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  1. A new whitepaper explores how digital twin technology can play its role in the future of a service-oriented environment – highlighting the potential benefits and opportunities as well as the challenges that can arise when implementing innovative digital solutions. The paper focuses on Moorfields Eye Hospital, leading provider of specialist eye health services in the UK and world centre of excellence for ophthalmic research and education, as it designs and constructs a smart hospital of the future. A Cambridge-based research team worked with multiple stakeholders – asset owners, management, service providers, and clinicians – to better understand how digital transformation of the built environment could create new opportunities to enhance inclusion and improve services provided to patients in new smart hospitals, and how the shift to the uptake of digital technologies around telemedicine and AI will impact service provision and service transition. The research paper uses Moorfields Eye Hospital as a case study, taking a service-oriented perspective to explore the potential of digital twin technology in addressing specific needs and pain points of users, and the subsequent implications for new models of service delivery. It will help Moorfields and similar organisations in their search for newer and better navigational guidance solutions to help visually impaired patients journey to and from the hospital, and to help provide an improved digitally enabled service experience once they reach the building itself. According to project lead Professor Michael Barrett, 'this new digitally-enabled assistive technology of visually-impaired navigation, which is still a burgeoning area, can help to ease anxiety, making visually-impaired navigation and travelling easier.' The research team considers the Moorfields journey, exploring patient-care opportunities and noting the challenges of transitioning the current service into the future service. Physical relocation of any hospital is an enormous task and the move of an eye hospital where the visually impaired patient community has a more complex relationship with the built environment and digital technologies will present additional challenges. In addition, current services provided to patients by Moorfields will need to be integrated with and transitioned onto the future service model and ecosystem. What are digital twins? Digital twins are realistic digital representations of physical assets, for example, a digital representation of an aeroplane that can be used to monitor and predict performance, feeding out insights and interventions. These insights lead to better interventions and unlock real-world value from assets through financial savings, improved performance and services, and better outcomes for society. As highlighted by the Gemini Principles, a high-quality and accurate digital twin depends on three components: the quality and quantity of data used for the model, the fidelity of the algorithms that constitute the model, and the validity of the assumptions/competence of the model and the quality of final output’s presentation. 10933 DigitalTwin_WhiPap_int_v7.pdf
  2. Hi All, At Hadean we’ve been working with a predictive digital twin for epidemiology, and modelling the spread of COVID-19. Part of our work has leveraged the Hadean platform to quickly calibrate our model so infection dynamics match the real-world’s. We’ve written up the work that we have done so far in a blog page that I wanted to share: https://hadean.com/modelling-an-evolving-pandemic-keeping-your-digital-twin-calibrated-and-in-sync-with-the-data/ We used Approximate Bayesian Computation, ABC, to ensure that an initial variant had the same infectivity as that found from official case statistics, and then recalibrated as a new strain emerged. For epidemiology, in-particular, we’ve found that it’s critical to keep a model up-to-date with the real world so that predictions are meaningful at point-of-use. I’m interested in how others keep their predictive digital twins up-to-date. Do you calibrate and synchronise your digital twins? If so, how? If not, why not? Ping me an email if you’d like a chat - daniel.gorringe@hadean.com
  3. Osama Zaki

    Connected Digital Things

    Several Terms such as Digital Ecosystem, Digital Life, Digital World, Digital Earth have been used to describe the growth in technology. Digital twins are contributing to this progress, and it will play a major role in the coming decades. More digital creatures will be added to our environments to ease our life and to reduce harms and dangerous. But can we trust those things? Please join the Gemini call on the 29th of March; Reliability ontology was developed to model hardware faults, software errors, autonomy/operation mistakes, and inaccuracy in control. These different types of problems are mapped into different failure modes. The purpose of the reliability ontology is to predict, detect, and diagnose problems, then make recommendations or give some explanations to the human-in-the-loop. I will discuss about these topics and will describe how ontology and digital twins are used as a tool to increase the trust in robots. Trust in the reliability and resilience of autonomous systems is paramount to their continued growth, as well