John Williams, World Coal, July 1 2019
Original article published on World Coal.
GE Research: Flexible Plants for More Renewable Intensive Grids
This article written by John Williams for World Coal, makes some interesting observations about using Digital Twins to make coal power more sustainable. This is through their predictive technology that allows data sources to interoperate and predict whether a fault might occur, before it has even happened. This is done by creating a Digital Twin of the coal power plant and allowing it to intelligently interact with other twins within a single, interoperable ecosystem. This allows data to be accessed and shared both internally and externally to the power plant, meaning information such as weather and temperature, which may affect the coal power production, is easily accessible through a single feed of information, and can be used to predict whether a fault might occur.
Using this same technology, similarly to our work with BAM Nuttall and Cranfield University with The Learning Camera, you can then monitor elements of the coal power plant, and the intelligent technology will alert you to an issue when one arises. This diminishes the fear of human error and sometimes dangerous environments that checks could be conducted in.
Find out more about Digital Twin technology and how it can help to not just make coal power a more sustainable and efficient source of energy, but how it can help any business or company to increase efficiency and overall productivity, on our website.
Joseph Chukwube, ReadWrite, June 28 2019
Original article published on ReadWrite.
Electronic Design is Utilizing AI-Enabled Solutions to Render Top-Grade Service
This article written by Joseph Chukwube for ReadWrite explores AI solutions for the engineering industry, specifically in Electronic Design companies, commenting on customer engagement, how companies are able to communicate between themselves and their machines, and predictive technologies. However, while the majority of the points Chukwube makes are true and align with our values at Iotic, many of them need to be taken further.
1. Harnessing Effective Data
Chukwube here, states that 'data, no matter how voluminous, is practically useless when not properly organized and analyzed.' This is true, but how should this be tackled? He touches on the use of Digital Twins and how they can be used to monitor data and predict problems before they arise, but this doesn't reach the full limits of how Digital Twins can be used to help a company's data.
Digital Twins do more than just monitor systems to predict issues and analyse data, they have the ability to gather and share information, internally and externally to a business. This allows a user to gain information that is entirely relevant to them and their company, without having to lift a finger, and is how the predictive qualities of Digital Twins are enabled. Twins of individual assets, whether this is a single engine or an entire construction site, can be created, which produce a feed of information about the asset, as well as potential factors that may affect its functioning, such as weather conditions, wind speeds, or delivery information. Digital Twins make this all possible, and more, today.
2. Faster and More Efficient Communication
While it is true that technology exists today that can bridge a gap between a business and their machines, predicting issues before they occur, this technology can be - and has been - developed even further. These predictions are based on real life data, and new technology means that this data can be collected and collated all into one place, so information can be gained with ease and with minimal effort from the user. Therefore, this not only gives businesses the ability to communicate with their machines and gain information and data quickly and easily, but also allows them to collate all the information they receive into one single location, giving a single source of truth that is more easily utilised. It also enables a business to communicate with data sources outside of their immediate company, to gain additional information that gives them 'the flexibility to meet up with demands, prevent downtime losses and control cost'.
3. Customer Engagement
Agreed, 'customer engagement is crucial' in order to maintain efficiency and stability within a business, and chatbots are a start at improving customer service and ensuring that efficiency and customer satisfaction remain high. But wouldn't it be great if companies were able to more easily and quickly access important and relevant data for their customers? Technology exists and is being utilised today that provides companies with a single source of truth, allowing data and information to be more easily accessed and utilised to solve customer enquiries. Find out more about a real use case of this technology in our collaboration with Rolls Royce Power Systems, and discover how this technology can be useful to you, your business, and your customers.
4. Quality Checks and Control
Ensuring that quality checks are conducted to the highest of standards is important to ensure the smooth running of a site, these checks require accuracy and can also sometimes be dangerous, so relying on human checks alone can be risky. Therefore, a practical solution such as a 'high resolution camera' that 'not only views but processes the information gathered such that defects are automatically flagged for correction', could be the answer. Iotic have developed intelligent technology in partnership with BAM Nuttall and Cranfield University, called The Learning Camera, that does exactly this.
