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  1. To asset owners and managers, understanding how people move through and use the built environment is a high priority, enabling better, more user-focused decisions. However, many of the methods for getting these insights can feel invasive to users. The latest output from Digital Twin Journeys looks at how a researcher at the University of Cambridge has solved this problem by teaching a computer to see. Watch the video to learn more. Working from the University of Cambridge Computer Laboratory, Matthew Danish is developing an innovative, low-cost sensor that tracks the movement of people through the built environment. DeepDish is based on open-source software and low-cost hardware, including a webcam and a Raspberry Pi. Using Machine Learning, Matthew has previously taught DeepDish to recognise pedestrians and track their journeys through the space, and then began training them to distinguish pedestrians from Cambridge’s many cyclists. One of the key innovations in Matthew’s technique is that no images of people are actually stored or processed outside of the camera. Instead, it is programmed to count and track people without capturing any identifying information or images. This means that DeepDish can map the paths of individuals using different mobility modes through space, without violating anyone’s privacy. Matthew’s digital twin journey teaches us that technological solutions need not be expensive to tick multiple boxes, and a security- and privacy-minded approach to asset sensing can still deliver useful insights. To find out more about DeepDish, read about it here. This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge. It was enabled by the Construction Innovation Hub, of which CDBB is a core partner, and funded by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF).
  2. Motion sensors, CO₂ sensors and the like are considered to be benign forms of monitoring, since they don’t capture images or personal data about us as we move through the buildings we visit. Or at least, that’s what we want to believe. Guest blogger Professor Matthew Chalmers (University of Glasgow) helped develop a mobile game called About Us as part of the CDBB funded Project OAK. The game takes players through a mission using information from building sensors to help them achieve their aims — with a twist at the end. He writes about why we all need to engage with the ethics of data collection in smart built environments. Mobile games are more than just entertainment. They can also teach powerful lessons by giving the player the ability to make decisions, and then showing them the consequences of those decisions. About Us features a simulated twin of a building in Cambridge, with strategically placed CO₂ sensors in public spaces (such as corridors), and raises ethical questions about the Internet of Things (IoT) in buildings. The premise of the game is simple. While you complete a series of tasks around the building, you must avoid the characters who you don’t want to interact with (as they will lower your game score), and you should contact your helpers — characters who will boost your score. You can view a map of the building, and plan your avatar’s route to accomplish your tasks, based on which route you think is safest. On the map, you can watch the building’s sensors being triggered. By combining this anonymous sensor data with map details of which offices are located where, you can gather intelligence about the movements of particular characters. In this way, you can find your helpers and avoid annoying interactions. If you’ve avoided the bad characters and interacted with the good characters while completing your tasks, you win the game. However, a twist comes after you have finished: the game shows you how much could be inferred about your game character, from the exact same sensors that you had been using to make inferences about other characters. Every task in the game exposes some sensitive data about the player’s avatar, and reinforces the player’s uncomfortable realisation that they have exploited apparently neutral data to find and avoid others. What does this tell us about the ethics of digital twins? Our journeys through the built environment can reveal more than we intend them to, e.g. our movements, our routines, where we congregate, and where we go to avoid others. All this information could inadvertently be revealed by a building digital twin, even though the data used seems (at first glance) to be anonymous and impersonal. The game used CO₂ levels as an example of apparently impersonal data that, when combined with other information (local knowledge in this case), becomes more personal. More generally, data might be low risk when isolated within its originating context, but risk levels are higher given that data can be combined with other systems and other (possibly non-digital) forms of information. The Gemini Principles set out the need for digital twins to be ethical and secure, but About Us demonstrates that this can be surprisingly difficult to ensure. Collecting data through digital twins provides aggregate insights — that’s why they’re so useful — but it also creates risks that need ongoing governance. It’s vitally important that citizens understand the double-edged problem of digital twins, so that citizens are more able to advocate for how they want the technology to be used, and not used, and for how governance should be implemented. Gamification is now a well-established technique for understanding and changing user attitudes toward digital technology. About Us was designed to create a safe but challenging environment, in which players can explore an example of data that could be collected in distributed computing environments, the uses to which such data can be put, and the intelligence that can be gathered from resulting inferences. The ultimate purpose of Project OAK is to enable anyone concerned with how data is managed (e.g., data processors, data subjects, governance bodies) to build appropriate levels of trust in the data and in its processing. Only if we recognise the ethical and legal issues represented by digital twins can we start to give meaningful answers to questions about what good system design and good system governance look like in this domain. Information about this project is available on their GitHub page. This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge. It was enabled by the Construction Innovation Hub, of which CDBB is a core partner, and funded by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF). To join the conversation with others who are on their own digital twin journeys, join the Digital Twin Hub.