as their safe and effective utilisation. A recent global review into aviation regulation for BVLOS (Beyond Visual Line of Sight) with UAVs (Unmanned Aerial Vehicles) by the United States Congressional Research Office, highlighted that run-time safety and reliability is a key obstacle in BVLOS missions in all of the twelve European Union countries reviewed . A more recent study also highlighted that within a survey of 1500 commercial UAV operators better solutions towards reliability and certification remain a priority within unmanned aerial systems. Within the aviation and automotive markets there has been significant investment in diagnostics and prognostics for intelligent health management to support improvements in safety and enabling capability for autonomous functions e.g. autopilots, engine health management etc. The safety record in aviation has significantly improved over the last two decades thanks to advancements in the health management of these critical systems. In comparison, although the automotive sector has decades of data from design, road testing and commercial usage of their products they still have not addressed significant safety concerns after an investment of over $100 Billion in autonomous vehicle research. Autonomous robotics face similar, and also distinct, challenges to these sectors. For example, there is a significant market for deploying robots into harsh and dynamic environments e.g. subsea, nuclear, space etc which present significant risks along with the added complexity of more typical commercial and operational constraints in terms of cost, power, communication etc which also apply. In comparison, traditional commercial electronic products in the EEA (European Economic Area) have a CE marking, Conformité Européenne, a certification mark that indicates conformity with health, safety, and environmental protection standards for products sold within the EEA. At present, there is no similar means of certification for autonomous systems. Due to this need, standards are being created to support the future requirements of verification and validation of robotic systems. For example, the BSI standards committee on Robots and Robotic Devices and IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems (including P7009 standard) are being developed to support safety and trust in robotic systems. However, autonomous systems require a new form of certification due to their independent operation in dynamic environments. This is vital to ensure successful and safe interactions with people, infrastructure and other systems. In a perfect world, industrial robotics would be all-knowing. With sensors, communication systems and computing power the robot could predict every hazard and avoid all risks. However, until a wholly omniscient autonomous platform is a reality, there will be one burning question for autonomous system developers, regulators and the public - How safe is safe enough? Certification infers that a product or system complies with legal relevant regulations which might slightly differ in nature from technical or scientific testing. The former would involve external review, typically carried out by some regulators to provide guidance on the proving of compliance, while the latter usually refers to the reliability of the system. Once a system is certified, it does not guarantee it is safe – it just guarantees that, legally, it can be considered “safe enough” and that the risk is considered acceptable. There are many standards that might be deemed relevant by regulators for robotics systems. From general safety standards, such as ISO 61508, through domain specific standards such as ISO 10218 (industrial robots), ISO 15066 (collaborative robots), or RTCA DO-178B/C (aerospace), and even ethical aspects (BS8611). However, none of those standards address autonomy, particularly full autonomy wherein systems take crucial, often safety critical, decisions on their own. Therefore, based on the aforementioned challenges and state of the art, there is a clear need for advanced data analysis methods and a system level approach that enables self-certification for systems that are autonomous, semi or fully, and encompasses their advanced software and hardware components, and interactions with the surrounding environment. In the context of certification, there is a technical and regulator need to be able to verify the run-time safety and certification of autonomous systems. To achieve this in dynamic real-time operations we propose an approach utilising a novel modelling paradigm to support run-time diagnosis and prognosis of autonomous systems based on a powerful representational formalism that is extendible to include more semantics to model different components, infrastructure and environmental parameters. To evaluate the performance of this approach and the new modelling paradigm we integrated our system with the Robotics Operating System (ROS) running on Husky (a robot platform from Clearpath) and other ROS components such as SLAM (Simultaneous Localization and Mapping) and ROSPlan-PDDL (ROS Planning Domain Definition Language). The system was then demonstrated within an industry informed confined space mission for an offshore substation. In addition, a digital twin was utilized to communicate with the system and to analysis the system’s outcome.
