4.7 Article

Digital twin challenges in biodiversity modelling

Related references

Note: Only part of the references are listed.
Article Ecology

Digital twins: dynamic model-data fusion for ecology

Koen de Koning et al.

Summary: Digital twins are emerging as a new tool in monitoring and understanding systems and processes, with the potential to transform ecology digitally. However, it is crucial to avoid misguided developments and instead combine data, models, and domain knowledge and align them with the real world.

TRENDS IN ECOLOGY & EVOLUTION (2023)

Article Green & Sustainable Science & Technology

Digital Twins in agriculture: challenges and opportunities for environmental sustainability

Warren Purcell et al.

Summary: Food security, land degradation, climate change, and population growth are interconnected challenges for sustainable agriculture. The Digital Twin (DT) can overcome these challenges and support sustainability by utilizing advanced technologies and increasing information availability. However, potential negative effects and dangers of the technology must be assessed and mitigated. An exploratory review outlines progress and identifies necessary milestones for supporting open and sustainable development of DTs in agriculture.

CURRENT OPINION IN ENVIRONMENTAL SUSTAINABILITY (2023)

Article Engineering, Multidisciplinary

Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology

Zheyuan Hu et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2023)

Article Computer Science, Interdisciplinary Applications

Simulation-assisted machine learning for operational digital twins

Christos Pylianidis et al.

Summary: In the field of environmental sciences, combining process-based models with machine learning models can enhance modeling capabilities. However, both types of models have limitations in terms of input data. To overcome these limitations, we propose a methodology that uses a process-based model to generate data, aggregates them to a lower resolution to mimic real situations, and utilizes a fraction of the process-based model inputs to develop machine learning models. In a case study of pasture nitrogen response rate prediction, we demonstrate the practicality and accuracy of this method.

ENVIRONMENTAL MODELLING & SOFTWARE (2022)

Article Multidisciplinary Sciences

Digital rheometer twins: Learning the hidden rheology of complex fluids through rheology-informed graph neural networks

Mohammadamin Mahmoudabadbozchelou et al.

Summary: This paper presents a method for constructing Rheology-informed Graph Neural Networks (RhiGNets) using machine learning techniques to learn the hidden rheological properties of complex fluids through a limited number of experiments. A multifidelity approach is used to combine limited additional experimental data with RhiGNet predictions to develop digital rheometers.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2022)

Article Environmental Sciences

Digital Twin Technology Challenges and Applications: A Comprehensive Review

Diego M. Botin-Sanabria et al.

Summary: A digital twin is a virtual representation of a physical object or process that collects information from the real environment to validate and simulate its present and future behavior. It plays a crucial role in data-driven decision making, complex systems monitoring, product validation and simulation, and object lifecycle management.

REMOTE SENSING (2022)

Article Engineering, Marine

Operational Modeling of North Aegean Oil Spills Forced by Real-Time Met-Ocean Forecasts

Panagiota Keramea et al.

Summary: Over the past few decades, oil marine pollution has become a significant threat to global ocean health. This study used an oil spill model to test the dispersion properties of oil and examine the impact of accidental spills on the main tanker transportation route in the North Aegean Sea. Numerical simulations were conducted to understand the influence of turbulent kinetic energy on oil spreading and mass properties.

JOURNAL OF MARINE SCIENCE AND ENGINEERING (2022)

Article Computer Science, Theory & Methods

Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence

Jorge Ejarque et al.

Summary: The paper discusses the convergence of High-Performance Computing (HPC), data analytics (DA), and artificial intelligence (AI), and identifies the main challenges faced in integrating these technologies. It proposes a new workflow platform and the HPC Workflow as a Service (HPCWaaS) paradigm to address these challenges and facilitate the management and reusability of complex workflows in federated HPC infrastructures.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2022)

Article Engineering, Mechanical

Digital twins for design in the presence of uncertainties

Jiannan Yang et al.

