As the world’s elderly population grows at a record pace and half of all elderly adults living alone report suffering from loneliness, ElliQ is a social robot helping older adults stay active, engaged
and seamlessly connected with family and friends. ElliQ makes technology accessible to seniors and proactively promotes an active lifestyle.
To be genuinely engaging, the robot needed to be intuitive, personalized and friendly. Machine learning vision was needed to locate people in the room, their faces, and to enable ElliQ to look towards them when ‘she’ talks and listens. Highly robust vision technology was required to support countless situations.
To deliver the required performance, Intuition Robotics used Arm-based technology in the Qualcomm Snapdragon 820 system on a module, with Brodmann17’s machine learning functionality.
“We’ve used the best technology available to overcome gaps created by the generational digital divide”
said Dor Skuler, CEO and co-founder of ElliQ.
“Arm-based technology lets ElliQ use machine learning , such as Brodmann17 and others, to adapt her personality and the proactive suggestions she gives to the individual in front of her.”
Next-Generation Deep Learning Vision
A key to success was finding a highly accurate deep learning vision technology that would allow ElliQ to maintain interactivity with the people in the room, turning her head to the right direction in real time, even if people are partly obstructed or hidden in a home environment. Brodmann17 was chosen to tackle the task.
Brodmann17’s software-only deep learning vision solution provides ElliQ with best-in-class vision capabilities, utilizing a single Arm core per camera to reduce power consumption. In addition, with Broadmann17 vision technology, the robot requires no active cooling or fan, resulting in a quieter, more human-like experience.
“We chose a Qualcomm Snapdragon 820 system on a module, based on Arm technology, to deliver the processing power we needed for ElliQ’s level of intelligence”
“Thanks to Arm’s rich ecosystem of partners, we were able to team up with Brodmann17 to deliver industry-leading computer vision with the fastest and most accurate results, using a small fraction of the computing power.”
- Intuitive, human-like behavior and enhanced engagement
- Real-time facial detection with state-of-the-art accuracy, even in challenging environments, such as reduced lighting
- Ability to track the home environment for possible issues
- Low battery consumption while maintaining world-class performance and accuracy, using
minimal computing power
“We are proud to see Brodmann17 next-generation vision technology powering intelligent devices at the home”
Said Adi Pinhas, CEO and co-founder of Brodmann17