  4. Intelligent infrastructure is a new trend that aims to create a work of connected physical and digital objects together in industrial domains via a complex digital architecture which utilises different advanced technologies. A core element to this is the intelligent and autonomous component. Two-tiers intelligence is a novel new concept for coupling machine learning algorithms with knowledge bases. The lack of availability of prior knowledge in dynamic scenarios is without doubt a major barrier for scalable machine intelligence. The interaction between the two tiers is based on the concept that when knowledge is not readily available at the top tier, the knowledge base tier, more knowledge cab be extracted from the bottom tier, which has access to trained models from machine learning algorithms. It has been reported that the need for intelligent autonomous systems – based on AI and ML – operating in real-world conditions to radically improve their resilience and capability to recover from damage. It has been expressed the view that there is a prospect for AI and ML to solve many of those problems. A claim has been made that a balanced view of intelligent systems by understanding the positive and negative merits will have impact in the way they are deployed, applied, and regulated in real-world environments. A modelling paradigm for online diagnostics and prognostics for autonomous systems is presented. A model for the autonomous system being diagnosed is designed using a logic-based formalism, the symbolic approach. The model supports the run-time ability to verify that the autonomous system is safe and reliable for operation within a dynamic environment. However, during the work we identified some areas where knowledge for the purpose of safety and reliability is not readily available. This has been a main motive to integrate ML algorithms with the ontology. After decades of significant research, two approaches to modelling cognition and intelligence have been investigated and studied: Networks (or Connectionism) and Symbolic Systems. The two approaches attempt to mimic the human brain (neuroscience) and mind (logic, language, and philosophy). While the Connectionism approach considers learning as the main cognitive activity, the Symbolic Systems are broader, they also look at reasoning (for problem solving and decision making) as the main cognitive activity besides learning. Although, learning isn’t the focus of Symbolic Systems, powerful – but limited – methods were applied, such as ID3 (define) and its different variations and versions. Furthermore, the Connectionism approach is concerned with data while Symbolic Systems are concerned with knowledge. Psychologists have developed non-computational theories of learning that have been the source of inspiration for both approaches. Psychologists have also differentiated between different types of learning (such as learning from experience, by examples, or a combination of both). In addition, unlike in animals (it is difficult to test intelligence in non-human creatures), human psychologists have also produced methods to test human intelligence. Mathematicians have also contributed statistical methods and probabilistic models to predict behaviour or to rank a trend. The subject of Machine Learning (ML) is the bag for all algorithms used to mine data in the hope that we can learn something useful from the data, which is usually distributed, structured or unstructured, and of significant size. Although there are several articles on the differences and similarities between Artificial Intelligence and Machine learning, and articles on the importance of the two schools, there are no real or practical attempts that have been reported in the literature to practically use or combine the two approaches together. Therefore, this is an attempt to settle the ongoing conflicts between the two existing thoughts for modelling cognition and intelligence in humans. We argue that two-tiers intelligence is a mandate for machine intelligence as it is the case for human. Animals, on the other hand, have one-tier intelligence, which is the intrinsic and the static know-how. The harmony between the two tiers can be viewed from different angles, however they complement each other, and both are mandatory for human intelligence and hence machine intelligence. The lack of availability of prior knowledge in dynamic complex systems of is without doubt a major barrier to scalable machine intelligence. Several advanced technologies are used to control, manipulate, and utilise all parts whether software, hardware, mobile assets such as robots, or even infrastructure assets such as wind turbines. The two-tiers intelligence approach will enhance the learning and knowledge sharing process in a setup that heavily relies on some sort of symbiotic relationships between its parts and the human operator.
