Found in 2009, Cairo and Boston based Affectiva has raised another $26 million to drive emotional and object detection AI for cars. Till date, Affectiva has raised total funding of $53 million. Affectiva believes that its technology would be integrated into car safety cameras to determine the driver’s mood. This round was led by automobile supplier Aptiv. Affectiva, in the near future, also wants its technology to identify driver-passenger and passenger-object interactions.
Affectiva’s computer vision system will help in recognizing a driver’s mood, then use text-to-speech AI to talk to the driver, in-turn asking him/her about the future course of actions. With beginnings in making emotional intelligence AI for videos, the company has now expanded to voice emotion detection in 2017.
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Affectiva’s solutions are adopted by a plethora of companies some of which are –
- Home Robotics makers
- Businesses that build AI assistants
- Autonomous vehicle manufacturers
Affectiva is serious about developing a product that avoids bias altogether along with ensuring that its products are able to detect complex moods and feelings.
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Other capabilities that Affectiva is focusing on are –
- Autonomous cars taking over in a situation where the driver is undergoing sensory overload
- Enabling its technology to operate seamlessly in situations where the hardware configurations are not robust
- Object detection – like notifying a passenger about goods being left behind
- Detect poor customer experience via sentiment analysis by studying a passenger’s face
- System response for a better user experience
Affectiva’s main aim is to transform an automobile into a wellness pod. The company stated that it wants its technology to sense the mood of the passenger. This is especially helpful for companies that operate in the ride-sharing landscape, like Uber or Lyft. Upon distress detection, Affectiva’s computer vision technology may play the passenger’s favorite music, change the lighting in the car or the temperature or use scents to improve mood.
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