  3. Sensor technology has come a long way over the last 30 years, from the world’s first, bulky webcam at the University of Cambridge Computer Science Department to near ubiquitous networks of sleek sensors that can provide data at an unprecedented volume, velocity and quality. Today, sensors can even talk to each other to combine single points of data into useful insights about complex events. The new webcomic ‘Coffee Time’ by Dave Sheppard, part of the Digital Twin Journeys series, tells the story of this evolution and what it means for what we can learn about our built environment through smart sensors. Starting with a simple problem – is there coffee in the lab’s kitchen? – researchers in the early 1990s set up the world’s first webcam to get the information they wanted. Today, people in the Computer Lab still want to know when the coffee is ready, but there are more ways to solve the problem, and new problems that can be solved, using smart sensors. Smart sensors don’t just send information from point A to point B, providing one type of data about one factor. That data needed to be collated and analysed to get insights. Now sensors can share data with each other and generate insights more instantaneously. The West Cambridge Digital Twin team at the computer lab have looked at how specific sequences of sensor events can be combined into an insight that translates actions in the physical world into carefully defined digital events. When someone makes coffee, for example, they might turn on a machine to grind the coffee beans, triggering a smart sensor in the grinder. Then they’d lift the pot to fill it with water, triggering a weight sensor pad beneath to record a change in weight. Then they would switch the coffee machine on, triggering a sensor between the plug and the outlet that senses that the machine is drawing power. Those events in close succession, in that order, would tell the smart sensor network when the coffee is ready. These sequences of sensor triggers are known as complex events. Using this technique, smart sensors in the built environment can detect and react to events like changes in building occupancy, fires and security threats. One advantage of this approach is that expensive, specialist sensors may not be needed to detect rarer occurrences if existing sensors can be programmed to detect them. Another is that simple, off-the-shelf sensors can detect events they were never designed to. As the comic points out, however, it is important to programme the correct sequence, timing and location of sensor triggers, or you may draw the wrong conclusion from the data that’s available. Something as simple as wanting to know if the coffee is ready led to the first implementation of the webcam. Digital twin journeys can have simple beginnings, with solving a simple problem with a solution that’s accessible to you, sparking off an evolution that can scale up to solve a wide range of problems in the future. You can read and download the full webcomic here. You can read more from the West Cambridge Digital Twin project by visiting their research profile. This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge. It was enabled by the Construction Innovation Hub, of which CDBB is a core partner, and funded by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF).
  4. By 2050, an estimated 4.1 million people will be affected by sight loss in the UK, making up a portion of the 14.1 million disabled people in the UK. How might digital twins create opportunities for better accessibility and navigability of the built environment for blind and partially sighted people? A new infographic presents a conception of how this might work in the future. In their work with the Moorfields Eye Hospital in London, the Smart Hospitals of the Future research team have explored how user-focused services based on connected digital twins might work. Starting from a user perspective, the team have investigated ways in which digital technology can support better services, and their ideas for a more accessible, seamless experience are captured in a new infographic. In the infographic, service user Suhani accesses assistive technology for blind people on her mobile phone to navigate her journey to an appointment at an eye hospital. On the way, she is aided by interoperable, live data from various digital twins that seamlessly respond to changing circumstances. The digital twins are undetectable to Suhani, but nevertheless they help her meet her goal of safely and comfortably getting to her appointment. They also help her doctors meet their goals of giving Suhani the best care possible. The doctors at the eye hospital are relying on a wider ecosystem of digital twins beyond their own building digital twin to make sure this happens, as Suhani’s successful journey to the hospital is vital to ensuring they can provide her with care. Physical assets, such as buildings and transport networks, are not the only things represented in this hypothetical ecosystem of connected digital twins. A vital component pictured here are digital twins of patients based on their medical data, and the team brings up questions about the social acceptability and security of digital twins of people, particularly vulnerable people. No community is a monolith, and disabled communities are no exception. The research team acknowledges that more research is needed with the user community of Moorfields to understand the variety of needs across the service pathway that digital