Leveraging the power of IoT for digital twins

With population growth and the rise of urbanization, there is less room for trial and error during urban planning. But what if we can test real-life scenarios before implementing them?

Well, the short answer is we can. Cities worldwide use digital twins, a 3D virtual representation of their city in a test environment. Digital twins allow the simulation of everything from energy patterns to traffic and construction. For example, the city of Gothenburg set up five pilot studies to develop its digital twin, helping to answer the city’s critical questions relating to changing the skyline with new buildings, adapting for driverless vehicles, and protecting against heavy rainfall. All of this testing happens before costly resources go into planning and construction.

CoExist 2 pilot project in the city of Gothenburg to explore how we will share space with autonomous vehicles. Image source

Understanding the digital twins’ landscape

A digital twin involves creating a virtual replica of an intended or actual real-world physical asset. Just as the city of Gothenburg uses 3D imaging to test and measure scenarios before applying them to city planning, many other industries also use digital twins. These industries include but are not limited to manufacturing, construction and real estate, utilities, agriculture, healthcare, retail, and mining. Digital twins are effective for many applications, for example, simulation, testing, monitoring, and maintenance, depending on the use case.

The role of IoT in digital twins 

Static maps and data models are the basic building blocks of digital twins. However, digital twins are much more helpful when they harness the power of IoT. IoT involves collecting data from sensors and devices associated with the physical entity, such as temperature, pressure, humidity, location, and motion. It then centrally integrates this data into the digital twin to make a copy.

IoT facilitates connectivity and data intelligence within the real world. 

• IoT sensors and data collection

The foundation of a digital twin lies in the data collected from IoT sensors deployed on the physical product. IoT sensors can be placed in infrastructure, machinery, vehicles, and outdoor spaces to collect data points. The sensor provides the most accurate physical world representation with real-time data, building an identical twin. As IoT devices continuously collect data, real-time updates ensure that the digital model stays current with the physical. This seamless integration allows for monitoring, feedback, and analysis without delays. 

• Data transmission and communication protocols 

Many communication protocols transfer the data from the sensors to the digital twin. Which protocol to use depends on the range of communication, power consumption, data rates, and requirements of the IoT system. As IoT sensors continuously send data, a process must be in place to manage everything incoming. IoT platforms seamlessly integrate incoming data from different devices into one place. IoT platforms such as akenza manage the analysis and visualization of IoT data. The data is stored indefinitely to allow for historical research, which helps create a digital twin. 

An example of a city's digital twin

Advantages of IoT-driven digital twins

IoT and digital twins are two powerful technologies that, when combined, offer several key advantages to the virtual representation of physical objects: 

• Predictive maintenance and reduced downtime 

Predictive maintenance relies on the actual condition and trends from the normal state of the object to predict future needs. By collecting real-time data and sending alerts according to the machine’s operating status, analysis detects abnormalities to anticipate the requirement of future maintenance before machine failure. Dashboard visualizations help to make these predictions. Drawing these conclusions reduces downtime to keep operations up and running, which is critical, especially for the manufacturing, aviation, and healthcare industries, where machines are highly relied on. 

• Enhanced decision making 

Testing on a digital twin allows for evaluating performance and design before implementing the physical product. This way, decision-makers can monitor the object’s performance, status, and behavior as it operates and also allows for “what if” scenarios, testing hypothetical situations. Historical data better addresses wear and tear to predict maintenance requirements and plan for upgrades or replacements. Digital twins also facilitate collaboration among stakeholders. It is easy to share the digital representation of the system so different teams can work together and make collaborative decisions based on the data. 

Use cases

Many industries have taken advantage of the benefits of digital twins. We will look into a few and their applications. 

Construction and real estate

With the help of digital twin technology, construction and real estate projects can be better managed. Digital twins help in design and planning, prototyping, construction simulation, asset management, building performance analysis, maintenance, and renovation. Digital twins help identify design coordination and optimize construction in the planning phase. With a virtual prototype, stakeholders can make data-driven decisions based on design and functionality. After construction, collecting equipment, materials, and maintenance data can help to manage assets. Digital models can continue to assist in building health maintenance and renovation throughout their lifetime. 

Archilogic’s 3D, interactive, and customizable digital floor plans. Image source

Manufacturing 

Digital twins help move from being reactive to predictive, especially in manufacturing. It helps to predict when equipment is wearing down or needs repair, as well as gives insights into machine performance. For example, quality control can signal potential defects. This alert allows manufacturers to understand better equipment needs to extend their lifetime and foster innovation and enhanced design. 

Automotive

Analyzing driving behavior optimizes vehicle performance and personal driving experience and is crucial for developing autonomous vehicles. Virtual prototyping helps to identify potential flaws early in the development process. Sensors can collect data on vehicle health, tire wear, battery status, and other critical components. With the development of autonomous vehicles, virtual simulations allow manufacturers to test these vehicles in a controlled environment. These practices enhance safety and help shape the adoption of technical advancements. 

How akenza supports digital twins 

The akenza platform offers a low-code solution to data integration, processing, and analysis to support you in your digital twin project. Our Device Type Library hosts many pre-integrated IoT sensors that will fit most situations and measurements requirements. You can also add your custom devices to the open-source library. Our Rule Engine allows you to trigger alerts when data reaches a certain threshold and our Dashboard Builder lets you customize your data the way you want. We host many low-code features to help you start on your project in one afternoon.