5. Implementation of Virtual Assistants
Quality checks are an example of a job within a company that is time consuming, sometimes dangerous, and often repetitive. Therefore, if technology exists today to assist with these kinds of tasks, why wouldn't we jump at the chance? Intelligent technology can not only do the odd job that Chukwube describes, but it can help increase efficiency and productivity hugely throughout a company, as it frees up time for individuals to undertake other jobs. This includes tasks like quality and Health & Safety checks, as well as the everyday running of the business, as data is much more easily accessible, quickly and with complete relevance to each specific situation. This technology exists today to increase business efficiency and free people from time consuming and sometimes dangerous tasks.
6. Predictive Maintenance
3D generated models were only the beginning of predictive technologies and how they may help to detect issues with assets and products. Digital Twin technology can provide accurate, real time information that can help companies to predict factors that may influence the development of a project or that may affect a specific asset. A Digital Twin is not a 3D model of something, as many believe it to be, it is instead a virtual copy of a particular asset, whether this is a person, an engine, a car, or an entire building site. This Digital Twin is then able to interoperate with other twins within one ecosystem, gaining information that is entirely relevant to the user's needs, without them having to monitor or continuously programme information into it. A river of news can then be created which provides the user with any piece of information that could want to know about this specific asset, as long as it is relevant to their specific needs. This technology is available right now, and is helping companies to improve in productivity, customer service, cost effectiveness, and overall company efficiency.
Intelligent technology exists today and can not only help the Engineering Industry, and more specifically Electronic Design companies, but can help any business no matter how large or small. This is in the form of Digital Twins which have the ability to do all of the above, within one interoperable ecosystem, without the need to adopt a multitude of technologies and without creating complexity within your business. They provide answers to all your business problems, quickly, easily and effectively, with minimal effort and time from the user. As Chukwube agrees, you should consider joining the revolution, for fear of missing out on all this technology has to offer you. Discover more on our website.
Jan Rowell, Inside HPC, June 28 2019
Original article published in Inside HPC.
Advancing Manufacturing with Simulation Based Digital Twins
This article, written by Jan Rowell from Scientific Computing World for Inside HPC, eloquently explores simulation focused digital twins and real use cases within the manufacturing industry. The article also looks into ways digital twins can be used outside the manufacturing industry, and for more than just simulation of a physical asset.
Intelligent digital twins are being used today, both to simulate real life assets and predict factors that may affect them, as well as to interoperate with other twins, internally and externally to a business, in order to aid these predictions and discover information that may affect their real world counterparts.
These twins are accessible to you, right now. Discover more on our website.
Bhaskar Roy, Forbes, June 19 2019
Original article published in Forbes.
Why Digital Transformation Isn't Happening - - And How You Can Change That
This article written for Forbes by Bhaskar Roy, explains true problems that enterprises face when attempting to successfully digitally transform themselves, and potential ways of solving these. However, we think it can be taken further. What do 'technology investments with the future in mind' look like and how can these solve enterprises' digital transformation problems?
Roy makes excellent points about why businesses are failing to digitally transform themselves, however some of these need to be explored further. Yes, it is easy to underestimate 'the damage complex processes can do, both to your digital transformation goals and to overall productivity', but what if this complexity was removed?
Part of the reason that enterprises are failing at successful digital transformation is the fact that on average, they are utilising '1,935 apps... a 15% increase compared to 2017'. The perception individuals have about digital transformation being down to them spending ridiculous amounts of money and adopting multiple different apps and technologies, is flawed, as Roy agrees. Exploring this further reveals the true issue with digital transformation, that by adhering to this mindset, companies are creating complexity for themselves, as their data is disparate and confined to a multitude of different apps and silos that are difficult to manage.
The removal of this complexity with a single technological solution that collates all a company's data and allows it to intelligently communicate with each other, as well as one that enables information to be gathered and shared with external organisations, could be the answer. This would enable a business to utilise its data more effectively and being to digitally transform itself.
