While the digital twin itself isn’t regarded as a technology, business profitability relies on the collaboration of many of the latest digital technologies. The concept of the digital twin benefits companies, bringing together aspects like intelligence, insights, tools, power of visualisation and automation on a single platform. As the complexities involved in industries like aerospace, automotive, and telecommunication aren’t easy to comprehend, even a marginal upgrade in simplifying these intricacies would be massive in context.

Concepts that are similar to the data twins have long been applied in the field of telecom. However, there is still opportunity to take the network to a superior level, and the digital twin seems to be the foundation of it. According to Craig Badrick, CEO of Turn-key Technologies, “to facilitate better network design, a digital twin of a network gives an IT team the ability to run simulations for any event imaginable. It also adjusts its actual network configuration as needed.”

The concept of the digital twin could be applied in various sectors within the telecommunication. Below are four substantial sectors that rely on the telecom industry, and ways in which digital twins could integrate.

Better Tower Management: Sensor networks enable the engineers to collect data such as proximity, image, touch, temperature, motion and position of the tower. Having an exact twin of that tower would allow the engineers to extract key information without even visiting the site. Furthermore, experts in the command centres would be able to assist field workers by just observing the clone tower. It will further develop a thorough understanding between the experts and the fieldworkers.

Field Service Management: A digital twin with its Augmented Reality will assist the field staff by providing them all the information prior to their visit to the field. The information would enable them in preparing for any unpredictable or possible failure. Currently, they do not have much on-hand information to deal with these problems, and consequently spare extra time in rectifying them.

Network Planning & Design: Network capacity planning and design predictions beforehand are virtually impossible for the network providers. Deployed network configurations change over time, and hence maintaining a precise inventory of network elements and a follow up of changing configuration becomes challenging. With a digital twin at the helm, networking engineers would be able to analyse data to keep up with the changes. Additionally, the digital twin’ AI/ML capabilities will also allow them to stimulate, plot patterns, and predict faults. All these tools together would significantly provide for better network planning and design.

DevOps Sandbox: Latest technologies like 5G or SDN requires testing the interworking of multiple vendor devices and solutions. The digital twin could act as a testing play-field for all the latest technologies. The developers won’t have to risk their innovations by testing them on conventional devices. The digital twin would provide developers flawless testing and accurate results before they would deploy it on real networks.