Digital Twin Software Development: Hot-Button Questions Answered

According to Research and Markets, over 95% of vendors across multiple industries recognize the need for IoT APIs and platform integration with digital twinning functionality. What’s more, digital twin-supported solutions in smart cities will reach $3.77 billion by 2026.

In this article, we will delve into the reasons behind the digital twin technology success, and talk about the intricacies of the implementation processes.

What is a digital twin software?

A digital twin is when every physical product, process, or service gets a dynamic digital form or representation. A digital twin platform is a simulation-based software that uses the integration of digital models, sensor networks, information systems, data platforms, etc., to achieve multi-dimensional simulation and complete the mapping in the virtual space. This way, the entire life cycle process of the physical object is reflected digitally.

Where can digital twin technology be used?

Examples of digital twins can be found across multiple industries and are used for a range of applications and purposes. Some notable examples include:

• Real estate. A digital twin here contains a whole spectrum of data concerning the smart building itself like floor plans, data from the HVAC (heating, ventilation, and air-conditioning) system, real-time sensor data from the building management system, security system, environmental sensors of lighting and fire, and data about the assets and the people in the building (tenants, staff, and visitors).
  The purpose of a digital twin is to understand, predict and prevent potential performance and maintenance issues, and find new ways of generating more revenue from it.
• Smart cities. Digital twin software implementation can also be used to help cities become more environmentally, economically, and socially sustainable. Virtual models can guide planning decisions and offer solutions to complex challenges faced by modern cities. For instance, real-time responses to problems can be informed by real-time information from digital twins to allow assets such as healthcare or educational organizations to react to a crisis.
• Disaster management. Global climate change has had an impact across the world in recent years. However, digital twins can help to combat this by the informed creation of smarter infrastructures, emergency response plans, and climate change monitoring.
• Healthcare. The medical sector has benefitted from creating a digital twin in areas such as surgery training, organ donation, and de-risking of procedures. Systems have also modelled the flow of people through hospitals, allowing them to track where infections may exist and who may become in danger through contact.
• Automotive. One example of where digital twins are used in the automotive industry is to collect and analyze operational data from a vehicle in order to assess its status in real-time mode and inform product improvements.
• Retail. Outside of manufacture and industry, digital twins are intensely employed in the retail sector to model and augment the customer experience, whether at the level of a shopping center or for individual stores.
• Manufacture. Digital twins can make manufacturing more productive and streamlined by reducing throughput times.

What are the benefits of digital twin software?

In this section, we’ve selected the top three benefits of digital twins for business.

• Reduced costs. Usually, a product goes through several iterations before a functional prototype is displayed. It is very costly because the process requires a significant contribution of time and work. Digital twins allow engineers to perform tests and simulations in a virtual environment, which reduces defects significantly during actual production. It is much cheaper and faster to correct defects in the digital world than in the real world. Manufacturers can eliminate almost all risks of future output and make sure that the physical object will work exactly as planned.
• Less time to market for new products. Getting to market faster than competitors is often a problem due to long steps and constant changes in production. Advanced imaging algorithms of digital twins help to greatly reduce time to market. The product life cycle is carried out in the digital environment, where all improvements can be made quickly and easily. A virtual prototype validates how the physical copy is going to behave in reality, thus optimizing efficiency and development time.
• Predictive maintenance. The primary advantage of a digital twin technology is that it can solve problems well in advance. This feature is called predictive maintenance. Virtual prototypes perform constant remote control of their physical prototypes, gathering various sources of information through sensors. The analysis of the collected data allows us to predict possible problems, for example, if a spare part is almost worn out and needs to be replaced.

Human operators will receive reports on possible problems and be able to address them in a timely manner. If a part is replaced before it is broken, the manufacturer will avoid more serious damage and unnecessary downtime, saving time and money.

Is your business ready for a digital twin?

Digital twin software development requires prior groundwork. Here are the key elements required for your digital twin investment to pay off.

• Clear business objectives and goals.
• Build a smart technology ecosystem including sensors, APIs, actuators, etc. to create a connected ecosystem. Of course, ecosystem components can differ depending on your business type.
• Train business leads, data analysts, IT managers, and IT security teams to implement a digital twin strategy.
• Create an effective data management policy that covers ownership, ethics, and security.
• Invest in real-time data processing, predictive analytics, 3D modeling, and ML to build robust data models.

Real-world digital twin software examples

Take a look at the ways digital twins streamline the development of many industries.

Construction

Take a look at the Collins Wharf’s digital twin that tests and determines the viability of building a multi-story complex from sustainable timber, located on the Yarra River in Melbourne. The timber had not been tested in buildings of this height (a 28- and a 29-story apartment tower). The inclusion of the project’s processes and materials in the digital twin gave a more granular understanding of the process and cost for developers.

Source: Global Infrastructure Initiative

Twin cities

Shanghai and Singapore both have complete digital twins that work to improve traffic flow, and energy consumption, and they even help to plan developments. Smart cities are fast becoming a reality, providing an excellent way to reduce pollution and increase the wellbeing of residents.