While complexity is the main issue encountered by businesses, Roy suggests that a true solution to all business problems would be for companies to adopt 'a combination of business, process and technology', which to a certain extent is true, but is not an entire solution. A technological solution is still possible, while still accounting for the business and the process elements that are so important to a company's development. Technology that is centred around a users specific needs; one that is scalable and can be built around the business, could be the true answer. This keeps the business' main interests central, and also means technology can be adopted with process and future processes in mind, as it allows for any changes the company may encounter, whether these are developments or setbacks.
According to Roy, 'even the best technology can't make up for complicated, difficult to execute processes', but we think it can. A single technological solution could be the answer to successful digital transformation; a virtual interoperable ecosystem with a future focus. An environment that is entirely secure, scalable, and able to be built around you and your company's specific needs. Discover more on our website.
'Human buy-in' needed for digital twin deployment
Professional Engineering, Institution of Mechanical Engineers, July 2 2019
Originally Published by Professional Engineering in Institution of Mechanical Engineers
Faced with increased competition in asset data management, Rolls-Royce Power Systems (RRPS) realised that it needed to change the way its client base was served.
It appeared that what was needed was a technology solution, in the form of a virtual representation of physical systems. But, the outcome also called for a complete strategic rethink at management level.
"The issue was that we didn't see our products the way our customers do," says Sean Gigremosa. "We saw data that was stored in different systems and our focus was on those silos. We saw the world based on our technology and process, infrastructure and delivery methodology." The conceptual shift put in place by RRPS was to put "what matters to customers at the centre of what we do".
Practically, this meant the installation of asset-focused digital twins providing a single access point for the data needed by service managers to resolve customer service issues and deliver systems insights. To do this, RRPS harnessed digital twin technology from Iotic, to provide a virtual composite of the entirety of an asset's data and controls, "securely and meaningfully, while interacting with other twins, to provide a single source of truth that helps suppliers become service providers and customers to become partners".
This benefits the client in three ways. First, potential problems can be identified more promptly, leading to faster issue resolution. The second is quality, with Gigremosa explaining that the implementation of digital twins, "means that we see not only each customer's point of view, but can collectively gain insight across a customers assets enabling us to improve our products". Third is the provision of detailed insight to the customer, which can anticipate problems before they arise, with the result that there is reduced downtime.
For all the technology, to achieve these goals there needed to be human buy-in. Gigremosa says that if he could pick one word to define how success was achieved, it is involvement. "Agile development focuses on the user, so we started with our service management personnel, involving the team, testing and validating at every stage," he says. "We ran a design thinking process to understand our customer needs, Ultimately, agility depends on people. Being agile has put the customer at the heart of our everyday conversations." Which is more than simply predicting their requirements: "It's really about including the customer in the discussion, so they can tell you what they want."
This is where Gigremosa points out that it's important to draw distinctions between business, digital and process transformations. While business transformation is a common goal, and digital transformation - in this case, the implementation of digital twins - is what needs to be done to achieve this, it is the area of process transformation that can create roadblocks, because "you're asking users to do new things in new ways, and disrupting downstream services. Key to the RRPS implementation of Iotic is that the process is "additive and complementary to existing workflows". The user experience is enhanced in such a way that disruption is kept to a minimum, making acceptance of, and involvement in, the new landscape "easier for everyone".
"The main driver for change is the environment we find ourselves in," says Gigremosa. Because technology is moving "so fast, start-ups and more agile companies are now able to compete with larger organisations. Think about Amazon," he says, "that was at first only an online bookseller. But, due to agility and innovation, it has become one of the largest and most successful companies in the world."
NEWS: Learning camera project is developing ai - enabled tech to boost uk construction industry productivity
Learning Camera project is developing AI - enabled tech to boost UK construction industry productivity
Cranfield University, 26th June 2019
Originally Published by Cranfield University.
