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What are the challenges to digital twin software adoption?

The 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.

In i4twins, we know about all the challenges and spare no effort to offer you the best and the most convenient solution.


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