Summary: A tailored approach is needed to identify high value information from uncertain data when applying digital twins in the design process. The proposed sensitivity metric toolbox integrates black-box digital twins to capture evolving key design performance indicators and provide relevant metrics, including KPI-free metrics based on entropy and Fisher information. These KPI-free metrics are shown to play an important role in influencing KPI-based metrics, ensuring consistent identification of high value data throughout the design process.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

Article Computer Science, Interdisciplinary Applications

B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data

Liu Yang et al.

Summary: The paper introduces a Bayesian physics-informed neural network (B-PINN) for solving nonlinear problems, and conducts experimental comparisons on posterior estimation methods and uncertainty quantification. The KL model is as accurate and faster than BNN, but cannot be applied to high-dimensional problems.

JOURNAL OF COMPUTATIONAL PHYSICS (2021)

Article Computer Science, Interdisciplinary Applications

Pipedream: An interactive digital twin model for natural and urban drainage systems

Matthew Bartos et al.

Summary: This study introduces a novel digital twin model for water resources management, which integrates sensor data and online models to real-time model water systems and control system dynamics effectively; Using real-world watershed data, it is found that the model can accurately interpolate hydraulic states and predict future states; By providing a complete real-time hydraulic view, it helps to rapidly detect floods, improve maintenance, and control water systems.

ENVIRONMENTAL MODELLING & SOFTWARE (2021)

Article Chemistry, Multidisciplinary

Developing a Digital Twin and Digital Thread Framework for an 'Industry 4.0' Shipyard

Toh Yen Pang et al.

Summary: This paper provides an overview of advanced digital twin and digital thread technologies in industrial operations, introducing a new framework that combines both for improved data management and innovation.

APPLIED SCIENCES-BASEL (2021)

Review Engineering, Environmental

Plastic pollution: A focus on freshwater biodiversity

Valter M. Azevedo-Santos et al.

Summary: Plastic pollution is a major environmental issue in global freshwater ecosystems, impacting 206 freshwater species from invertebrates to mammals. Addressing this problem will require coordinated action, such as recycling, proper disposal, stringent legislation, inspection, synthetic polymer replacement, and ecological restoration. Current information suggests that the situation in freshwater ecosystems may be as severe as ocean pollution, despite being highly underestimated.

AMBIO (2021)

Article Engineering, Multidisciplinary

hp-VPINNs: Variational physics-informed neural networks with domain decomposition

Ehsan Kharazmi et al.

Summary: The study proposes a general framework for hp-variational physics-informed neural networks (hp-VPINNs) based on the nonlinear approximation of shallow and deep neural networks and hp-refinement via domain decomposition and projection onto high-order polynomials. The hp-refinement corresponds to a global approximation with a local learning algorithm for efficient network parameter optimization, demonstrating advantages in accuracy and training cost for function approximation and solving differential equations.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2021)

Article Environmental Sciences

A digital twin of Earth for the green transition

Peter Bauer et al.

Summary: The EU plans to fund the development of digital twins of Earth to support its green transition. By using a methodological framework, they aim to create a new Earth system simulation and observation capability.

NATURE CLIMATE CHANGE (2021)

Article Agriculture, Multidisciplinary

Introducing digital twins to agriculture

Christos Pylianidis et al.

Summary: Digital twins are increasingly adopted by various industries, yet it is uncertain whether agriculture is making efforts to embrace this technology. This research investigates the added-value of digital twins for agriculture through a mixed-method approach, providing insights into adoption levels and suggesting a roadmap for implementation based on digital twin characteristics in agriculture and other disciplines.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)

Article Chemistry, Multidisciplinary

A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture

Jesus David Chaux et al.

Summary: This paper introduces the application of digital twin architecture in CEA systems, which can optimize productivity by improving crop production and management strategies, contributing to food security.

