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Digital twins in farm management: illustrations from the FIWARE accelerators SmartAgriFood and Fractals
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The Internet of Things (IoT) provides a vision of a world in which the Internet extends into the real world embracing everyday objects. In the IoT, physical objects are accompanied by Digital Twins: virtual, digital equivalents to physical objects. The interaction between real/physical and digital/virtual objects (digital twins) is an essential concept behind this vision. Digital twins can act as a central means to manage farms and has the potential to revolutionize agriculture. It removes fundamental constraints concerning place, time, and human observation. Farming operations would no longer require physical proximity, which allows for remote monitoring, control and coordination of farm operations. Moreover, Digital Twins can be enriched with information that cannot be observed (or not accurately) by the human senses, e.g. sensor and satellite data. A final interesting angle is that Digital Twins do not only represent actual states, but can also reproduce historical states and simulate future states. As a consequence, applications based on Digital Twins, if properly synchronized, enable farmers and other stakeholders to act immediately in case of (expected) deviations. This paper introduces the concept of Digital Twins and illustrate its application in agriculture by six cases of the SmartAgriFood and Fractals accelerator projects (2014-2016).
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... Nonetheless, certain industries, including aero manufacturing [104], oil field services [105], software [42], fast-moving consumer goods [106], and tire manufacturing [106], are already harnessing the advantages of DTs. Similarly, the experiments and review literature mentioned earlier [8,15,17,20,21,24,49,[51][52][53][106][107][108][109][110][111] enable the broad adoption of DTs in the livestock sector to enhance animal management, early disease detection, farm administration, environmental management, and optimization of feed and water resources. This study aims to bridge the knowledge gap in DT adoption in livestock by providing a comprehensive overview that builds on but expands beyond existing reviews. ...
... Despite the promising potential of digital twins, their widespread adoption necessitates addressing several practical knowledge gaps. The authors express concern regarding several open issues identified in recent research [8,10,15,17,20,21,24,49,[51][52][53][106][107][108][109][110][111]] that warrant attention in future studies. To fully leverage the advantages of DTs in livestock production systems, several unresolved issues and challenges must be addressed, as follows: Data Overload and Mismanagement: A DT system generates large amounts of data, and a farm without proper data management and analytics may not be able to act upon such information. ...
The impacts of climate change on agricultural production are becoming more severe, leading to increased food insecurity. Adopting more progressive methodologies, like smart farming instead of conventional methods, is essential for enhancing production. Consequently, livestock production is swiftly evolving towards smart farming systems, propelled by rapid advancements in technology such as cloud computing, the Internet of Things, big data, machine learning, augmented reality, and robotics. A Digital Twin (DT), an aspect of cutting-edge digital agriculture technology, represents a virtual replica or model of any physical entity (physical twin) linked through real-time data exchange. A DT conceptually mirrors the state of its physical counterpart in real time and vice versa. DT adoption in the livestock sector remains in its early stages, revealing a knowledge gap in fully implementing DTs within livestock systems. DTs in livestock hold considerable promise for improving animal health, welfare, and productivity. This research provides an overview of the current landscape of digital transformation in the livestock sector, emphasizing applications in animal monitoring, environmental management, precision agriculture, and supply chain optimization. Our findings highlight the need for high-quality data, comprehensive data privacy measures, and integration across varied data sources to ensure accurate and effective DT implementation. Similarly, the study outlines their possible applications and effects on livestock and the challenges and limitations, including concerns about data privacy, the necessity for high-quality data to ensure accurate simulations and predictions, and the intricacies involved in integrating various data sources. Finally, the paper delves into the possibilities of digital twins in livestock, emphasizing potential paths for future research and progress.
... Implementing Digital Twins at a basic level, down to individual plants or animals, can offer more value but is also more challenging and costly. Managing the interdependencies between Digital Twins at different granularity levels is a key challenge in this context (Verdouw and Kruize, 2017). ...
