Let's put Attention back in the Driver's Seat...
Car crashes in the US (400k+ in 2015) have shown a 2-years rise, after a decade of slow but steady declines. Although safer cars and improved driving assist equipment have helped prevent crashes, distracted driving is more than offsetting all these benefits.
State bans on the use of cell phones in cars don't seem to be effective. Mobile apps that intercept distracting calls or the use of apps are easy to circumvent and distractions can also come from sources other than phones.
The old fashioned way to solve the problem is to have a front seat passenger who 1) is aware of sudden driving risks, 2) can tell whether the driver is paying attention, and 3) will warn the driver when needed.
dreyev mimics the behavior of a dependable passenger who can evaluate the risk (associated with the current speed, acceleration, braking, cornering, pavement, weather and traffic conditions), then match it against the level of attention exhibited by the driver. If the driver looks away from the road for too long or too often, or the car is zigzagging in the lane, the virtual passenger warns the driver with specific signals or with spoken utterances.
dreyev uses Computer Vision to analyze head pose and analyze eye gaze and eyelid closing to flag possible distraction and drowsy conditions. Machine Learning enables the creation of custom models of driving habits and experience to ensure that warnings are only given when necessary.
CEO and Co-Founder
Pioneered Virtual Assistants at Conversational Machines, IBM Watson
Built up IBM CIO Innovation Teams spanning global locations incl. India, China, Vietnam and the US
Led multi-million dollar advanced technology deals across Industry and Technology Clients
CTO and Co-Founder
25+ years leading World First R&D projects
First IBM Speech Recognition Product worldwide
First Navigation and infotainment system ("Sally" - Honda), reference for conversational access in car
Program Director at IBM Watson, first computer to beat human champions at Jeopardy!
Image Processing Guru
Machine Vision and Industrial Automations expert
Most Innovative App Prize for Eye Type mobile app at EESTEC International Android Competition 2015 and Computer Society Award at IEEE Mobile Application Development Contest 2015
Best Paper Award at the 3rd Panhellenic Student Conference Eureka, 2009.
SOFTWARE DEVELOPMENT LEAD
Vision-Based, In-Cabin Analysis and On-Road Vehicle Detection Systems.
Interests: Artificial Intelligence, Artificial Consciousness, Autonomous Vehicles, Computer Vision
Additional areas: Computational Geometry, Computer Graphics, Virtual Reality
Maria Grazia Verardi
Advisory Board Member
Internationally recognized Telematics Expert, Project Manager, Consultant and Trainer
Extensive expertise in telematics, Usage Based Insurance (UBI), Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications
Co-author of ETSI and CEN standards and technical reports in Human Machine Interface in cars, V2V, V2I communications & pan European eCall
Advisory Board Member
25 years of venture capital investment experience
Active Board member of both public and private corporations, guidance on business strategy, corporate expansion, corporate combinations and organizational development
Responsible for Nexus’ successful investment in Biodel Inc., a company developing a new formulation of insulin
Advisory Board Member
Sales and Business Strategist
35 years of senior executive management experience
Principal and Founder of The CXO Advisory Group
Startup Mentor, Competition Judge (Mass Challenge, Seedcamp, Parallel18, MIT Enterprise Forum Cambridge, IBM Smartcamp Cambridge)
TeleLingo is a startup created in 2014 with the ambitious goal to save lives of drivers by observing and modeling their attention in order to prevent crashes caused by distraction and drowsiness.
Co-founders, Dr. Maggie Stys (CEO) and Dr. Ing. Roberto Sicconi (CTO), met at IBM Watson Research and share their vision for the use of disruptive technologies and creative business models to enhance mobility, embedded devices, personalized user interfaces, and ubiquitous access to information.
The current dreyev solution is a risk mitigation system which includes the ability to detect safe driving conditions and support for simple mind-stimulating spoken interactions. The product will have added machine vision and AI capabilities and proceed with building the ultimate Digital Assistant with Copilot Expertise.