twins could support. As such, developers need to consider the range of users with different abilities and work with those users to design a truly inclusive ecosystem of digital twins. The work by the Smart Hospitals research team raises wider questions about the role of digital technology both in creating more physical accessibility in the built environment but also potentially creating more barriers to digital accessibility. It is not enough to create assistive technologies if not everyone can – or wants to – have access to those technologies. ‘The role of digital technologies in exacerbating potentially digital inequalities is something that needs to be looked at from a policy perspective, both at the hospital level, but also more generally, from a government Department of Health perspective,’ says Dr Michael Barrett, the project’s principal investigator. Dr Karl Prince, co-investigator, reflects that, ‘The traditional questions when it comes to this type of technology are raised as to: do they have access to equipment, and do they have the technical ability?’ The lesson is that you can build digital twins that create a better experience for people if you design digital systems from the perspective of an ecosystems of services, with input from users of that ecosystem. Through exciting case studies, the project raises vital questions about digital ethics and the potentially transformative effects of digital twins on the physical built environment. To read the infographic in detail, click here. You can read more from the Smart Hospitals project by visiting their research profile page. This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge. It was enabled by the Construction Innovation Hub, of which CDBB is a core partner, and funded by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF). To join the conversation with others who are on their own digital twin journeys, join the Digital Twin Hub.
  5. When we travel by train, we expect that we will arrive at our destination safely and on time. Safety and performance of their service network is therefore a key priority for Network Rail. Our latest video in the Digital Twin Journeys series tells the story of how researchers have inherited two intensively instrumented bridges and are transforming that high volume and velocity of data into a digital twin showing the wear and pressures on the bridges, as well as other information that can help the asset owners predict when maintenance will be required and meet their key priorities. Remote monitoring has several benefits over using human inspectors alone. Sensors reduce the subjectivity of monitoring. Factors such as light levels, weather and variations in alertness can change the subjective assessments made by human inspectors. They may also be able to identify issues arising before visual inspection can detect them by monitoring the stresses on the bridge. A human inspector will still be sent to site to follow up on what the remote sensing has indicated, and engineers will of course still need to perform maintenance. However, remote monitoring allows the asset owners to be smarter about how these human resources are deployed. One important insight for Network Rail is based on more accurate data about the loads the bridges are experiencing, and the research team have developed a combination of sensors to make a Bridge Weigh-In-Motion (B-WIM) Technology. As shown in the video, a combination of tilt sensors, bridge deformation and axle location sensors to calculate the weight of passing trains. As the accuracy of weight prediction data is impacted by changes to ambient humidity and temperature, sensors were added that detect these factors as well. Accelerometers were added to calculate rotational restraints at the boundary conditions to improve the accuracy of weight predictions and cameras were installed so that passing trains can be categorised by analysing the video footage.   The digital twin of the Staffordshire Bridges centres on a physics-based model for conducting structural analysis and load-carrying capacity assessments. The site-specific information, such as realistic loading conditions obtained by the sensors, will be fed into the physics-based model to simulate the real structure and provide the outputs of interest. A digital twin replica of the structure will be able to provide bridge engineers with any parameter of interest anywhere on the structure, including in non-instrumented locations. All of the sensors on these bridges produce a high volume of data at a high velocity. Without data curation, we could easily be overwhelmed by the volume of data they produce, but the research team is learning to narrow down to managing the right data in ways that provide the right insights at the right time. Working with Network Rail, this project will demonstrate the use of real-time data analytics integrated with digital twins to provide useful information to support engineers and asset managers to schedule proactive maintenance programmes and optimise future designs, increasing safety and reliability across their whole portfolio of assets. You can read more from the Staffordshire Bridges project by visiting their research profile. This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge. It was enabled by the Construction Innovation Hub, of which CDBB is a core partner, and funded by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF). To see more from the Digital Twin Journeys series, see the homepage on the CDBB website.
