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Intangles Releases Digital Twinning in Vehicle Life Cycle Management


News provided by

Intangles

12 Jun, 2018, 11:56 GMT

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PUNE, India, June 12, 2018 /PRNewswire/ --

Intangles, after releasing Connected Vehicle and Advanced Telemetry technology, has now released Digital Twinning (DT) solution using Hybrid Analytics in Vehicle Life Cycle Management. Through digital twinning, Intangles creates virtual sensors for automobile components, thus predicting performance and failures, which are generally too late to detect or lead to vehicle breakdown.

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Intangles Digital Twin vs Other Connected Vehicles (PRNewsfoto/Intangles)

     (Photo: https://mma.prnewswire.com/media/704641/Intangles_Digital_Twin.jpg )

"We believe that Digital Twinning foreshadows the Connected Vehicle and Advanced Telemetry space significantly. As against automating the operational needs Digital Twinning opens up a whole new paradigm of analyzing data using virtual sensors," said Anup Patil, CEO, Intangles Lab. As per Gartner, Digital Twins is among the Top 10 Technology Trends to watch out for in 2017.

Intangles has deployed its Digital Twinning solution, Ingenious, to help manage the Life Cycle of Vehicles by predicting and interrogating data from vehicles. The company has established its own set of algorithms that allow fleet operators to keep track of performance of the vehicle in real time.

"Intangles developed a brilliant voltage vs. time curve. Its built-in virtual sensor was able to trigger alerts well in advance about future deterioration of alternator and battery systems. In the last few months we have reduced our alternator related breakdowns to zero," said Abhijit Konduskar, owner of Konduskar Travels, a large fleet of Volvo vehicles across Western India.

Combining Deep Learning with Physics-based modeling, Ingenious predicts component-level failures by analyzing sensor data. The data gathered through their proprietary hardware feeds into the Physics + Deep Learning-based model, which transforms the data into a much higher realm where certain target features allow the algorithms to predict the health of the vehicle under study.

"One of the critical elements to build an effective time series data and physics-based analytics model is the capability of the warehouse to aggregate large amounts of data acquired from the vehicle and analyze data from a wide variety of installed base over a statistically significant period," said Aman Singh, Head of Analytics at Intangles.

About Intangles 

Intangles is an IoT and Deep Learning Company with expertize in Digital Twinning. Intangles has developed its own set of proprietary algorithms that allow asset owners to monitor the performance of assets in real-time enabling them to make informed decisions. Intangles has its own state-of-the-art solution that analyzes data using Physics-based analytics in the virtual world and further improves the predictive index by making use of Deep Learning.

For more information about Intangles, see http://www.intangles.com/ or write to Anup Patil at intouch@intangles.com.

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