Digital twins for well-being: an overview

Digital Twin ◽  
2021 ◽  
Vol 1 ◽  
pp. 7
Author(s):  
Rahatara Fardousi ◽  
Fedwa Laamarti ◽  
M. Anwar Hossain ◽  
Chunsheng Yang ◽  
Abdulmotaleb El Saddik

Digital twin (DT) has gained success in various industries, and it is now getting attention in the healthcare industry in the form of well-being digital twin (WDT). In this paper, we present an overview of WDT to understand its potential scope, architecture and impact. We then discuss the definition  and the benefits of WDT. After that, we present the evolution of DT frameworks. Subsequently we discuss the challenges, the different types, the drawbacks, and potential application areas of WDT. Finally we present the requirements for a WDT framework extracted from the literature.

2021 ◽  
pp. medethics-2020-106134
Author(s):  
Matthias Braun

Simulations are used in very different contexts and for very different purposes. An emerging development is the possibility of using simulations to obtain a more or less representative reproduction of organs or even entire persons. Such simulations are framed and discussed using the term ‘digital twin’. This paper unpacks and scrutinises the current use of such digital twins in medicine and the ideas embedded in this practice. First, the paper maps the different types of digital twins. A special focus is put on the concrete challenges inherent in the interactions between persons and their digital twin. Second, the paper addresses the questions of how far a digital twin can represent a person and what the consequences of this may be. Against the background of these two analytical steps, the paper defines first conditions for digital twins to take on an ethically justifiable form of representation.


Author(s):  
Suresh Neethirajan ◽  
Bas Kemp

Digital twin technology is already improving efficiencies and reducing costs across multiple industries and sectors. As the earliest adopters, space technology and manufacturing sectors have made the most sophisticated gains with automobile and natural resource extraction industries following close behind with recent investments in digital twin technology. The application of digital twins within the livestock farming sector is the next frontier. The possibilities that this technology may fuel are nearly endless as digital twins can be used to improve large-scale precision livestock farming practices, machinery and equipment usage, and the health and well-being of a wide variety of farm animals. Currently, many pioneers of digital twins in livestock farming are already applying sophisticated AI technology to monitor both animals and environment around the clock, which leads to a better understanding of animal behavior and distress, disease control and prevention, and smarter business decisions for the farmer. Mental and emotional states of animals can be monitored using recognition technology that examines facial features such as ear postures and eye white regions. Used with modeling, simulation and augmented reality technologies, digital twins can help farmers build more energy-efficient housing structures, predict heat cycles for breeding, discourage negative behaviors of livestock, and potentially much more. As with all disruptive technological advances, the implementation of digital twin technology will demand a thorough cost and benefit analysis by individual farms. Digital twin application will need to overcome challenges and accept limitations that arise. However, regardless of these issues, the potential of digital twins promises to revolutionize livestock farming in the future.


Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1008
Author(s):  
Suresh Neethirajan ◽  
Bas Kemp

Artificial intelligence (AI), machine learning (ML) and big data are consistently called upon to analyze and comprehend many facets of modern daily life. AI and ML in particular are widely used in animal husbandry to monitor both the animals and environment around the clock, which leads to a better understanding of animal behavior and distress, disease control and prevention, and effective business decisions for the farmer. One particularly promising area that advances upon AI is digital twin technology, which is currently used to improve efficiencies and reduce costs across multiple industries and sectors. In contrast to a model, a digital twin is a digital replica of a real-world entity that is kept current with a constant influx of data. The application of digital twins within the livestock farming sector is the next frontier and has the potential to be used to improve large-scale precision livestock farming practices, machinery and equipment usage, and the health and well-being of a wide variety of farm animals. The mental and emotional states of animals can be monitored using recognition technology that examines facial features, such as ear postures and eye white regions. Used with modeling, simulation and augmented reality technologies, digital twins can help farmers to build more energy-efficient housing structures, predict heat cycles for breeding, discourage negative behaviors of livestock, and potentially much more. As with all disruptive technological advances, the implementation of digital twin technology will demand a thorough cost and benefit analysis of individual farms. Our goal in this review is to assess the progress toward the use of digital twin technology in livestock farming, with the goal of revolutionizing animal husbandry in the future.


2021 ◽  
Vol 4 (2) ◽  
pp. 36
Author(s):  
Maulshree Singh ◽  
Evert Fuenmayor ◽  
Eoin Hinchy ◽  
Yuansong Qiao ◽  
Niall Murray ◽  
...  

Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.


Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 483
Author(s):  
Nikola Žižlavská ◽  
Tomáš Mikita ◽  
Zdeněk Patočka

The article is on the effects of woody vegetation growing on the roadside on the temperature of the surface of cycle paths. The main hypothesis of the study is that vegetation has the effect of lowering the temperature of the surroundings in its shadow and thus improves the comfort of users of cycle paths in the summer months. The second hypothesis is to find out which type of road surface is most suitable for the thermal well-being of users. This goal was achieved by measuring the temperature of selected locations on cycle paths with different types of construction surfaces with nearby woody vegetation using a contactless thermometer over several days at regular intervals. The positions of the selected locations were measured using GNSS and the whole locality of interest was photographed using an unmanned aerial vehicle (UAV), or drone, and subsequently a digital surface model (DSM) of the area was created using a Structure from Motion (SfM) algorithm. This model served for the calculation of incident solar radiation during the selected days using the Solar Area Graphics tool with ArcGIS software. Subsequently, the effect of the shade of the surrounding vegetation on the temperature during the day was analysed and statistically evaluated. The results are presented in many graphs and their interpretation used to evaluate the effects of nearby woody vegetation and the type of road surface on the surrounding air temperature and the comfort of users of these routes. The results demonstrate the benefits of using UAVs for the purpose of modelling the course of solar radiation during the day, showing the effect of roadside vegetation on reducing the surface temperature of the earth’s surface and thus confirming the need for planting and maintaining such vegetation.


2016 ◽  
Vol 20 (4) ◽  
pp. 195-198 ◽  
Author(s):  
Richard Seymour ◽  
Michael Murray

Purpose There is increasing evidence that participation in various art forms can be beneficial for health and well-being. The purpose of this paper is to examine the impact of participating in a poetry reading group on a group of older residents of an assisted living facility. Design/methodology/approach Six poetry sessions, each on a different theme, were conducted with a group of volunteer participants. These sessions, those of pre- and post-study focus groups and interviews with the group facilitator and staff contact were audio-recorded. The transcripts of the recordings were then subjected to a thematic analysis. Findings Overall the participants were enthused by the opportunity to participate in the project and the benefits were confirmed by the support staff. In addition, reading poetry on particular themes promoted different types of discussion. Research limitations/implications The number of participants in this study was small and the study was conducted over a short period of time. Practical implications This paper confirms the impact of poetry reading for older people. The challenge is to explore this impact in more detail and over community as well as residential settings. Originality/value This paper is the first empirical report on the value of poetry reading for older people.


Author(s):  
Maja Bärring ◽  
Björn Johansson ◽  
Goudong Shao

Abstract The manufacturing sector is experiencing a technological paradigm shift, where new information technology (IT) concepts can help digitize product design, production systems, and manufacturing processes. One of such concepts is Digital Twin and researchers have made some advancement on both its conceptual development and technological implementations. However, in practice, there are many different definitions of the digital-twin concept. These different definitions have created a lot of confusion for practitioners, especially small- and medium-sized enterprises (SMEs). Therefore, the adoption and implementation of the digital-twin concept in manufacturing have been difficult and slow. In this paper, we report our findings from a survey of companies (both large and small) regarding their understanding and acceptance of the digital-twin concept. Five supply-chain companies from discrete manufacturing and one trade organization representing suppliers in the automotive business were interviewed. Their operations have been studied to understand their current digital maturity levels and articulate their needs for digital solutions to stay competitive. This paper presents the results of the research including the viewpoints of these companies in terms of opportunities and challenges for implementing digital twins.


2021 ◽  
pp. 1-7
Author(s):  
Nick Petro ◽  
Felipe Lopez

Abstract Aeroderivative gas turbines have their combustion set points adjusted periodically in a process known as remapping. Even turbines that perform well after remapping may produce unacceptable behavior when external conditions change. This article introduces a digital twin that uses real-time measurements of combustor acoustics and emissions in a machine learning model that tracks recent operating conditions. The digital twin is leveraged by an optimizer that select adjustments that allow the unit to maintain combustor dynamics and emissions in compliance without seasonal remapping. Results from a pilot site demonstrate that the proposed approach can allow a GE LM6000PD unit to operate for ten months without seasonal remapping while adjusting to changes in ambient temperature (4 - 38 °C) and to different fuel compositions.


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