  6. A new infographic, enabled by the Construction Innovation Hub, is published today to bring to life a prototype digital twin of the Institute for Manufacturing (IfM) on the West Cambridge campus. Xiang Xie and Henry Fenby-Taylor discuss the infographic and lessons learned from the project. The research team for the West Cambridge Digital Twin project has developed a digital twin that allows various formats of building data to function interoperably, enabling better insights and optimisation for asset managers and better value per whole life Pound. The graphic centres the asset manager as a decision maker as a vital part of this process, and illustrates that each iteration improves the classification and refinement of the data. It also highlights challenges and areas for future development, showing that digital twin development is an ongoing journey, not finite destination. The process of drawing data from a variety of sources into a digital twin and transforming it into insights goes through an iterative cycle of: Sense/Ingest - use sensor arrays to collect data, or draw on pre-existing static data, e.g. a geometric model of the building Classify - label, aggregate, sort and describe data Refine - select what data is useful to the decision-maker at what times and filter it into an interface designed to provide insights Decide – use insights to weigh up options and decide on further actions Act/Optimise - feed changes and developments to the physical and digital twins to optimise both building performance and the effectiveness of the digital twin at supporting organisational goals. Buildings can draw data from static building models, quasi-dynamic building management systems and smart sensors, all with different data types, frequencies and formats. This means that a significant amount of time and resources are needed to manually search, query, verify and analyse building data that is scattered across different databases, and this process can lead to errors. The aim of the West Cambridge Digital Twin research facility project is to integrate data from these various sources and automate the classification and refinement for easier, more timely decision-making. In their case study, the team has created a digital twin based on a common data environment (CDE) that is able to integrate data from a variety of sources. The Industry Foundation Classes (IFC) schema is used to capture the building geometry information, categorising building zones and the components they contain. Meanwhile, a domain vocabulary and taxonomy describe how the components function together as a system to provide building services. The key to achieving this aim was understanding the need behind the building management processes already in place. This meant using the expertise and experience of the building manager to inform the design of a digital twin that was useful and usable within those processes. This points to digital twin development as a socio-technical project, involving culture change, collaboration and alignment with strategic aims, as well as technical problem solving. In the future, the team wants to develop twins that can enhance the environmental and economic performance of buildings. Further research is also needed to improve the automation at the Classify and Refine stages so they continue to get better at recognising what information is needed to achieve organisational goals. You can read more from the West Cambridge Digital Twin project by visiting their research profile. This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge. It was enabled by the Construction Innovation Hub, of which CDBB is a core partner, and funded by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF). To see more from the Digital Twin Journeys series, see the homepage on the CDBB website.
  7. Digital twins enable asset owners to use better information at the right time to make better decisions. Exploring the early stages of a digital twin journey – understanding the information need – are Staffordshire Bridges researcher Dr Farhad Huseynov and Head of Information Management Henry Fenby-Taylor. Network Rail manages over 28,000 bridges, with many being more than 150 years old. The primary means of evaluating the condition of the bridges is through two assessment programmes; visual examination and Strength Capability Assessment. Every conceivable form of bridge construction is represented across Network Rail’s portfolio of assets, from simple stone slabs to large estuary crossings, such as the Forth Bridge. Managing a portfolio of this diversity with frequent and extensive assessments is a considerable challenge. Condition monitoring The current process for condition monitoring involves visual examination by engineers and takes place every year, along with a more detailed examination every six years. The visual inspection provides a qualitative outcome and does not directly predict the bridge strength; it is conducted to keep a detailed record of visible changes that may indicate deterioration. The load-carrying capacity of bridges is evaluated every five years through a Strength Capability Assessment, conducted in three levels of detail: Level 1 is the simplest, using safety assumptions known to be conservatively over-cautious (i.e. 1-dimensional structural idealisation). Level 2 involves refined analysis and better structural idealisation (i.e. grillage model). This level may also include the use of data on material strength based on recent material tests, etc. Level 3 is the most sophisticated level of assessment, requiring bridge-specific traffic loading information based on a statistical model of the known traffic. Understanding the information and insights that asset owners require helps shape what