BIMScaler Blog – The combination of digital twin and IoT is set to change the way we interact with the physical world.
Today, we’re in the first era where a physical object, from a simple sensor to a huge city, has a virtual copy mimicking its every move.
This leads to a multi-dimensional result: we can predict what the building will be like in the future, and even experiment with its possibilities without having to touch it.
Right, let’s look at the various possibilities of the digital twin and IoT.
What is a Digital Twin in IoT?
In the context of the IoT, a digital twin is basically a virtual copy of a physical object, system, or process.
The idea is that it should accurately reflect its real-world counterpart in real time.
IoT and digital twin technologies work together by using connected sensors and devices to gather data.
This data is then processed and analysed to create a complete digital picture of the asset.
Michael Jacoby and Thomas Usländer explain in “Digital Twin and Internet of Things—Current Standards Landscape,” that the digital twin makes it easier to organise and understand the data collected by IoT devices, which in turn makes predictive analytics and automation possible.
In Australia, industries like AEC, mining, and energy are already using digital twins to simulate and optimise processes.
That way, the digital twin is helping industries make better decisions and manage their resources better.
In fact, Infrastructure Australia plans to make sure all infrastructure projects funded by the federal government have a digital twin within the next 10-15 years. This is all part of the Infrastructure Australia Plan for 2021.
Let’s look at Cross River Rail in Brisbane as an example. This is one of the most advanced digital twin projects in Australia.
It models 300 square kilometres of Brisbane to help with the design and planning of the largest piece of public transport infrastructure ever built in Queensland.
What is the Difference Between Digital Twin and IoT?
The terms ‘digital twin’ and ‘IoT’ are often used together, but they actually represent two different but related ideas.
The IoT is all about connectivity. It’s a network of physical devices with sensors, software, and other tech built in, so they can connect and exchange data over the internet.
On the flip side, the digital twin is all about representation and analysis.
It’s the virtual version you can use to create a dynamic model of the physical object using data from the IoT.
As R. Minerva, G. M. Lee, and N. Crespi, explain in their paper, “Digital Twin in the IoT Context: A survey on technical features, scenarios, and architectural models,” shows that the IoT captures real-time data from the environment.
At the same time, the digital twin uses this data to simulate how the physical system works, so it can make predictions or suggest improvements.
In industries like healthcare or agriculture, IoT devices may monitor environmental conditions or patient vitals, but the digital twin adds value by using current and historical data to simulate future outcomes.
To put it simply, in the context of digital twin vs IoT, the IoT is like the nervous system, sensing and transmitting information.
Meanwhile, the digital twin is like the brain, processing that information and making intelligent decisions.
How Digital Twins and IoT Work Together
At the centre of this IoT digital twin system are the physical objects themselves – the real-world entities we’re replicating in the virtual world.
These can be anything from simple sensors to complex industrial machinery or even entire cities.
IoT sensors and devices are embedded in or attached to these physical objects.
These IoT sensors and devices are the eyes and ears of the digital twin.
They collect a constant flow of data about how the object is doing, how it’s performing, and what’s going on around it.
The data is then sent to the digital twin via connectivity and communication networks.
These networks, which can be wired or wireless, need to be reliable and secure to make sure the data is kept safe and private.
Once the data gets to where it needs to go, it’s processed and stored efficiently.
Typically, the data process and storage use cloud or edge computing technologies to handle the sheer volume, velocity, and variety of information generated by IoT devices.
The data is then used to create and update the digital twin model.
Next, we analyse the digital twin model using machine learning techniques.
The goal is to spot patterns, make predictions, and generate useful insights into how the physical object behaves and performs.
These insights can be used to make things run more efficiently, predict and prevent failures, and even enable autonomous decision-making.
Finally, a user interface and visualisation component lets users interact with the digital twin and understand the data and insights it generates.
This can range from simple dashboards to immersive virtual reality environments, depending on how complex the digital twin is and what it’s for.
