By: Deep Dave, Senior Engineer – Industrial IOT, LTIMindtree

A virtual representation of a physical system or object is called a ‘digital twin,’ made by compiling and examining data from multiple sources. This virtual model can imitate the behavior and performance of the physical object or system in real-time because it is an exact reproduction of the latter. Using digital twins, engineers, operators, and managers may simulate and test numerous scenarios without changing the original system, which helps optimize operations, increase efficiency, and lower costs.

Since the early 2000s, the idea of a ‘digital twin’ has existed. Still, it has only recently gained traction due to the development of the Internet of Things (IoT) and other technologies that make it possible to gather enormous amounts of data. With the help of advanced analytics and machine learning algorithms, this data can be used to create accurate and detailed virtual models of physical objects or systems.

To create a digital twin, data is gathered from several sources, including sensors, IoT devices, and other resources. The virtual model of the actual system or object is combined with this data to produce an in-depth and precise representation. Then, the virtual model can test different hypotheses, enhance performance, and spot potential problems. To ensure that the digital twin precisely matches the physical object or system, it can be produced, deployed, and continuously updated in the production environment.

Deploying a digital twin involves several steps that require careful planning and execution to ensure the virtual model accurately reflects the physical object or system. These steps include:

1. Collect data: Gathering data from various sources, including sensors, IoT devices, machine learning algorithms, simulations, history records, and other avenues, is the first stage in constructing a digital twin. This data may cover the performance, condition, and behavior of the actual object. It is crucial to ensure the information gathered is accurate, trustworthy, and pertinent to the virtual model.
2. Create a virtual model: The next stage is constructing a virtual representation of the system or object. This model should be as precise as possible and contain all necessary information. Based on the data gathered, the virtual model must precisely depict the behavior and performance of the physical object or system.
3. Integrate data: The information gathered in step 1 should be integrated with the virtual model. This will enable the virtual model to faithfully reproduce the behavior and functionality of the real object or system. The integration process may include data cleansing, standardization, and other data processing procedures to ensure that the virtual model accurately represents the physical object or system.
4. Test and optimize: After the virtual model has been built and data has been incorporated, it may be utilized to test different scenarios and improve performance. This will increase effectiveness and aid in identifying potential problems. To ensure that the virtual model accurately represents the behavior and implementation of the actual object or system, testing and optimization can be done through simulations and scenario planning.
5. Implement: The digital twin can be used in the production environment after testing and optimization. To guarantee that it accurately depicts the real object or system, it should be continuously reviewed and updated. Ensuring data is accurate, securing data integration and instructing staff on how to use and interact with the virtual model are all possible components of the implementation process.

Transforming Healthcare with Digital Twins

Several industries, including manufacturing, healthcare, transportation, and construction, use digital twins. Digital twins, for instance, can be used in manufacturing to streamline production lines, decrease downtime, and enhance product quality. Digital twins can be utilized in the healthcare industry to replicate and evaluate surgical procedures, improve patient care, and enhance outcomes. Digital twins have the potential to decrease fuel consumption, increase fuel economy, and optimize maintenance schedules in the transportation sector. By enabling medical experts to develop virtual replicas of human organs, tissues, and systems, digital twins are changing the healthcare sector. These digital replicas can be used to test and mimic medical operations, enhance outcomes, and improve patient care.

One unique research example of the application of digital twins in healthcare is the work being done by the Living Heart Project. The Living Heart Project is a collaborative effort between the medical industry and engineering communities to create accurate and detailed digital twins of the human heart.

Through the Living Heart Project, researchers have created a virtual model of the human heart that includes detailed representations of the heart’s structure, function, and electrical activity. This digital twin can simulate and test various medical procedures, including surgeries, device implantations, and drug therapies. The virtual model can also optimize patient care by predicting patient outcomes and identifying potential issues before they occur.

The utilization of digital twins to develop individualized treatment regimens for individuals is another instance of how they are transforming healthcare. Medical experts can simulate and test several treatment options by building a virtual model of a patient’s organs and systems, then choose the most likely successful strategy for that patient. This individualized therapy method may improve patient outcomes while costing less to provide.

Digital twins are also being used to train medical professionals and students. Medical professionals can practice and improve their skills by creating virtual models of human organs and systems without putting patients at risk.  Students can also use these virtual models to learn about the human body and how it functions, which can help them become better medical professionals in the future.

In conclusion, digital twin technology is revolutionizing the healthcare sector by enabling real-time simulation, monitoring, and optimization of patient care. For healthcare providers and patients, building a virtual replica of a physical system and constantly updating and enhancing it using real-world data has many advantages.  Digital twins are having an increasingly significant impact on the healthcare industry, from enriching patient experiences to bettering diagnosis and treatment outcomes. We anticipate seeing even more cutting-edge applications and use cases emerge as we continue to develop and improve this technology, paving the way for a better and healthier future.

References:

Corral-Acero, J., Margara, F., Marciniak, M., Rodero, C., Loncaric, F., Feng, Y., Gilbert, A., Fernandes, J. F., Bukhari, H. A., Wajdan, A., Martinez, M. V., Santos, M. S., Shamohammdi, M., Luo, H., Westphal, P., Leeson, P., DiAchille, P., Gurev, V., Mayr, M., … Lamata, P. (2020). The ‘digital twin’ to enable the vision of Precision Cardiology. European Heart Journal, 41(48), 4556–4564. https://doi.org/10.1093/eurheartj/ehaa159

Levine, S. (2022, September 21). The Living Heart Project and how Virtual Twin Technology can improve healthcare for all. The Journal of MHealth. Retrieved April 26, 2023, from https://thejournalofmhealth.com/the-living-heart-project-and-how-virtual-twin-technology-can-improve-healthcare-for-all/