data is needed and how frequently it should be collected – two essential factors in creating infrastructure that is genuinely smart. During the discussions with Network Rail, the research team found that Level 3 assessment is only used in exceptional circumstances. This is because there is no active live train load monitoring system on the network; hence there is no site-specific traffic loading information available for the majority of bridges. Instead, bridges failing Level 2 assessment are typically put under weight and/or speed restrictions, reducing their ability to contribute to the network. This means that there is potentially huge value in providing Level 3 assessment at key sites with greater frequency. Digital twins for condition assessment The Stafford Area Improvement Programme was setup to remove a bottleneck in the West Coast Main Line that resulted in high-speed trains being impeded by slower local passenger and goods trains. To increase network capacity and efficiency, a major upgrade of the line was undertaken, including the construction of 10 new bridges. Working with Atkins, Laing O’Rourke, Volker Rail and Network Rail, a research team including the Centre for Smart Infrastructure and Construction (CSIC), the Centre for Digital Built Britain (CDBB) and the Laing O’Rourke (LOR) Centre for Construction Engineering and Technology at the University of Cambridge is collaborating with Network Rail to find a digital twin solution for effective condition monitoring. Two bridges in the scheme were built with a variety of different sensors to create a prototype that would enable the team to understand their condition, performance and utilisation. Both bridges were densely instrumented with fibre optic sensors during construction, enabling the creation of a digital twin of the bridges in use. The digital twin’s objective is to provide an effective condition monitoring tool for asset and route managers, using the sensor array to generate data and derive insights. Identifying challenges and solutions Meetings were held with key stakeholders including route managers and infrastructure engineers at Network Rail to learn the main challenges they face in maintaining their bridge stock, and to discover what information they would ideally like to obtain from an effective condition monitoring tool. The team liaised closely with the key stakeholders throughout to make sure that they were developing valuable insights. Through discussions with Network Rail about the team’s work on the two instrumented bridges in the Staffordshire Bridges project the following fundamental issues and expected outcomes were identified: A better understanding of asset risks: How can these be predicted? What precursors can be measured and detected? A better understanding of individual asset behaviour Development of sensor technology with a lifespan and maintenance requirement congruent with the assets that they are monitoring How structural capability be calculated instantly on the receipt of new data from the field Development of a holistic system for the overall health monitoring and prognosis of structures assets Realistic traffic population data in the UK railway network. (Can this be predicted with sufficient accuracy for freight control and monitoring purposes?) To address these issues, the team instrumented one of the bridges with the following additional sensors, which, combined, produce a rich dataset: Rangefinder sensors to obtain the axle locations. A humidity and temperature sensor to improve the accuracy of weight predictions against variations in ambient temperature. Accelerometers to calculate rotational restraints at the boundary conditions and therefore improve the accuracy of weight predictions. Cameras to categorise passing trains. Data from these sensors feeds into a finite element model structural analysis digital twin that interprets the data and provides a range of insights about the performance of the bridge and the actual strain it has been put under. Applying insights to other bridges Significantly, information from the instrumented bridge sites is relevant to adjacent bridges on the same line. Having one bridge instrumented on a specific route would enable Level 3 assessment for other structures in their portfolio and those of other asset owners, including retaining walls, culverts, and other associated structures. Just as the new bridges relieved a service bottleneck, digital twins can resolve procedural and resource bottlenecks by enabling insights to be drawn about the condition of other assets that weren’t instrumented. This is a valuable insight for those developing their own digital twins, because given that one bridge is instrumented it follows that where trains cannot have diverted course, then any other bridges along that same stretch of track will be undergoing the same strain from the same trains. This insight will enable teams implementing sensors to be able to efficiently implement a sensor network across their own assets. One of the outcomes of the Staffordshire Bridges project is development towards a holistic approach for the overall health monitoring and prognosis of bridge stocks. Such changes improve workforce safety by reducing the requirement for costly site visits while maintaining a healthy bridge network. You can read more from the Staffordshire Bridges project by visiting their research profile. This research forms part of the Centre for Digital Built Britain’s (CDBB) work at the University of Cambridge. It was enabled by the Construction Innovation Hub, of which CDBB is a core partner, and funded by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF). To keep up with the Digital Twin Journeys project, check out the Digital Twin Journeys home page.