Source: Augmate

Energy system

GE’s wind farm has increased productivity by 20%. The real-time information fed to their digital replicas from sensors on each of the wind farm turbines enables more efficient designs and even suggests changes for making each active turbine more effective.

Source: GE

Healthcare

Mater Private Hospital in Dublin integrated a digital twin model representation for the radiology department. Such simulation optimizes the process and improves the patient experience by effectively managing emergency services, optimum utilization of lab and medical equipment, staffing requirements, and managing device downtimes, as well as reducing waiting times. Thus, hospital management can monitor the entire infrastructure from a unified platform: patient to clinician to data to workflow.

Source: Digital Progression

Entertainment

At the Spring Festival Gala aired on China Central Television, the four human hosts were joined by an AI copy of themselves. These were their very own digital twins created by ObEN. The company used machine learning, natural language processing, and computer vision to build virtual copies of the hosts. The technology can be used during isolation times when people can’t attend public spaces.

Source: Forbes

Agente expertise in developing digital twin software

We have vast experience in IoT software development, 3D modelling, and creating digital twins in particular. For example, one of our recent projects was for real estate.

It was a complex application for a smart house that helped to make the management of a skyscraper more effective. The building had a large number of monitoring devices, and the service team struggled to maintain all of them on site. Our client wanted to optimize the process by creating a system that would enable the service team to do their job online.

It was a full-cycle web app project in which we created the building digital twin, enabled data preload from hundreds of building devices, integrated an analytics service, and enabled a 3D building preview and interaction with the building map.

Now, the client can easily monitor the data coming from all the devices and make decisions about the building maintenance.

How to develop digital twin software?

The key functions a digital twin should have:

• Space monitoring. These are insights from sensor data capture, integration, and visualization, to the end-user app through a series of touchpoints.

Source: Fracture Reality

• Connectivity. All the core systems within the physical prototype should be connected and reflected in the digital twin, for example, HVAC systems, water pumps, fire alarms, power, and lighting in a smart building.

Source: Seebo

• Access control. A digital twin should allow smart access to specific areas for designated individuals based on user identity captured from multiple data sources.

Source: Pinterest

• Data Analytics. The feature means processing large volumes of real-time valuable data about the physical product.

Source: Seebo

• Security. It involves applying the best practices of the IoT security experience to the context of digital twin apps.
• Seamless integrations. A digital twin app should allow connection with a wide range of third-party hardware and software.

• Source: Smart Cities World

Development process

We can break the digital twin development process into the following main stages: discovery, UX/UI design, app development, quality assurance, release, and support.

• Design discovery. We create potential user personas and go over their user stories and user flows. At this stage, we also build information architecture and low fidelity wireframes to have a structural look at the digital twin.
• Technical discovery. We prepare documentation with detailed information about general data flow in a digital twin, project architecture, and technological stack, as well as development and QA principles.
• UX/UI design. We build UX/UI wireframe and, prototypes, and we create high-fidelity UI mockups in a digital space to determine how the real object will look.
• App development. We prepare a product requirements document and perform frontend and backend development of the digital twin, enabling connectivity with the physical prototype, controlled access, integrations, data analytics, and security measures.
• Quality assurance. We develop the test strategy and plan; we go through all the possible test scenarios and compile a test summary.
• Release. At this stage, a fully-featured digital twin is deployed. Usually, digital twin implementations start small, such as monitoring the performance of a single part within an asset, and expand over time. This can happen in two ways: first, by bringing a number of smaller digital twins together to give a complete picture of an entire machine, asset or business process. Second, organizations add more sophisticated capabilities, for example simulations.
• Support. In the case of a turnkey development we offer a 3 to 6-month guarantee.

What are the challenges to digital twin software adoption?

Three main adoption challenges you should be ready to face are security, data quality, and team qualification.

• Update your data security protocols. According to Gartner’s estimation, 75% of the digital twins for IoT-connected OEM products will use at least five kinds of integration endpoints by 2023. Each of the endpoints represents a potential area of security vulnerability. The areas of highest security importance are data encryption, access privileges, least privilege principles, routine security audits, and addressing known device vulnerabilities.
• Manage your data quality. Digital twin models depend on the data from thousands of remote sensors that usually communicate over unreliable networks. Improved data quality for a digital twin creates more certainty for the recommendations or changes it provides to improve the construction or operation of a built asset. Companies that want to implement digital twin technology must manage gaps in the data streams.
• Train your team. Although digital twins have huge benefits, the technology is not easy to implement as it involves new ways of working, which can potentially lead to problems in building new technical capabilities. You need to make sure that your staff members have the required skills and tools to work with digital twin models.

Final words

Agente has learned the stumbling blocks of digital twin software implementation. We employ that knowledge to guarantee accurate representation of the twin, and precise data is collected from the relevant elements of the system. A digital twin accelerates risk assessment and production time. It allows you to perform real-time remote monitoring, helps to proactively identify any problems within the system, and promotes better financial decision making.

If you need to build a custom digital twin platform from scratch or upgrade an existing one, get back to us.