Researchers from Cranfield University are working with BAM Nuttall and Iotic, to develop an artificial intelligence-enabled safety board monitoring system for the UK construction industry. Funded by Innovate UK, The Learning Camera project aims to improve safety, while reducing the number of health and safety-related tasks carried out by construction staff, in order to improve productivity.
The project is using a combination of technology concepts including the Internet of Things, computer vision, Semantic Web, machine learning and cloud technologies, to develop self-learning technology capable of monitoring and analysing various scenarios on construction sites.
The UK construction industry is said to have poor productivity in comparison to other sectors - in part due to ever-changing project environments and large amounts of regulation when it comes to health, safety and environmental issues. While this highly-regulated approach is currently wholly necessary, it is hoped that the new technology will reduce the burden on staff - in terms of both tasks and resources - meaning more of their time can be spent on tasks directly impacting the build, therefore increasing productivity while maintaining the same level of safety standards, The Learning Camera project will focus on developing a safety board monitoring system, which automatically alerts staff if any safety equipment is used or missing.
Dr Yifan Zhao, Lecturer in Image and Signal Processing and Degradation Assessment at the Through-life Engineering Service Institute at Cranfield University, believes this is a great opportunity to apply artificial intelligence technologies to a traditional industry. Dr Zhao said: "Using The Learning Camera, construction sites will be better equipped to manage and deliver projects. It also helps to promote the need for the construction industry to attract talent with skills in software and hardware development, in order to tackle the much-publicised poor productivity of the industry."
Colin Evison, Head of Innovation at BAM Nuttall, said: "This is a real opportunity to explore how we can make our construction projects smarter by the adoption and development of technology solutions that are not traditionally available in the construction industry. The use of tools such as The Learning Camera will enable out people to focus more of their efforts on the actual delivery of projects, with the knowledge that it will notify them automatically if their intervention is required. In addition, by creating new additive business relationships with organisations such as Iotic Labs Limited and Cranfield University, we are able to have access to talent and resources in different sectors."
Sophie Peachey, Head of Customer Success at Iotic, said: "The application of Digital Twin technology within The Learning Camera allows us to broker access to a potentially increasing number of data sources and controls to perfect the accuracy of the algorithms used in solution. these algorithms must be able to interpret differences correctly and instigate appropriate actions to make The Learning Camera a solution that people trust. You can see how this could apply to different situations in which people have to balance the importance of knowing that something is there, has changed, or is working, against the cost of their time in checking. While this is not restricted to construction, we are very excited by the impact this could have on productivity and in providing construction staff with a safe working environment.
Find out more about The Learning Camera project.
The Rise of the Digital Twin in the AEC Industry
Ali Nicholl, PBC Today, May 7 2019
Originally published on PBC Today
Digital continues to disrupt and excite the construction industry in equal measure. The cavalcade of terms and technologies - Big Data, data warehousing, ubiquitous connectivity, artificial intelligence, augmented reality, and so on (and on) - continues unabated, promising increased efficiencies, greater insights and improved service delivery. However, the value of this technology remains only a fraction of what it could be.
As Stefan Webb from Future Cities Catapult (now part of the Connect Places Catapult) highlighted in his article for PBC Today, back in 2017, data, especially within cities and infrastructure, remains a largely untapped resource.
The greatest barrier to liberating value is that data and controls are traditionally locked within platforms, systems, and silos. New technologies promising greater flexibility, agility, and transformation, are too often isolated from incumbent platforms, systems, and databases. The existing silos of data and controls are unmanageable. Legacy systems, which should be a competitive advantage, exist in parallel to the new developments rather than informing and complementing them. Traditional IT solutions that present single-vendor solutions are seen as inflexible and expensive. According to a recent survey by the SAP User Group, DSAG, 62% of companies described their progress on Digital Transformation Projects, seen as critical to business, as 'Not Far' due to ever expanding scope and cost.
Are Digital Twins a Solution?
As frustrations with the challenge of siloed data and hidden value continues, we have seen the launch of a number of initiatives to take the systemic barriers to further development.
