Cloud to help realise smarter AI-powered digital twins – FutureIoT

The demand for digital twin or simulation solutions is growing among enterprises, and cloud computing is an increasingly important component of any digital twin solution. Digital twins are set to become more intelligent by integrating AI algorithms and ML models delivered using cloud platforms.

ABI Research forecasts a steady increase in uptake for cloud-driven digital twin solutions, driven by advancements in AI/ ML, edge computing, multi and hybrid cloud deployments, 5G networks, and smart connectivity.

We are seeing the emergence of cloud computing in operational technology (OT). The deployment and integration of cloud solutions with OT solutions in areas such as asset performance monitoring and product lifecycle management provide compelling benefits such as performance reliability, increase in computational power, and seamless AI/ ML processing, explains Yih-Khai Wong, distributed and edge computing senior analyst at ABI Research.

Cloud hyperscalers such as AWS, Microsoft Azure, and Google Cloud provide tools and packaged solutions to build digital twin solutions. Customers can also leverage contextual data from public datasets and funnel this information to optimize their digital twin platforms.

Scalability: Provides flexibility for businesses to scale up or down according to current business needs, ensuring optimal performance of the digital twin solution.

Computational Power: Complex simulations can be processed on the cloud using solutions such as Virtual Machines (VMs) and containers. The availability of various cloud computational components ensures that businesses can match resources according to specific digital twin platforms.

AI/ML Processing: Cloud computing platforms often provide data analytics tools to help process AI/ML workloads. These tools range from the infrastructure compute power components such as the Central Processing Unit (CPU) and Graphics Processing Unit (GPU) to industry-specific application software that can analyse, predict, and make recommendations based on data processed by a digital twin.

The convergence of IT and OT is gathering pace, and digital twin is a great example of how this convergence can elevate existing scenarios into achieving greater possibilities and ultimately increase the value, productivity, and competitive advantage of enterprises, Wong concludes.

Go here to see the original:
Cloud to help realise smarter AI-powered digital twins - FutureIoT

Related Posts

Comments are closed.