... Digital Twins offer farmers the ability to separate the physical aspects of farm operations from their informational aspects, as explained by (Verdouw and Kruize, 2017). This decoupling of control involves translating measurements of the object system's status into a Digital Twin, as illustrated in Fig. 6.9. ...
A digital twin is a virtual representation or a digital counterpart of a physical object, system, or process. It is created using real-time data and simulations to mimic the characteristics, behaviors and functionalities of its physical counterpart. The idea of the Digital Twin debuted in NASA's preliminary technological blueprint in 2010, where it was alternatively termed the 'Virtual Digital Fleet Leader.' NASA is recognized as the pioneer in defining the Digital Twin. They described it as an extensive, multi-dimensional, and probabilistic mimic of a vehicle or system. The simulation integrated cutting-edge physical models, real-time sensor data, historical fleet performance data, and other pertinent information. The primary goal was to faithfully replicate the real-world performance and behavior of the operational counterpart over its entire lifespan. Today, Digital twins are used in various domains, including manufacturing, engineering, healthcare, and urban planning, to better understand, monitor, and optimize physical assets and processes.
As we move forward, given the continuous advancement of AI technology, there will be an escalating need for increased vigilance, well-defined regulatory frameworks, and supplementary measures to uphold responsible and ethical deployment. These measures will be aimed at ensuring that algorithms are developed in a way that prioritizes the protection of user data. The paper aims to explore the concept of the digital twin, addressing its initial challenges. A significant emphasis is placed on the practical application of digital twin technology for the progression of villages. The study then delves into the origins and technological foundations of the digital twin. It further elucidates its historical development through illustrative cases, including its use in Disaster Management within Smart Villages and its implementation in the realm of farming.
https://shop.elsevier.com/books/digital-twins-for-smart-cities-and-villages/iyer/978-0-443-28884-5
... It's defined by its arrangement, purpose, and specific spatial and temporal limits. DT concepts can also apply to agriculture (Verdouw et al., 2017) and healthcare (Lee et al., 2020), focusing on natural events or biological processes. ...
... The DT's final element is the link between tangible existence and digital representation (Verdouw et al., 2017), enabling bidirectional data transmission (Autiosalo et al., 2019). IoT and sensor technology are often cited for data collection in DT, but offline methods like maintenance records and visual inspections are also valuable. ...
A digital twin (DT) can be seen as a tool that speeds up the process of innovation. DT provides numerous advantages by generating a real-time replica of tangible systems. These benefits include faster business processes, higher productivity, and more innovative ideas at lower costs. It is one of the most exciting new digital technologies being worked upon to provide assistance to different types of businesses to go digital and make decisions. The idea of a DT has been around for almost 20 years, but it is still changing as it is used in various fields. This chapter looks at 46 different definitions and research work of DT that have been written in the last 10 years and comes up with a single, more general definition that includes all of them. It also gives a detailed description of the DT and how it differs from other digital technologies. A case study is provided on how DT works and how it can be used, along with discussions on future opportunities of DT.
... Digital twins of cyber-biophysical systems have been applied to drug discovery [35] and livestock farming [30]. In smart agriculture, digital twin prototypes have been developed for the identification of diseases from images [37] or the harvesting of potatoes [15]. Such approaches either do not integrate the collaboration of multiple stakeholders for the operation of the system, or do not model different abstractions of the physical entity. ...
Digital twins of complex systems are operated by stakeholders from different domains, who typically do not work in the same language. This problem is exacerbated in digital twins where domain-specific representations are required to convey actionable results, such as in cyber-biophysical systems. Particularly, in controlled environment agriculture, agronomists devise seasonal production plans and run simulations to optimize the system in terms of crop phenology while growers maintain crops and ensure their optimal growth by assessing crop morphology. To breach this gap, we consider an optimization problem to reconcile the different users' points of views. We propose a modeling methodology that bridges the gap between crop phenology and morphology, generating visual representations of crops based on simulated phenological characteristics. To demonstrate the validity of our proposed methodology for digital twins in smart farming, we apply our approach to two case studies: a strawberry vertical farm and a smart canola field.