The 2017 National Infrastructure Commission (NIC) report, 'New Technology Study: Data for the Public Good' looked at the opportunities that innovation enables and how open data sharing can support those opportunities. It made the recommendation that there should be a creation of "a digital twin of Britain's infrastructure". An outcome of that recommendation has been the creation, by the Centre for Digital Built Britain and their partners, of a set of principles behind creating an ecosystem of connected Digital Twins, the Gemini Principles.
Elsewhere we have seen Greater Cambridgeshire Partnership and Telensa announce the creation of a city-wide digital twin, with the aim of designing better city infrastructure, delivering more efficient city services.
Digital Twins individually and federated together are increasingly being seen as a solution to the need for interoperability between data sets, silos and services, but there remains a lot of confusion as to what a Digital Twin is and, as importantly, what it isn't!
What is a Digital Twin?
A significant element of the ambiguity around Digital Twins and their value is owing to the emphasis on visualisation rather than virtualisation. In many sectors, Digital Twins have come to be seen as 3D Models, reporting tools and, at their best, constructs for simulation and emulation. They tend to be representations of a specific geography, asset, system, or process: distinct and separate. While many are static, little more than CAD/CAM models, increasingly there have been improved virtualisation visualisations, which use live data alongside historical interoperating platforms and sources. Once again in Cambridge, we've seen innovative mapping Start-Up, SenSat, demonstrate, in collaboration with Mott MacDonald and Safehouse Sensors, what can be achieved with new technology to map, visualise, and interrelate multiple data sources and sets.
We can however go further. At Iotic, we define a Twin as a comprehensive, interoperable version of anything, all its data, all its controls, through its whole life. The addition of controls, as well as data, is vital. The great power of Digital Twins comes not from what they can show us, but how they can securely and meaningfully interact with each other. The ecosystem of connected Digital Twins highlighted in the Gemini Principles or, as I presented at a TechUK event on this subject earlier in the year, can create not a National Digital Twin, but a nation of digital twins.
A real twin is one that can interact, interrelate and behave in a digital environment as its twinned counterpart does in the real world. It is a semantically defined virtual counterpart to anything which can securely interact and be federated together across organisations and supply chains, enabling a single source of truth (we aren't copying data into platforms, or creating new data lakes), enhanced monitoring, prognostics, new services and solutions that would not otherwise be possible.
By creating Digital Twins of anything and everything - every source and consumer of data and controls - what we are really doing is creating a machine-readable world: a world that can harness the power of Machine Learning, Artificial Intelligence, algorithms, business process rules, and security and access control profiles and platforms.
These twins provide security to our vital assets and infrastructure not only through the insight information and management they enable but through their very existence. Twins are by their very definition, not the thing itself. This abstraction from the real to the virtual digital space, enables interoperability between twins, brokered interactions between sources and consumers of data across companies, buildings, supply chains, and the wider world without the need to provide direct access to any of the 'real' asset platforms, processes or systems.
There remains of course a role for representations and renders of interoperable twins. 3D models can be powerful tools presenting insights and helping partners to see opportunities to collaborate, highlight bottlenecks and enable others to visualise assets, systems, and whole processes powerfully.
But they are just one manifestation of a twin: a view of the data and controls that a twin has. In our experience, different users, organisations within a supply chain and stakeholders can, and will increasingly, have their own visualisation, dashboards, and models of the same twins, interacting with what is important to them and interoperating with the other twins in their world. A Site Manager may want a twin of an individual construction site, showing live deliveries. Meanwhile, an Area Manager may want to access the performance of equipment across sites, making his or her twins the individual pieces of equipment.
From Disruptor to Disrupted
As organisations start to adopt real Digital Twins, they are liberated from viewing data and controls based on technology, which is traditionally a view of the world determined by an organisation's internal processes, databases, tech providers and silos of information. Instead, they can take the perspective of a customer's view of the world, federating twins around what matters to them - their site, building, office, city, network, service agreement, or entire organisation.
