26.85 million! Smart tire sensor company raises funds to measure car driving environment conditions

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Black technology, forward-looking technology, autonomous driving, Revvo, IntelliTire, smart tire sensors, tire sensors to measure driving environment, new automotive technology

(Image source: venturebeat.com)

According to foreign media reports, Revvo is a company that makes machine learning software and sensors to predict the life of vehicle tires. On March 26, local time, the company announced the completion of a round of financing of US$4 million (about RMB 26.85 million) to expand its business. The newly raised funds will be used to expand the company's technical team. Last year, Revvo conducted a trial with Goodyear Tire Company, and the newly raised funds will also support similar trials.

Revvo's smart sensors are installed in the wheel housings of cars to track indicators such as tire pressure, tire temperature, wheel rotations, and tire sounds. In addition, these sensors can measure environmental conditions, such as whether the vehicle is driving on a rough or smooth road, or whether the wheels are frequently exposed to ice or rain.

Revvo, which is in the process of rebranding from its former name IntelliTire, initially developed the sensor-driven software to target fleet operators who buy large quantities of tires and want to reduce tire consumption and costs. In the future, Revvo hopes to help drivers understand how their personal driving behavior affects the safety and performance of their vehicles.

Revvo co-founder and CEO Sunjay Dodani said he hopes the smart tire sensor can support the driver assistance systems built into current cars, as well as the control output systems of future self-driving cars. For example, if the self-driving system knows that one of the car's tires has only half of the tread left, the self-driving car may brake earlier than normal.

Revvo's financing was led by Norwest Venture Partners, with participation from AngelList and Vulcan Capital. So far, the company has raised a total of US$4.6 million (approximately RMB 30.89 million).


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