Digital Twin Technology Reshaping IoT-Enabled Environments
What is a digital twin? Digital Twins can be best defined as digital copies or virtual replicas of physical assets. Data scientists can make use of digital twins to try and run simulations before they build and deploy actual devices. Digital Twin technology transforms the way in which the Internet of Things, Artificial Intelligence, as well as, Data Analytics is optimized.
The concept of ‘digital twin’ rewinds back to the year 1970 with the launch of Apollo 13. NASA’s digital twin model of Apollo 13 was a famous rescue mission to assess space monitoring conditions. The concept ofDigital Twins later gained recognition in 2002 at the onset of a presentation by Challenge Advisoryat the University of Michigan. According to Gartner, the digital twin is one of the top 10 strategic technology trends since 2017. Gartner estimates 21 billion connected sensors and endpoints by the end of the year 2020!
Data scientists build digital twins that can receive input from sensors that collect data from its real-world counterpart. The twin is then allowed to simulate in real-time. This process provides critical insights and feedback that helps in analyzing the actual system’s performance. For instance,a twin carcan be built digitally by validating various inputs to check on factors such as safety, mileage, etc.
Digital Twins impact various IoT-enabled environments such as manufacturing, automotive, healthcare, financial services, urban planning and many more. The major IoT-enabled industries that can leverage the benefits of digital twin technology and how they benefit from it are as follows:
Manufacturing Industry : The Digital Twin concept with the IIoT (Industrial Internet of Things) is implemented in the manufacturing domain. It can be designed and deployed in numerous ways such as in tracking and monitoring systems, evaluating production, troubleshooting equipment used, etc. As digital twins can predict failure chances, it helps in saving costs, time and in improving customer loyalty.
Automotive Industry: The future of autonomous vehicles lies on well-connected road systems and vehicles. Critical data gathered from this network. The digital twins then act as simulated models that help engineers analyze the behavior of vehicles before they are used on roads.
Healthcare: Medical monitoring technology is used to gather critical data such as heart rate, oxygen levels, etc. This data is used in the creation of digital simulations. Digital twins help the healthcare ecosystem in disease diagnosis, remote monitoring of patients, etc.
Urban Planning Sectors: Vital data such as maps, blueprints of buildings, real-time data from sensors, etc are used to create digital twin models to improve urban planning services. These services include waste disposal, mobility services, providing resources like electricity and water, etc.
Asset Management: Both worksite and remote industrial operations can be managed via digital twins with the help of remote asset monitoring services. Predictive maintenance of assets like machinery improves operational efficiencies and decreases disruption of business operations.
Digital twins can also be converged with augmented and virtual reality techniques for better visualization of industrial workflows. Financial Services: Customer behavior can be easily monitored with digital twin technology.