Redefining around what matters to you, or more pertinently to customers or stakeholders, additionally creates the flexibility to adopt new technologies and approaches while maintaining downstream services, leveraging existing process, and benefitting from technologies that have previously been confined to proof of concept or innovation activities.
Adoption and transformation is coming: BAM Nuttall the civil engineering contractor, has been working with Iotic to start creating twins of its assets, supply chain, and partner information by interrelating point solutions, third-party information and innovation programs and develop an interoperable ecosystem that delivers benefits within projects, across organisations and to their partners and stakeholders.
The power of Digital Twins is in their ability to interact meaningfully with each other and to create ecosystems where data and controls from anything, owned by anyone, can safely interoperate. The ecosystems will grow and evolve over time, powering multiple use cases, solutions and services, and working across technology providers and legacy systems. With real Digital Twins, we can start anywhere and grow exponentially, flexibly evolving the federated and composite twins of what we need now and what we will need in the future, adapting to new technology and changing requirements, and delivering outcomes we cannot yet even envisage.
Davey Winder, The Times. December, 19 2018
Iotic helps make dumb machines smart by creating intelligent digital twins of connected IoT devices and the wider data estate using a cloud-hosted middleware space. Last year, Gartner heralded digital twins as a top-ten strategic technology trend. What they deliver is something often regarded as impossible: IoTsecurity coupled with open interoperability. Imagine different platforms, services, networks and devices securely interrelating with public and private third-party sources. Robin Brattel, Iotic’s chief executive, explains that this patented technology “enables secure programmatic interoperability of data and controls for interactions across organisations, supply chains and silos”.
Unsurprisingly, it is garnering support in the high value manufacturing and construction sectors.
“It is the digital twins that interrelate, with actual devices, data sources and equipment never exposed,” says Mr Brattel. “These interactions are securely brokered with granular access control; the source or control is always in charge adaptively choosing when and to whom they are visible.” What this means is that by using an intelligent abstraction layer, Iotic can overcome the well-documented challenges of IoT security that have led to the creation of data siloes and vertical technology stacks that previously limited return on investment.
“Our technology is being adopted by market-leading global enterprises to achieve the impossible,” Mr Brattel concludes. These abstracted digital twins become a single source of truth, enabling solutions from simulation models to reality and minimum viable product to scale.
Data, Data Everywhere
The data-powered IoT market in 2020 is estimated at anywhere in the $300 billion (Gartner) to $7.1 trillion (IDC) range with a substantial rise in the storage and analysis of data held in Big Data silos to exceed 40 zetabytes by 2020 (GP Bullhound). In reality the market is an order of magnitude greater as these estimates do not include derived things. Connecting what we encounter daily further multiplies this figure many fold, before even greater scaling driven by derived data addressing business, government and societal needs.
Because no business is an island the narrative needs shifting from big data storage, and associated communication networks, to collaborative use and reuse of information internally and externally. The ability to share and interrelate data and things is at the heart of the Internet of Things. When things connect to share data and silos are opened, we can create communities of unrelated things that can interact. Generate solutions and products with automated genres of service, operations and logistics. Disrupt business models and transform consumer expectations.
When can we start?
We don’t need to agree to one platform in order to progress. We don’t need to wait for 5G, bigger databases, new sensors, or better analytical techniques. The traditional structured inter-relationships between citizens, SMEs, enterprises, infrastructures, utilities, healthcare, transportation, cities, regions and governments are increasingly at risk of becoming redundant, we need to act.
There is no tipping point. We can today improve efficiency, effectiveness, and quality of life through greater collaboration, sharing, and innovation.
What are the emergent trends in data sharing?
The data and information that we need already exists, with more being created all the time. That information has a value currently, but increasingly we will see value creation through its reuse and recycling. A simple example is a temperature gauge. The data from your temperature gauge is only of value to you when you look at it, but what if that information, and its accuracy was continuously available and shared. How could servicing, repairs, and reliability be improved?
