of a real-life object of which it mirrors its behaviour and states over its lifetime in a virtual space. Using Digital Twins as a central means for farm management enables the decoupling of physical flows from its planning and control. As a consequence, farmers can manage operations remotely based on (near) real-time digital information instead of having to rely on direct observation and manual tasks on-site. This allows them to act immediately in case of (expected) deviations and to simulate effects of interventions based on real-life data. This paper analyses how Digital Twins can advance smart farming. It defines the concept, develops a typology of different types of Digital Twins, and proposes a conceptual framework for designing and implementing Digital Twins. The framework comprises a control model based on a general systems approach and an implementation model for Digital Twin systems based on the Internet of Things—Architecture (IoT-A), a reference architecture for IoT systems. The framework is applied to and validated in five smart farming use cases of the European IoF2020 project, focussing on arable farming, dairy farming, greenhouse horticulture, organic vegetable farming and livestock farming.

[1]  Cor Verdouw,et al.  Digital twins in farm management : illustrations from the FIWARE accelerators SmartAgriFood and Fractals , 2017 .

[2]  Richard McClatchey,et al.  Support for product data from design to production , 1998 .

[3]  Artemis Moroni,et al.  Vision and Challenges for Realising the Internet of Things , 2010 .

[4]  Mike Philpotts,et al.  An introduction to the concepts, benefits and terminology of product data management , 1996 .

[5]  Bedir Tekinerdogan,et al.  Systems Architecture Design Pattern Catalog for Developing Digital Twins , 2020, Sensors.

[6]  Folorunso Oludayo Fasina,et al.  Systematic review and meta-analyses of cases and deaths associated with highly pathogenic avian influenza H5N1 in humans and poultry , 2016 .

[7]  Arquimedes Canedo,et al.  Industrial IoT lifecycle via digital twins , 2016, 2016 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[8]  Jason Yon,et al.  Characterising the Digital Twin: A systematic literature review , 2020, CIRP Journal of Manufacturing Science and Technology.

[9]  Steven J. Fenves,et al.  A product information modeling framework for product lifecycle management , 2005, Comput. Aided Des..

[10]  R. Yin Case Study Research: Design and Methods , 1984 .

[11]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[12]  Spyros Fountas,et al.  Farm management information systems: Current situation and future perspectives , 2015, Comput. Electron. Agric..

[13]  Zhong Fan,et al.  Digital Twin: Enabling Technologies, Challenges and Open Research , 2020, IEEE Access.

[14]  C StoreyVeda,et al.  Design science in the information systems discipline , 2008 .

[15]  Florian Michahelles,et al.  An Architectural Approach Towards the Future Internet of Things , 2011, Architecting the Internet of Things.

[16]  Victoria Beltran,et al.  Decision support systems for agriculture 4.0: Survey and challenges , 2020, Comput. Electron. Agric..

[17]  Thomas Bartzanas,et al.  Internet of Things in agriculture, recent advances and future challenges , 2017 .

[18]  Martin Bauer Nec,et al.  Internet of Things – Architecture IoT-A Deliverable D1.5 – Final architectural reference model for the IoT v3.0 , 2013 .

[19]  Sang Do Noh,et al.  Design and implementation of a digital twin application for a connected micro smart factory , 2019, Int. J. Comput. Integr. Manuf..

[20]  S. Wolfert,et al.  Big Data in Smart Farming – A review , 2017 .

[21]  M. B. Santosh Kumar,et al.  Digital Twin in Smart Farming: A Categorical Literature Review and Exploring Possibilities in Hydroponics , 2020, 2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA).

[22]  Edward H. Glaessgen,et al.  The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles , 2012 .

[23]  Soh-Khim Ong,et al.  Product Information Modeling , 2008 .

[24]  Carsten Magerkurth,et al.  IoT Reference Model , 2013 .

[25]  J. Wolfert,et al.  Virtualization of food supply chains with the internet of things , 2016 .

[26]  Sandro Wartzack,et al.  Shaping the digital twin for design and production engineering , 2017 .

[27]  J. Wyatt Decision support systems. , 2000, Journal of the Royal Society of Medicine.

[28]  Hyeon Park,et al.  Smart Livestock Farms Using Digital Twin: Feasibility Study , 2018, 2018 International Conference on Information and Communication Technology Convergence (ICTC).

[29]  Peter Hehenberger,et al.  Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and their Designers , 2016 .

[30]  Gregoris Mentzas,et al.  Prescriptive analytics: Literature review and research challenges , 2020, Int. J. Inf. Manag..

[31]  Bedir Tekinerdogan,et al.  Architecture framework of IoT-based food and farm systems: A multiple case study , 2019, Comput. Electron. Agric..

[32]  Stefan Boschert,et al.  Digital Twin—The Simulation Aspect , 2016 .