... A digital twin is "a digital clone having either a living or non-living physical thing," and its purpose is to "produce live electronic simulation models that upgrade and evolve as their true counterparts change," according to [Digital Twin Wiki]. The Digital twins in agriculture and farm management enable remote monitoring, control, and also agricultural operation coordination since they eliminate the need for physical proximity (Verdouw & Kruize, 2015). In terms of SPAE, simulation models like the DNDC, CEEOT, COMET-Farm, and/ or NTT models listed above are a few techniques that might be utilized as the foundation for assuring the least possible environmental impact without increasing expenses (Figure 6.1). ...
... However, due to the open nature of agricultural and forestry environments, the definition of DTs cannot clearly reflect the dynamic and unpredictable conditions that are met in these environments. This was the main reason for the delay in the development and implementation of DTs in these sectors [103]. In the current review study, a detailed description of the DTs and the categorization of the different levels of implementation in agriculture and forestry were discussed. ...
Digital twins aim to optimize practices implemented in various sectors by bridging the gap between the physical and digital worlds. Focusing on open-field agriculture, livestock farming, and forestry and reviewing the current applications in these domains, this paper reveals the multifaceted roles of digital twins. Diverse key aspects are examined, including digital twin integration and maturity level, means of data acquisition, technological capabilities, and commonly used input and output features. Through the prism of four primary research questions, the state of the art of digital twins, the extent of their achieved integration, and an overview of the critical issues and potential advancements are provided in the landscape of the sectors under consideration. The paper concludes that in spite of the remarkable progress, there is a long way towards achieving full digital twin. Challenges still persist, while the key factor seems to be the integration of expert knowledge from different stakeholders. In light of the constraints identified in the review analysis, a new sector-specific definition for digital twins is also suggested to align with the distinctive characteristics of intricate biotic and abiotic systems. This research is anticipated to serve as a useful reference for stakeholders, enhancing awareness of the considerable benefits associated with digital twins and promoting a more systematic and comprehensive exploration of this transformative topic.
The hybridization of energy sources in an electric UAV poses problems of instantaneous power management, efficient distribution of energy between the power sources, monitoring the state of the battery, saving energy and increasing UAV’s autonomy. Energy management strategies (EMS) are in great demand to solve these problems. To date, research efforts have largely focused on energy management strategies and algorithms tested through simulations. Despite the good results obtained in terms of energy optimization and maximizing flight autonomy in simulation situations, the EMS of hybrid electric UAVs continues to suffer from its lack of application in the real world. This paper proposes the concepts of integrated energy management strategy (iEMS) and digital twin (DT) to experiment with EMS for hybrid electric UAVs through flight testing. These approaches offer the capabilities of real-time EMS management, real-time optimization and monitoring, and remote access. This research aims to demonstrate the usefulness of integrated energy management strategy (iEMS) and digital twins (DT) for improving energy and thermal performance, as well as increasing the flight duration of hybrid electric UAVs under real flight conditions. This research not only describes iEMS and DT, but also outlines the technical, economic, operational and normative issues associated with their practical application in UAVs, as well as the respective countermeasures. It highlights recent research developments on the combined use of digital twins and digital technologies such as AI, ML, DRL, 5G/6G, Blockchain, cloud computing and IoT in drones. Readers will also find insights into future research, as well as interdisciplinary perspectives on how different fields (mechanical and materials engineering, electrical, computer science, data science, telecommunications, meteorology) can collaborate to optimize drone energy management.