  5. A4I round 6 launches tomorrow, 29/07/2021. This funding is aimed at SMEs looking to solve analysis or measurement problems. Below are some example ideas which might be eligible for A4I funding, and relevant to Digital Twin development: Collection of real-time data Accessing new sensing technologies, analytical tools & methodologies for input into Digital Twins Data analysis techniques Developing new analytical techniques or systems to improve existing Digital Twins e.g. data quality verification, or generating new insights using AI. Measurement of Digital Twin performance Note that this is a fast tracked funding round so please pay close attention to the closing dates. Link to the full information on the A4I funding: https://apply-for-innovation-funding.service.gov.uk/competition/975/overview For projects requiring Hartree Centre capabilities (AI, Data Science, HPC) you can also contact me directly to discuss the project and funding submission process. Examples of previous A4I projects: https://www.a4i.info/a4i_case_studies/data-performance-consultancy-limited/?bpage=1 https://www.a4i.info/a4i_case_studies/riskaware/?bpage=1 Summary:
  6. until
    The London Digital Twin Research Centre would like to extend an invitation to all the Digital Twin researchers and enthusiasts from industry and academia to attend our annual 2021 workshop which is held online on June 4th, 2021. This virtual “Workshop on Transforming Industry and Society with Digital Twins” brings together experts from industry and academia to share their valuable insights regarding the adoption of the Digital Twin technology across different industries, from structural health monitoring, pandemic management, smart campuses through to health and wellbeing. The domains covered in this event provide opportunities and research challenges that the future maturation of digital twin technology demands. The virtual workshop represents an excellent opportunity for networking for Digital Twin enthusiasts to share ideas for future developments in digital twins. Programme Free Eventbrite registration: Link Time/date: 10am-3:30pm on Friday 4th June 2021 DT workshop_June2021.pdf
  7. Construction sites generate tons of data on a daily basis, most of which can be used to drive tangible business benefits for a company’s bottom line. Join this free webinar on 19th March at 3.30pm to hear how Project Controls which are often cited as creating particular issues at site level, can be managed better. How can leveraging technology help you overcome the challenges of data silos, data analysis and how organisations can move along the path to AI from the ground up. https://attendee.gotowebinar.com/register/1956726490522384911
  8. The use of Robotics and Artificial Intelligence (RAI) has been recognised by the UK government in its relationship with the published Industrial Strategy and the Industrial Strategy Challenge Fund (ISCF) to deliver growth and sustain its economic wealth. https://attendee.gotowebinar.com/register/3615339780733212942 Artificial intelligence (AI) and robotics are a very powerful combination for automating regular tasks inside and outside of the project setting. In recent years, AI has become an increasingly common presence in robotic solutions in other sectors (outside of Engineering in Capital Projects), introducing flexibility and learning capabilities in previously rigid applications. While AI is still in the early stages, it has so far been a transformative technology for some applications in the manufacturing sector, although there are many that have yet to feel the impact. In today’s global manufacturing sector, there are a few ways in which Robotic Applications and Artificial Intelligence could be deployed. Everything from assembly through the customer service, the possibilities are endless. Join us on 26th to hear on a few examples of how massive improvements are possible.
  9. until
    Join us on Friday at 3.30pm to hear on the power of visual data, third-party APIs and IoT integration, and how a system can provide complete situational awareness and project visibility to all key stakeholders in major capital projects. Hear how project teams can visualize the entire life of their CapEx project, and even beyond as a live asset. Enabling cross-organisational and cross-vendor workflows, planning of future worksite activities and tracking project milestones allows for big data to be managed in a slick, intuitive and digestible way. A system that allows users to visualize both in 2D and 3D their site/facility and combine IoT and GIS functionalities together to become the "single source of truth". https://attendee.gotowebinar.com/register/4510351039689315851
  10. until
    Elements within the Capital project world could be transformed through the use of DfMA (off site manufacturing)….. If we take housing as an example, the target set by government in 2015 (1.5 million house strategy) has not been achieved The benefits of DfMA linked with the advantages of autonomous assembly lines have been widely published. If these advantages are correct, why is the uptake so low? Is there a chicken and egg scenario? You need the use of DfMA to increase to gain capital investment (autonomy investment), you need investment to enable a greater output and wider use? Where are we heading? Join us to hear our panel of Industry experts including government that will discuss the current thoughts and ideas around this subject and what we can do to improve uptake
