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Google and Microsoft develop more technology for the infrastructure sector

Microsoft hololens

Technology giants Google and Microsoft are making further inroads into the civil engineering sector, using tools such as artificial intelligence to improve efficiency. 

Microsoft has just launched HoloLens 2, the next generation of its wearable holographic computer.

Construction is high on Microsoft’s agenda and it has worked with software firm Bentley Systems to develop a sector-specific app.

Syncro XR takes data from a project’s digital twin and visualises it through the HoloLens 2 via Bentley’s connected data environment, powered by Microsoft Azure.

It means that civil engineers and site workers can visualise planned work, check construction progress, identify site risks and access key data such as safety briefings. Users can interact with the model together and collaboratively experience 4D objects in space and time.

Meanwhile Google’s, DeepMind division has developed new technology which it claims will boost the efficiency of onshore wind farms by 20%.

DeepMind took a neural network – computer system inspired by the structure of biological networks – and trained it using weather forecasts and historical turbine data. DeepMind engineers configured their AI to predict power output of wind turbines 36 hours ahead of time. Benefits include better prediction of production, better prediction of power demands, and operational cost savings. 

Another division of Google parent company Alphabet is planning to build an extension to Toronto’s light rail transit (LRT) system.

The project is being developed by Sidewalk Labs, which develops technology to improve urban infrastructure, covering areas such as construction methods and transport. This work is being concentrated in the development of a 350-acre site in Toronto’s Port Lands area to create a huge new “smart” district, which will also include a new Canadian-headquarters for Google. 

Sidewalk’s plans for the development include timber buildings and streets designed for autonomous vehicles.

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