Digital innovation significantly contributes to the transformation of agrifood systems, aiming to achieve the Sustainable Development Goals (SDGs) and the realization of the Society 5.0 vision. The agriculture sector is currently witnessing significant breakthroughs due to the utilization of many technologies, including artificial intelligence (AI), robots, data analytics, mobile apps, blockchain technology, and digital twins. These innovations not only help in productivity enhancement, efficiency, and sustainability but also address societal challenges. These digital innovations contribute to achieving the SDGs by improving food security, reducing poverty, promoting sustainable practices, and fostering inclusive economic growth. Furthermore, these innovations in agrifood systems support the transition toward Society 5.0, in which humans and advanced technologies cooperate for sustainable development. This transition enables precision agriculture, autonomous farming, smart logistics, and intelligent distribution systems, creating more efficient and resilient agrifood systems.
This literature review on Internet of Things (IoT) in agriculture and food, provides an overview of
existing applications, enabling technologies and main challenges ahead. The results of the review
show that this subject received attention by the scientific community from 2010 on and the number
of papers has increased since then. The literature on IoT in agriculture and food is very much
dominated by Asian scientists, especially from China. In other continents, the concept of IoT was up
to recently mainly adopted by non-agricultural scientists. The application area of food supply chains is
addressed most frequently, followed by arable farming. Most papers report the results of explorative
studies or they present IoT systems that are designed or implemented in prototypes and pilots. The
literature reviewed focuses on sensing and monitoring, while actuation and remote control is much
less addressed. The findings indicate that IoT is still in its infancy in the agriculture and food domain.
Applications are often fragmentary, lack seamless integration and especially more advanced solutions
are in an experimental stage of development. Important challenges to overcome this situation include
(i) integration of existing IoT solutions by open IoT architectures, platforms and standards,
(ii) upscaling the usage of interoperable IoT technologies beyond early adopters especially by the
simplification of existing solutions and make it more affordable for end users, and (iii) further
improvement of IoT technologies to ensure a broad usability in the diversity of the agri-food domain.
Systems do not simply pop into existence. They progress through lifecycle phases of creation, production, operations, and disposal. The issues leading to undesirable and unpredicted emergent behavior are set in place during the phases of creation and production and realized during the operational phase, with many of those problematic issues due to human interaction. We propose that the idea of the Digital Twin, which links the physical system with its virtual equivalent can mitigate these problematic issues. We describe the Digital Twin concept and its development, show how it applies across the product lifecycle in defining and understanding system behavior, and define tests to evaluate how we are progressing. We discuss how the Digital Twin relates to Systems Engineering and how it can address the human interactions that lead to “normal accidents.” We address both Digital Twin obstacles and opportunities, such as system replication and front running. We finish with NASA’s current work with the Digital Twin.
Internet technologies allow supply chains to use virtualizations dynamically in operational management processes. This will improve support for food companies in dealing with perishable products, unpredictable supply variations and stringent food safety and sustainability requirements. Virtualization enables supply chain actors to monitor, control, plan and optimize business processes remotely and in real-time through the Internet, based on virtual objects instead of observation on-site. This paper analyses the concept of virtual food supply chains from an Internet of Things perspective and proposes an architecture to implement enabling information systems. As a proof of concept, the architecture is applied to a case study of a fish supply chain. These developments are expected to establish a basis for virtual supply chain optimization, simulation and decision support based on on-line operational data. In the Internet of Things food supply chains can become self-adaptive systems in which smart objects operate, decide and learn autonomously.
This paper introduces the concept of a " Digital Twin " as a virtual representation of what has been produced. Compare a Digital Twin to its engineering design to better understand what was produced versus what was designed, tightening the loop between design and execution.
Foreword by Peter Friess & Gérald Santuci:
It goes without saying that we are very content to publish this Clusterbook and to leave it today to your hands. The Cluster of European Research projects on the Internet of Things – CERP-IoT – comprises around 30 major research initiatives, platforms and networks work-ing in the field of identification technologies such as Radio Frequency Identification and in what could become tomorrow an Internet-connected and inter-connected world of objects. The book in front of you reports to you about the research and innovation issues at stake and demonstrates approaches and examples of possible solutions.