APPLIED SCIENCES-BASEL (2021)

Editorial Material Computer Science, Hardware & Architecture

THE ROAD TO EUROPEAN DIGITAL SOVEREIGNTY WITH GAIA-X AND IDSA

Arnaud Braud et al.

Summary: Digitalization is reshaping the world with significant economic and social impacts. The ban on Huawei by the U.S. raises concerns about how nations should manage digital technologies for national security and democratic values.

IEEE NETWORK (2021)

Article Chemistry, Analytical

A Redundancy Metric Set within Possibility Theory for Multi-Sensor Systems

Christoph-Alexander Holst et al.

Summary: In intelligent technical multi-sensor systems, studying the redundancy metric between sensors can improve system robustness against sensor failures and reduce computational costs.

SENSORS (2021)

Article Meteorology & Atmospheric Sciences

A Vector-Based River Routing Model for Earth System Models: Parallelization and Global Applications

Naoki Mizukami et al.

Summary: A vector-river network utilizes realistic geometries to improve the accuracy of physical properties in river modeling, requiring efficient methods for streamflow routing. A new parallelization method effectively decomposes river networks for parallel routing computations, demonstrating excellent computational scaling globally but facing challenges in computing for a single large basin. Global routing experiments show that vector-river network scale has less impact on discharge simulations compared to runoff inputs generated by land surface models and meteorological forcing.

JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS (2021)

Article Chemistry, Multidisciplinary

Digital Twin Providing New Opportunities for Value Co-Creation through Supporting Decision-Making

Shaun West et al.

Summary: This study explores the application of digital twins in supporting value co-creation and decision-making through multiple cases, identifying eight managerial issues to consider. Digital twin applications have the potential in both production and non-production environments, providing multiple perspectives to support decision-making and value creation.

APPLIED SCIENCES-BASEL (2021)

Review Environmental Sciences

Shedding Light on Deep-Sea Biodiversity-A Highly Vulnerable Habitat in the Face of Anthropogenic Change

Eva Paulus

Summary: The deep sea is one of the most biodiverse habitats on Earth, but is facing threats from human activities. Despite many mysteries remaining, there are challenges such as overfishing and environmental degradation that must be addressed to protect biodiversity in the deep sea.

FRONTIERS IN MARINE SCIENCE (2021)

Review Computer Science, Interdisciplinary Applications

Digital twin paradigm: A systematic literature review

Concetta Semeraro et al.

Summary: Manufacturing enterprises are facing the challenge of aligning themselves with new information technologies (IT) and responding to variable market demand. The key enabler of the IT revolution towards Smart Manufacturing is the digital twin (DT), which constantly synchronizes a virtual image with the real operating scenario to provide sound information for making decisions. This study aims to provide an overview of the main components of DT, their features, and interaction problems, while tracing ongoing research and technical challenges in conceiving and building DTs in different application domains and related technologies.

COMPUTERS IN INDUSTRY (2021)

Article Environmental Sciences

Digital Ecosystems for Developing Digital Twins of the Earth: The Destination Earth Case

Stefano Nativi et al.

Summary: The Digital Ecosystems (DEs) model is discussed as a framework for connecting and orchestrating online systems, infrastructures, and platforms to support the development of Digital Twins. Digital Twins help address global challenges and achieve sustainable development goals.

REMOTE SENSING (2021)

Article Computer Science, Information Systems

A Decision Support System for Urban Agriculture Using Digital Twin: A Case Study With Aquaponics

Adam Ghandar et al.

Summary: The global food system is facing various pressures such as urbanization, climate change, and environmental degradation. Urban agriculture has shown potential benefits in reducing waste and logistics costs, and can help relieve pressure on the natural environment. A new decision support system for urban farming is proposed, along with a case study on aquaponics technology enhanced with adaptive capabilities using digital twin system and machine learning, to plan production efficiently and sustainably. Additionally, a modelling framework for large-scale urban agriculture ecosystems is discussed, forming the basis of a suggested approach to coordinate activities of independent producers for collective goals in urban farming.