[33]  Izak Benbasat,et al.  The Case Research Strategy in Studies of Information Systems , 1987, MIS Q..

[34]  J.G.A.J. van der Vorst,et al.  Virtualisation of floricultural supply chains , 2013 .

[35]  Maurizio Tomasella,et al.  Vision and Challenges for Realising the Internet of Things , 2010 .

[36]  Olga Yalovenko,et al.  Developing a smart cyber-physical system based on digital twins of plants , 2020, 2020 Fourth World Conference on Smart Trends in Systems, Security and Sustainability (WorldS4).

[37]  Per Runeson,et al.  Guidelines for conducting and reporting case study research in software engineering , 2009, Empirical Software Engineering.

[38]  K. Eisenhardt Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[39]  Dionysis Bochtis,et al.  Conceptual model of a future farm management information system , 2010 .

[40]  Joachim Hertzberg,et al.  "Digitale Zwillinge" als Werkzeug für die Entwicklung von Feldrobotern in landwirtschaftlichen Prozessen , 2019, GIL Jahrestagung.

[41]  Karel Kruger,et al.  A Six-Layer Digital Twin Architecture for a Manufacturing Cell , 2018, SOHOMA.

[42]  Abdulmotaleb El Saddik,et al.  C2PS: A Digital Twin Architecture Reference Model for the Cloud-Based Cyber-Physical Systems , 2017, IEEE Access.

[43]  Veda C. Storey,et al.  Design science in the information systems discipline: an introduction to the special issue on design science research , 2008 .

[44]  W. Lockeretz,et al.  Organic farming : an international history , 2007 .

[45]  Abdulmotaleb El Saddik,et al.  Digital Twins: The Convergence of Multimedia Technologies , 2018 .

[46]  Alan R. Hevner,et al.  Design Science in Information Systems Research , 2004, MIS Q..

[47]  D. Bochtis,et al.  Conceptual model of a future farm management information system , 2010 .

[48]  Hajo A. Reijers,et al.  A control model for object virtualization in supply chain management , 2015, Comput. Ind..

[49]  Volker Stich,et al.  Business Models for Industrial Smart Services – The Example of a Digital Twin for a Product-Service-System for Potato Harvesting , 2019, Procedia CIRP.

[50]  J. Wolfert,et al.  Fostering business and software ecosystems for large-scale uptake of IoT in food and farming , 2017 .

[51]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[52]  Felix Wortmann,et al.  Internet of Things , 2015, Business & Information Systems Engineering.

[53]  Nicola Bui,et al.  Internet of Things Architecture - IoT-A , 2013 .

[54]  Wilfried Sihn,et al.  Digital Twin in manufacturing: A categorical literature review and classification , 2018 .

[55]  Andreas Kamilaris,et al.  Deep learning in agriculture: A survey , 2018, Comput. Electron. Agric..

[56]  Eric K. Clemons,et al.  Business Models , 2014, Bus. Inf. Syst. Eng..

[57]  Alessandro Bassi,et al.  Enabling Things to Talk: Designing IoT solutions with the IoT Architectural Reference Model , 2013 .

[58]  João Barata,et al.  Towards Sustainable Digital Twins for Vertical Farming , 2018, 2018 Thirteenth International Conference on Digital Information Management (ICDIM).

[59]  Jacques H. Trienekens,et al.  Global Food Supply Chains , 2014 .

[60]  Michael W. Grieves Product lifecycle management: the new paradigm for enterprises , 2005 .

[61]  Florian Michahelles,et al.  Architecting the Internet of Things , 2011 .

[62]  Elisa Bertino,et al.  Internet of Things (IoT) , 2016, ACM Trans. Internet Techn..

[63]  David Garlan,et al.  Documenting software architectures: views and beyond , 2002, 25th International Conference on Software Engineering, 2003. Proceedings..

[64]  J. Aken Management Research Based on the Paradigm of the Design Sciences: The Quest for Field-Tested and Grounded Technological Rules , 2004 .

[65]  Fei Tao,et al.  Digital twin-driven product design, manufacturing and service with big data , 2017, The International Journal of Advanced Manufacturing Technology.

[66]  B. Tekinerdogan,et al.  Internet of Things in agriculture , 2016 .

[67]  Reiner Anderl,et al.  Digital Twin Requirements in the Context of Industry 4.0 , 2018, PLM.

[68]  Bert Beck,et al.  Smart Farming Technologies – Description, Taxonomy and Economic Impact , 2017 .

[69]  John M. Antle,et al.  Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology , 2017, Agricultural systems.

[70]  Fabio Lima,et al.  A digital twin for smart farming , 2019, 2019 IEEE Global Humanitarian Technology Conference (GHTC).

[71]  Michael W. Grieves,et al.  Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems , 2017 .