  11. until
    Premieres: August 3rd, 9am-10am PT with live Q&A and on-demand following the event. [Click Here for iCal Invite] Join us live to learn and ask questions! Deep Dives are interactive technical live and on-demand events for developers, architects, or anyone building IoT solutions. Learn how to get started with iModel.js, an open-source programming library from Bentley Systems to create living digital twins: https://www.imodeljs.org/ Microsoft engineers and guest speakers do technical deep dives about a new feature or scenario. List of all upcoming Microsoft IoT Deep Dives: https://aka.ms/iotshow/deepdive Learn more about Integrating 3D Models and IoT data In this session we will demonstrate an application that combines 3D models, 2D maps, and reality mesh into a single environment for visualization. Within that environment we will demonstrate a live, real time, seamless visualization of IoT data streams. Next we will walk through the architecture that enables the application. We will show how we have mapped the IoT data to the assets within the digital twin. And we will show how to keep the digital twin in step with engineering changes. This is done by automating the generation of the Digital Twin Description Language (DTDL) .JSON. Bentley's iTwin platform and iModel.js open-source programming library provide powerful capabilities for aggregating 3D, 2D, reality data and other sources to link with IoT data for a "single pane of glass" visualization, analytics, and simulation so users can make more effective decisions in a timely manner. By integrating the iTwin platform with Azure Digital Twins and other Azure IoT services, Bentley and Microsoft are making it easier for developers, integrators, and customers to build digital twins of their infrastructure assets. Guest Speakers: Josh Schifter – Sr. Software Development Manager, Bentley Systems Roop Saini – Software Developer, Bentley Systems Deep Dive Host: Pamela Cortez - Azure IoT Senior PM Resources: Get started with iModel.js: https://www.imodeljs.org/ Learn more about iTwin: https://www.bentley.com/en/products/product-line/digital-twins/itwin Details on how to ask questions during the live event Add the Deep Dive invite to your calendar or come back to this page when the premiere airs and go to https://aka.ms/deepdive/digital-twins-live (link will be redirected to YouTube before the event) for the streaming event to view the video and chat box Make sure to sign in to YouTube to be able to ask questions to our engineers and talk to others on the chat! Have an idea for an IoT Deep Dive? Tweet #IoTDeepDive @AltaOhms with your request!
  12. Alexandra Robasto

    Digital Twins: The Next Phase of the AI Revolution?

    until
    The Turing Talk: Part of the IET EngTalk Series and BCS Lecture Series The idea of an Intelligent Digital Avatar conjures up many images from a complete virtual world that one can safely define, develop and play in to rogue robots running amok and destroying mankind. The reality is much less dramatic but no less far reaching and exciting. This year’s Turing Talk will be delivered by Mark Girolami; an academic statistician and the Sir Kirby Laing Professorship of Civil Engineering at the University of Cambridge. Mark will discuss Digital Twins and chart their history to present day technological capability, looking at some of the advances being made and the opportunities along with the open challenges faced to realise the potential of Digital Twins. Link to the event
  13. Alexandra Robasto

    Digital Twins: The Next Phase of the AI Revolution?

    until
    The Turing Talk: Part of the IET EngTalk Series and BCS Lecture Series The idea of an Intelligent Digital Avatar conjures up many images from a complete virtual world that one can safely define, develop and play in to rogue robots running amok and destroying mankind. The reality is much less dramatic but no less far reaching and exciting. This year’s Turing Talk will be delivered by Mark Girolami; an academic statistician and the Sir Kirby Laing Professorship of Civil Engineering at the University of Cambridge. Mark will discuss Digital Twins and chart their history to present day technological capability, looking at some of the advances being made and the opportunities along with the open challenges faced to realise the potential of Digital Twins. Link to the event
  14. until
    The idea of an Intelligent Digital Avatar conjures up many images from a complete virtual world that one can safely define, develop and play in to rogue robots running amok and destroying mankind. The reality is much less dramatic but no less far reaching and exciting. This year’s Turing Talk will be delivered by Mark Girolami; an academic statistician and the Sir Kirby Laing Professorship of Civil Engineering at the University of Cambridge. Mark will discuss Digital Twins and chart their history to present day technological capability, looking at some of the advances being made and the opportunities along with the open challenges faced to realise the potential of Digital Twins. Link to the event
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