Upcycling in the IoT is an additive process. Combining things in previously unimagined ways will generate benefits for the data owners, end users, and the innovators who create the transformative relationships.
Interactions not interfaces
As the number of connect things, their data – direct and derived - rapidly outstrips the global population it is clear that interactions between things can not rely on individuals and interfaces.
Programmatic creation of relationships between data, things, systems learning, artificial intelligence, inspired industrial design and a host of additional tools, will be needed to bring us closer to David Rose’s vision of “technology that atomizes, combining itself with the objects that make up the very fabric of daily living.”
Communities not consumers
As enterprises realise that the value of data comes not from hoarding, but from sharing, we will see this reflected in innovative services. Users will enhance their experience by sharing information with self-selected communities - just like the internet. Allowing data- and information-rich communities to self organise and propagate.
Flexibility and expandability will become a core feature of successful technology. Expectations are changing, solutions will fail where overly proscriptive uses and interactions prevent users from curating their own experiences and sharing that curation with others, who can, in turn, expand, modify, combine and personalise their experience.
Data sharing enables collaborative, creative communities of individuals and organisations to not do things differently but do different things. We have the technology now to break down our data silos and work together to develop new business and creative models, service lines, delivery methodologies, and transform our experiences. Why not make yours an enchanted life?
NOTE: A VERSION OF THIS BLOG WAS ORIGINAL PUBLISHED ON TECHUK'S WEBSITE (www.techuk.org) AS PART OF DATA DRIVEN ECONOMY WEEK.
Creating a model of the world
The first Emperor of China, Qin Shi Huang, (pictured right) ordered an elaborate burial chamber constructed on a scale almost unimaginable today. Around 700,000 men spent almost four decades building life-size models of warriors, farmers, officials, carts, horses, roads, farms, towers and palaces, as well as mercury simulations of the Yangtze and Yellow Rivers. These flowed mechanically to a mercury sea under a vaulted ceiling resplendent with depictions of heavenly constellations. The Emperor believed that if his model of the world were accurate enough, he would be able to continue to rule the empire in the afterlife. Understanding and seeing all as it happened in the real world, he would have omnipotence over every corner of the empire and realise his claim on universal and eternal rule as the “First August Thearch” (or god-ruler). His dream was one of total and enduring control through a complete understanding of everyone and everything within the empire.
Many Emperors shared the same dream of immortality through the construction of an enduring dynamic model of the world that was interchangeable with the real world: a facsimile so precise that to have mastery of the model was to have dominion over the world.
World building today
Transporting these emperors to the present, they would surely see progress in their dream of modelling the world, but have we managed to achieve the ultimate objective of creating a true facsimile of the world as it is? Some might say that Big Data has made available so much data that we must now be able to know the world, but the aim of Big Data is primarily to mine history, not to reveal the now. Big Data doesn’t provide dynamic behavioral responses. The Emperors’ desire to model the world as it is happening is proving more intractable.
The contemporary analogues of Emperors are decision-makers in business. They want to know what assets their companies possess - where assets may well be digital as well as physical, now that sources of data are of at least equal value as real things. They want to be able to see the state of things as they are so they can make decisions. They want a single source of truth. They want to run “what-if…?” scenarios to see which decisions make the biggest positive or the smallest negative impact. In short, they need a dynamic model of the real world. The contemporary analogues of the Emperor’s 700,000 army of builders and scores of overseers and bureaucrats are the data scientists, analysts and apps developers who must build these dynamic models.
Could “Digital Twins” be the solution to ancient Emperors’ and their modern-day counterparts’ dreams? Digital Twin is a buzz-phrase that is currently climbing the hype cycle, but what actually is a true Digital Twin? Many people apply the phrase to CAD/CAM 3D models of buildings, engines, components, etc., but these are static models of things that don’t have any dynamic data and don’t exhibit the behavior of the thing they claim to model. The model of the building doesn’t show how the building interacts with people waiting to use the lifts; the model of the engine doesn’t show how it works when some components are worn. These models don’t meaningfully interact with the world or each other.