Mitsubishi Electric Selects BlackBerry to Power its New In-Vehicle System

Mitsubishi Electric's new automotive in-cabin system, Mitsubishi Electric FLEXConnect, will be powered by BlackBerry IVY, an edge-to-cloud vehicle data platform.

The collaboration will help advance road safety by leveraging an array of sensor data to anticipate safety risks, reduce driver distractions, highlight potential driving hazards, and enable new consumer experiences.

"The collaboration between Mitsubishi Electric and BlackBerry to advance our in-cabin system takes the driving experience to the next level by truly going the extra mile," said Mark Rakoski, VP Advanced Engineering at Mitsubishi Electric Automotive America, inc. "With its advanced safety features, intuitive interface, and enhanced sensory feedback, Mitsubishi Electric FLEXConnect establishes a new cabin experience standard, revolutionizing the way we interact with vehicles. With BlackBerry IVY, we're able to bring innovations like this to market faster, and in full confidence that the security and privacy of user data is protected."

"We are delighted that Mitsubishi Electric has selected BlackBerry to power its new in-vehicle system," said Vito Giallorenzo, SVP General Manager of IVY and Head of Corporate Development at Blackberry. "By leveraging BlackBerry IVY as a key component of its FLEXConnect platform, Mitsubishi Electric raises the bar for in-cabin experiences and helps improve road safety. BlackBerry IVY is unique in how it enables automotive OEMs to leverage a multitude of vehicle signal data in real-time and cost-effectively into valuable insights."

Driver monitoring system

• Determining driver distraction and concentration levels by detecting signs of drowsiness, estimating cognitive load, monitoring interaction with the infotainment system and more.


• Collecting biometric information to provide insight into short- and long-term changes to a driver's physical status, such as health, triggering autonomous pullovers and alerts to emergency services.


• Analyzing facial features to create personalized identification profiles for automated verification to enable vehicle access and in-car payments.


• Correlating user preferences with environmental information, such as suggesting optimal parking locations based on preferences for cost, distance from destination, parking format and availability.