Learn more: AWS IoT TwinMaker: A Guide to AWS Digital Twin for Your Data & Projects
Components of Digital Twin IoT
As you see, the IoT and digital twin technology work together to create a closed-loop system where the physical and virtual worlds are joined at the hip.
The process we’ve illustrated above relies on a few key components, as you’ll see below:
- The Physical Objects
- The IoT Sensors and Devices
- The Connectivity and Communication Network
- The Data Processing and Storage
- The Digital Twin Model
- The Analytics and Machine Learning
- The User Interface and Visualization.
Types of Digital Twins in IoT
The digital twins can be grouped into different categories based on how complex, wide-ranging, and useful they are.
Each type of IoT digital twin has a specific purpose and offers unique benefits in different situations.
Component Twins
These are the individual parts that make up a larger system.
They’re pretty straightforward and concentrate on keeping an eye on and understanding how different parts are performing.
For instance, a component twin of a jet engine turbine blade can give you insights into things like temperature, stress, and vibration levels.
Asset Twins
These show the full picture of an asset or piece of equipment.
They’re more complex than component twins and give you a complete picture of the asset’s health and performance.
So, for instance, an asset twin of a wind turbine can keep an eye on things like power output, blade angle, and wind speed, which helps with predictive maintenance and optimisation.
System or Process Twins
These represent complex systems or processes, comprising multiple interconnected components and assets.
They give you a complete picture of how the system works and let you test out different ways of improving its performance.
For instance, a system twin of a manufacturing plant can simulate the entire production process, identify bottlenecks and optimize production schedules.
Product Twins
These show how a product develops from start to finish, from design and manufacturing to operation and maintenance.
They help us to make products better, keep track of them and give customers a more personal experience.
So, for instance, a product twin of a car can track how it’s used, give maintenance reminders and make personalized recommendations to the driver.
Learn more: 3 Unique Digital Twin Use Cases That Will Make You Rethink Construction
Applications of Digital Twin IoT Across Industries
The combination of digital twins and IoT technologies is set to have a huge impact across many industries, changing the way businesses operate and create value.
In manufacturing, digital twins have been a huge help in predictive maintenance and production optimisation.
It can also help you design and test new products in a virtual setting before you start making them in real life. This can help you cut costs and get your products to market faster.
In healthcare, the digital twin IoT can be used to create virtual replicas of patients.
So, the digital twin is helping to make personalised medicine and remote monitoring of health conditions a reality.
It can also be used to test out different treatments and procedures, which helps to improve patient outcomes.
In the energy sector, the digital twin IoT can be used to keep an eye on and make improvements to energy grids, which helps with predictive maintenance and demand forecasting.
It can also be used to test out different energy sources and storage technologies, which helps us move towards renewable energy.
How to Combine Digital Twin and IoT with Limited Resources
Bringing digital twins and IoT solutions to life can be a bit of a resource challenge, but there are ways to make it work even with limited resources.
One way to get started is to focus on a few specific use cases with high value, rather than trying to digitise the whole operation at once.
That’s why, a phased approach lets businesses use their existing IoT infrastructure while gradually adding digital twin capabilities.
It’s also a good idea to team up with external providers who know all about digital transformation. This approach can really cut down on the hassle in the short term.
Here in Australia, we at BIM Scaler can help your business integrate IoT and digital twin technology without the need for a big upfront investment.
We can help with model auditing, Revit modelling, and coordinating 4D and 5D planning.
These services make it easy for your business to manage your digital twin models.
Simply put, we’ve got you covered, but we’ll introduce them gradually, where they’ll give you the biggest return on your investment.
Want to see how this all works in the real world? Kindly take a look at what we do on our BIM Management Support page.
Or, even better, let’s grab lunch.
We’ll talk through any issues you’re facing – there’s no sales pressure – and see how we can make those digital dreams a reality, one step at a time.
In Closing
Remember, you don’t have to go all in on a digital twin IoT system right away.
Start small, focus on the main things, and gradually build up your capabilities as your resources allow.
Plus, if you team up with BIM Scaler, you can make the move to digital twins and IoT without putting too much strain on your resources.
