Amidst digital transformation, the concept of a “digital twin” has emerged as a revolutionary tool in the world of infrastructure. It refers to the digital replica of physical assets, processes, people, places, systems, and devices that can be used for various purposes. A digital twin comprises a virtual model that accurately reflects a physical object. It can continuously learn and update itself to reflect the near real-time status and the operating conditions of the physical system it replicates. Updates can come from various sources, including a human expert familiar with the system’s operation Embedded sensors within the large physical system can provide information about the system and its operating environment. Additionally, updates can be obtained from a connected artificial intelligence (AI) and machine learning (ML) system. The technology also leverages other advanced technologies such as internet of things (IoT) and cloud.
Blending in with AI and ML
Advancements in AI and ML are playing an increasingly important role in making digital twins more powerful and capable. With AI and automated learning, a digital twin can dynamically improve the quality and validity of predictions under various operational scenarios. When ML-based models integrate into the digital twin, designers can scale these models to large networks with tens or hundreds of nodes and represent diverse real-world situations. A digital twin offers the advantage of generating synthetic data with the required parameterisations while replicating previous tests. It is important that ML training generates similar datasets and has the informational complexity to fully access underlining algorithms. A physical system cannot perform all these tasks because of constraints such as limited time, resources, or tractability. If one intends to widely deploy AI and ML, this type of network digital twins will be crucial.
Industry use cases
Digital twins find many applications across various industries. The technology can yield benefits when applied on the manufacturing floor. With the use of virtual copies of equipment and spare parts, workers and managers can simulate several processes, conduct experiments, identify issues, and achieve desired results without risking or damaging physical assets. Four key technologies are needed to develop and deploy digital twins at scale – data from physical systems, IoT connectivity, modelling methods, and at-scale computing. Each of these technologies has been developed in parallel over the past few years.
In the consumer-packaged goods manufacturing industry, digital twins automatically provide comprehensive information about equipment or product performance without manual intervention. Given the current computing capabilities, factories can quickly analyse the data provided by the physical twin, using advanced ML algorithms, and convert it into actionable insights. Before the inception of digital twins, such a level of performance management and control in manufacturing was practically unattainable.
During the product life cycle, digital twins play a crucial role in reducing cost and time as customers incorporate them into design and test workflows. Industry pioneers are constantly exploring new ways to import and export digital twin data as well as aggregate and share specific models, schemes, and data across the product spectrum. They are also developing bionic digital twins or integrated digital twins to represent complex network systems that incorporate live hardware operational devices or hardware emulators as part of the overall digital twin.
Moreover, design verification (simulation) and hardware validation account for nearly two-thirds of product development time, an area where industries are working to improve. There are several similarities between these two activities, and both strive to characterise a design based on a set of requirements. One activity occurs within the virtual digital twin domain, and the other takes place within the physical test domain. It is possible to connect these tasks through digital threads, allowing the digital twin to deliver tangible benefits.
In the transportation sector, the metaverse enables intelligently networked and integrated multimodal transportation networks. It leverages the digital twins of physical infrastructure such as airports and major roadways. Users can plan and execute journeys across multiple transportation modes in an increasingly more cost-effective and efficient manner as these services become part of the larger metaverse. The metaverse could also be used to create virtual transportation hubs, where users can access a range of transportation options, such as trains, buses, and taxis. These virtual hubs could be accessed through virtual reality technology and could potentially be used to plan and book real-world transportation.
For example, the Kempegowda International Airport, owned and operated by Bengaluru International Airport Limited, entered the metaverse space by launching the first phase of BLR Metaport. Developed in collaboration with Amazon Web Services and Polygon, BLR Metaport offers a 3D virtual experience of Terminal 2 at the airport. The 3D interface enables customers to enquire and check into flights, navigate terminals, shop, and connect with other travellers. It is considered one of the first terminals worldwide that can be experienced within the metaverse.
Government’s move to encourage usage of digital twin technology
In a bid to encourage the usage of digital twin technology, the Department of Telecommunications (DoT) recently launched the Sangam: Digital Twin initiative, an unparalleled venture inviting expressions of interest (EoIs) from industry pioneers, startups, micro, small and medium enterprises (MSMEs), academia, innovators, and forward-thinkers.
The Sangam: Digital Twin is a proof-of-concept initiative divided into two stages, set to be conducted in one of the major cities in India. The first stage is exploratory, aimed at gaining clarity of horizon and fostering creative exploration to unleash the potential. Further, the second stage is for the practical demonstration of specific use cases for generating a future blueprint to serve as a roadmap to scale and replicate successful strategies in future infrastructure projects through collaboration.
In addition, the initiative symbolises a collaborative leap towards reshaping infrastructure planning and design, combining the prowess of 5G, IoT, AI, augmented reality/virtual reality, AI native 6G, digital twin, and next-generation computational technologies with the collective intelligence of public entities, infrastructure planners, tech giants, startups, and academia to break the silos and engage in a whole-of-nation approach.
According to the government, Sangam brings all stakeholders on one platform, aiming to transform innovative ideas into tangible solutions, bridging the gap between conceptualisation and realisation, ultimately paving the way for groundbreaking infrastructure advancements. It champions a holistic approach to innovation, urging stakeholders to transcend traditional boundaries and harness unified data and collective intelligence. Further, echoing global movements towards smart infrastructure and supported by India’s geospatial leapfrog, Sangam carves out a position of leadership for India in digital infrastructure and innovation, while also acknowledging similar strides made by global leaders. It is a call to action for creating an ecosystem that maximises the value of technological advancements to fulfil societal needs for efficient, effective, and sustainable development.
To this end, DoT has invited industry pioneers, startups, MSMEs, academia, innovators and forward-thinkers to pre-register and actively participate in Sangam’s outreach programmes, and explore, create, and commit to transform the future of infrastructure planning and design. The deadline for submission of EoI responses is March 15, 2024.
What lies ahead
With the government’s thrust on leveraging digital twin technology, this market is expected to grow significantly in the coming years. As per an industry report, it is anticipated to grow at a compound annual growth rate of 21.2 per cent during 2024-30. This growth can be attributed to various factors, including the increasing demand for digital transformation, advancements in technologies such as AI and IoT, and the need for improved operational efficiency and cost reduction. Additionally, the government’s initiatives towards promoting digitalisation and smart manufacturing are driving the adoption of digital twin technology in India.
However, the lack of awareness and understanding among businesses about digital twin technology is a major challenge hampering its growth. Additionally, the high initial investment required for implementing digital twins and the lack of skilled professionals in this field are significant issues. Another challenge is the integration of legacy systems with digital twin technology, which can be a complex and time-consuming process. In this regard, ironing out these issues can go a long way in enabling the widespread adoption of this technology across industries.
Kuhu Singh Abbhi