If you take a closer look you will realise that the Cluster reflects exactly the ongoing developments towards a future Internet of Things – growing use of Identification technologies, massive deployment of simple and smart devices, increasing connection between objects and systems. Of course, many developments are less directly derived from the core research area but contribute significantly in creating the “big picture” and the paradigm change.
We are also conscious to maintain Europe’s strong position in these fields and the result being achieved, but at the same time to understand the challenges ahead as a global endeavour with our international partners. As it regards international co-operation, the cluster is committed to increasing the number of common activities with the existing international partners and to looking for various stakeholders in other countries.
However, we are just at the beginning and, following the prognostics which predict 50 to 100 billion devices to be connected by 2020, the true research work starts now. The European Commission is decided to implement its Internet of Things policy for supporting an economic revival and providing better life to its citizens, and it has just selected from the last call for proposals several new Internet of Things research projects as part of the 7th Framework Programme on European Research.
We wish you now a pleasant and enjoyable reading and would ask you to stay connected with us for the future. Special thanks are expressed to Harald Sundmaeker and his team who did a remarkable effort in assembling this Clusterbook.
Many of the initial developments towards the Internet of Things have focused on the combination of Auto-ID and networked infrastructures
in businessto- business logistics and product life cycle applications. However, a future Internet of Things can provide a
broader vision and also enable everyone to access and contribute rich information about things and locations. The success
of social networks to share experience and personalised insights shows also great potential for integration with business-centric
applications. The integration and interoperability with mainstream business software platforms can be enhanced and extended
by real-time analytics, business intelligence and agent-based autonomous services. Information sharing may be rewarded through
incentives, thus transforming the Internet of Things from a cost-focused experiment to a revenue-generating infrastructure
to enable trading of enriched information and accelerate business innovation. Mash-ups and end-user programming will enable
people to contribute to the Internet of Things with data, presentation and functionality. Things-generated physical world
content and events from Auto-ID, sensors, actuators or meshed networks will be aggregated and combined with information from
virtual worlds, such as business databases and Web 2.0 applications, and processed based on new business intelligence concepts.
Direct action on the physical world will be supported through machine-interfaces and introduction of agile strategies. This
chapter aims to provide a concept for a future architecture of the Internet of Things, including a definition, a review of
developments, a list of key requirements and a technical design for possible implementation of the future Internet of Things.
As open issues, the evaluation of usability by stakeholders in user-centric as well as business-centric scenarios is discussed
and the need for quantifying costs and benefits for businesses, consumers, society and the environment is emphasised. Finally,
guidelines are derived, for use by researchers as well as practitioners.
Due to the emergence of the Internet of Things, supply chain control can increasingly be based on virtual objects instead of on the direct observation of physical objects. Object virtualization allows the decoupling of control activities from the handling and observing of physical products and resources. Moreover, virtual objects can be enriched with information that goes beyond human observation. This will allow for more advanced control capabilities, e.g. concerning tracking and tracing, quality monitoring and supply chain (re)planning. This paper proposes a control model for object virtualization in supply chain management, which is based on a multiple case study in the Dutch floriculture. It includes a typology of distinct mechanisms for object virtualization, which discerns reference objects and future projections next to the representation of real physical objects. The control model helps to define feasible redesign options for the virtualization of supply chain control. It is also of value as a basis to define the requirements for information systems that enable these redesign options.
Industrial iot lifecycle via digital twins
- A Canedo
Canedo A 2016. Industrial iot lifecycle via digital twins, Proceedings of the 11th IEEE/ACM/IFIP
International Conference on Hardware/Software Codesign and System Synthesis, CODES 2016.
Connected cattle: wearables are changing the dairy industry, The Institute
- K Pretz
Pretz K 2016. Connected cattle: wearables are changing the dairy industry, The Institute. IEEE.