  8. Digital twins can help organisations achieve various goals. In some cases, the end goal is for buildings and infrastructure to last longer, use less energy, and be safer. In others, it is enhancing the lives of people who interact with the built environment and its services. As highlighted by the Gemini Principles, these are not mutually exclusive aims, so wherever you are on your digital twin journey, it is important to consider other perspectives on the hybrid digital and physical systems you create. How will your digital twin fit into a wider ecosystem that provides services to all kinds of people? How will your asset’s performance impact the wider built environment and those who need to navigate it? Whose lives will be better if you share data securely and purposefully. In the first output from the Digital Twin Journeys series, the team working on the Smart Hospital of the Future research project, enabled by the Construction Innovation Hub, shared case studies from two smart hospitals and reflect on the innovations they saw during the COVID-19 pandemic. In this two video mini-series, the research team shares insights about how existing digital maturity enabled these hospitals to respond to the pandemic in agile ways, transforming to a hybrid physical and digital model of care distributed across multiple sites. They also explored how individual asset digital twins fit into a wider landscape of ecosystem services, guiding how we approach interoperability to achieve better outcomes. These insights inform the way we think about the role of digital twins in the smart built environments of the future. Dr Nirit Pilosof reflects that, ‘Digital twin as a concept can promote the design of the new system, the design process of the built environment and the technologies, but also really help operate… the hybrid models looking at the physical and virtual environments together.’ If health care is enabled by connected digital twins, how could the design of hospitals – and whole cities – change? In the videos, the team also discusses the limitations and ethics of services enabled by digital data and the use of digital technologies to improve staff safety, from isolated COVID wards to telemedicine. They frame service innovation as an iterative and collaborative process, informed by the needs of digital twin users, whether those are the asset owners and operators, or the people benefitting from the services they provide. According to project co-lead Dr Michael Barrett, ‘The people who need to drive the change are the people who are providing the service.' After the COVID crisis, we can better recognise what we have learned from implementing digital services at scale, as more people than ever have relied on them. The team reflect that having the right people in the right roles enabled the smart hospitals in these cases to transform their services rapidly in response to the need. The same human and organisational infrastructure that is creating the smart hospital of the future is also needed to create the flexible, responsive built environments of the future. Digital Twin Journeys can start from the perspective of available technology, from a problem-solving perspective, or from the perspective of users experiencing a service ecosystem. The smart hospitals project demonstrates the value of the latter two approaches. Hospital staff were instrumental in shaping the digitally-enabled service innovation to keep them safe and offer better services on and offsite, but project co-lead Dr Karl Prince points out how people accessing those services have to navigate a variety of different services in the built environment to get there. As we begin to connect digital twins together, we need to consider not just our own needs but the needs of others that digital twins can address. For more on this project, including links to their publications, see the team’s research profile on the CDBB website. Keep up with the Digital Twin Journeys series on the CDBB website or here on the Digital Twin Hub blog.
  9. hello as a masters student currently I'm doing my thesis related to digital twin, and I just proposed a cloud based tool that can control and monitor IoT device through cloud using BIM Model File. I've tested the tool and it is now working but my worry is which standard or ontology that states the relation between BIM and IoT device specially for Controlling? thanks in advance
  10. Morning All, Currently investigating a case for a Digital Twin concept - is there any guidance relating to the structure of the data to align up to a more national structure? Any useful guidance to help the beginnings of this case move in the right direction? Thanks, Lewis
  11. Predicting the future is something intrinsic to the human condition. Whether we are thinking about lunch, retirement, or developing a world-shaking invention like the iPhone. What if the biggest barrier to realising the potential of innovation is not technology, but belief? Predictions of the future from the 1950s included people flying around in their own helicopters to do their daily chores. Ignoring the acceptability of helicopters powering up and blowing the contents of everyone’s gardens everywhere, this future could have happened. There is no technological boundary to everyone having a helicopter in their garden or on the street. However, it was believed correctly that flying machines are extremely dangerous and that their ownership and piloting should be rigorously controlled. That then, is why that idea never took off. It may be tempting to scoff at this suggestion entirely, but there are now several places only accessible by plane and even a housing estate in Florida where every resident owns a plane as their primary means of transportation. If you would like your own home with an attached hanger, check them out here. The motor vehicle faced very similar push back from the populace and the media when they were introduced. They were smelly, loud and dangerous, not to mention costly. However, once the car had been accepted as an ordinary part of everyday life, the risk increased as they became faster. Cars were