IEEE ACCESS (2021)

Article Computer Science, Artificial Intelligence

A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives

Kendrik Yan Hong Lim et al.

JOURNAL OF INTELLIGENT MANUFACTURING (2020)

Article Biodiversity Conservation

The 'known unknowns' of invasive species impact measurement

Robert Crystal-Ornelas et al.

BIOLOGICAL INVASIONS (2020)

Review Engineering, Manufacturing

Characterising the Digital Twin: A systematic literature review

David Jones et al.

CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY (2020)

Article Computer Science, Information Systems

A Requirements Driven Digital Twin Framework: Specification and Opportunities

James Moyne et al.

IEEE ACCESS (2020)

Article Computer Science, Information Systems

Digital Twin for the Oil and Gas Industry: Overview, Research Trends, Opportunities, and Challenges

Thumeera R. Wanasinghe et al.

IEEE ACCESS (2020)

Article Computer Science, Interdisciplinary Applications

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

M. Raissi et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2019)

Article Environmental Sciences

A framework for automated anomaly detection in high frequency water-quality data from in situ sensors

Catherine Leigh et al.

SCIENCE OF THE TOTAL ENVIRONMENT (2019)

Article Green & Sustainable Science & Technology

Biodiversity impacts due to food consumption in Europe

E. Crenna et al.

JOURNAL OF CLEANER PRODUCTION (2019)

Review Biotechnology & Applied Microbiology

Public Microbial Resource Centers: Key Hubs for Findable, Accessible, Interoperable, and Reusable (FAIR) Microorganisms and Genetic Materials

P. Becker et al.

APPLIED AND ENVIRONMENTAL MICROBIOLOGY (2019)

Article Computer Science, Information Systems

Using agent-based modelling to simulate social-ecological systems across scales

Melvin Lippe et al.

GEOINFORMATICA (2019)

Article Computer Science, Information Systems

A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications

Barbara Rita Barricelli et al.

IEEE ACCESS (2019)

Article Engineering, Civil

Assessment of Future Climate Change Projections Using Multiple Global Climate Models

Han Thi Oo et al.

CIVIL ENGINEERING JOURNAL-TEHRAN (2019)

Article Computer Science, Theory & Methods

Gathering requirements for advancing simulations in HPC infrastructures via science gateways

Sandra Gesing et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2018)

Review Biodiversity Conservation

The impacts of increasing drought on forest dynamics, structure, and biodiversity in the United States

James S. Clark et al.

GLOBAL CHANGE BIOLOGY (2016)

Article Multidisciplinary Sciences

Comment: The FAIR Guiding Principles for scientific data management and stewardship

Mark D. Wilkinson et al.

SCIENTIFIC DATA (2016)

Review Environmental Sciences

Environmental Impacts of the Deep-Water Oil and Gas Industry: A Review to Guide Management Strategies

Erik E. Cordes et al.

FRONTIERS IN ENVIRONMENTAL SCIENCE (2016)

Review Environmental Sciences

The role of satellite remote sensing in climate change studies

Jun Yang et al.

NATURE CLIMATE CHANGE (2013)

Review Multidisciplinary Sciences

Biodiversity loss and its impact on humanity

Bradley J. Cardinale et al.

NATURE (2012)

Article Geosciences, Multidisciplinary

A conceptual glacio-hydrological model for high mountainous catchments

B Schaefli et al.

HYDROLOGY AND EARTH SYSTEM SCIENCES (2005)

Article Hospitality, Leisure, Sport & Tourism

Biodiversity and tourism - Impacts and interventions

R van der Duim et al.

ANNALS OF TOURISM RESEARCH (2002)

Article Meteorology & Atmospheric Sciences

Earth system models of intermediate complexity: closing the gap in the spectrum of climate system models

M Claussen et al.

CLIMATE DYNAMICS (2002)