now so intrinsically embedded in our society that the idea of removing them had become unconscionable. Digital twins will undergo the same process of becoming publicly acceptable as the question of risk continues to arise. The idea of a building or a motorway self-managing might seem like a stretch to the layperson, but this has already begun with Building Management Systems and Smart Motorways. It is important that we acknowledge the ability of these systems to fail and make sure that we have integrated fail safes that perform the equivalent role of airbags in cars. Similarly, the idea of the smartphone underwent a similar process of becoming acceptable to the general public not so long ago. They were already present in our society when the iPhone was released, but it was the iPhone that made the concept of the smartphone mainstream. Was it that the technology was superior? In part perhaps. What really made the difference was that Apple sold us a lifestyle choice. That narrative around the iPhone, its versatility thanks to the app store and its good looks were what really made the difference. The technology already existed, but it had never been brought together effectively as a whole product. The app store enabled owners to customise their experience and created a platform for services that today is worth billions of dollars. The Digital Twin is to the Internet of Things what the iPhone was to the smartphone. The concept of connecting things to the internet makes sense and smart speakers and smart devices have had some success. However, the concept of the internet of things is nebulous at its core. Its story raises questions, we connect things to the internet. That’s it. It’s up to the developers of technology to take that idea and turn it into real products. You cannot procure an internet of things; you cannot own one. A digital twin however is procurable. It is also neatly definable to the layperson. You have a physical asset and a digital representation of that asset; these twins communicate with each other so that you can manage your assets more effectively. You can see the digital twin, make changes to it and they happen in the physical twin. This simplicity of narrative is exactly what sold the first iPhone. Your email, music, calls and the internet are all in one place. It’s a very simple idea to communicate despite it being a very complex product. If you compare this sales pitch with the O2 XDA, the rival smartphone at the time, you see a focus on technical specifications. The advert did not answer how this product will make your life easier or better, instead it focused on power and speed, which for an enthusiast (such as myself, who owned an O2 XDA) is very enticing, but for the wider population made little or no headway. It is the narrative of the Digital Twin and the National Digital Twin that makes the difference, having prepared the groundwork for public acceptability with the Gemini principles of purpose, trust and function we have learnt the lessons of the past when adopting an innovation so that we do not need to sacrifice the individual’s rights and safety for the general public good as we did for cars. Similarly, with the story of the National Digital Twin we have learnt the lesson of the iPhone, that innovation must be tailored to people’s lifestyles, that is not simply a technology for the sake of it, but something that will enhance our lives in an easily understandable way. We have a challenge then, if the brand is as important as the technology, how do you think Digital Twins should be marketed? What should be the story we tell?
  12. Mark Coates

    Demonstrator project

    One for the calendar :- we recently did a demonstrator project with Microsoft’s Azure Digital Twins team for the Build Conference which will be featured as a Deep Dive on Microsoft’s Channel 9 IoT Show on August 3rd. https://channel9.msdn.com/Shows/Internet-of-Things-Show/Deep-Dive-Integrating-3D-Models-and-IoT-data-with-iTwin-and-Azure-Digital-Twins In this session we will demonstrate an application that combines 3D models, 2D maps, and reality mesh into a single environment for visualisation 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. It would be great to get feed back from as many as possible once the show has aired
  13. I'm thinking of promoting our HE Ontology in the hopes of a) being able to explain to normal people what we're doing (and why) and b) hopefully securing some interest and feedback from the wider community and ideally other road operators. It's also been a useful opportunity to condense and reiterate to myself what on earth I've been doing with my life. Anyway, before I fire this into the ether, I thought it might be useful to get some feedback. The draft article is here should you be interested... https://www.linkedin.com/pulse/draft/AgGQLPmRvH_kkgAAAXMLChJcc3Cpv-7oz99HbLpUZI7xX7d0XAb4vwRXGvs2CeEVWQ8VnAE Thanks in advance!
  14. andy cooney

    Digital Twin and IoT

    Sort of 2 questions What piece of IoT kit would make your Digital Twin more effective What IoT have you found that transforms your knowledge of business (helps you build a better DT) So what IoT would you like, what have you found/used?
  15. Peter Lee

    DTs for Smart Cities

    This webinar may be of interest from Smart Cities World: Leverage digital twins to optimise municipal operations Find out how Gwinnett County (USA) is unifying IT/OT/IoT systems to provide complete visibility to all municipal data. Using a Digital Twin of their municipal operations allows faster, more informed decisions and speeds crisis response while lowering their total cost to operate their services. https://www.smartcitiesworld.net/webinars/webinar-centralized-command-and-control-of-multi-site-municipal-water-operations
  16. Aerospace was one of the first industries to develop digital twins. This academic paper helps to identify the initial research papers around the concept, and the scope of Digital Twins within several sectors as they emerged https://www.sciencedirect.com/science/article/pii/S2351978917304067
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