Everything you need to know about BonsApps’ 10 winnners

BonsAPPs, the EU-funded project that supports small and medium-sized businesses, has announced it’s selected ten winners.

Started in September of last year, BonsAPP’s first Open Call looked to select AI Talents, including researchers, PhDs/postdocs, engineers and data scientists, that would apply the tools available on Bonseyes Marketplace to develop novel AI solutions.

At that time 30 AI talents were selected to solve an industrial AI challenge, with each receiving up to €28,000 for their participation. They presented their results during a hackathon in Bologna, with the strongest 10 AI Talents selected to progress to Stage 2.

Said Jesús Tapia, Head of ISDI Accelerator, “The ten finalists we’ve chosen to accelerate through the first round of this year’s open call represent entities seeking to solve the biggest challenges facing their industries through AI implementation and novel machine learning processes.”

“We are excited to see the solutions proposed by each project integrate into established industry processes to streamline and optimise issues that will benefit consumers, founders, and researchers as the Fourth Industrial Revolution takes flight,” said Miguel de Prado, Senior Researcher at BonsAPPs.

The finalists include:

CHEIRONOM, led by a team of 4 AI Talents from Greece in the quest to improve upon gesture recognition as a safety feature in the Automotive industry.

AUTO-MNET is striving to build MocapNETs (a high performance 2D to 3D single person pose estimator) for improved bodypart tracking in automotive applications, led by a team from Greece’s Foundation for Research and Tech. – Hellas (FORTH).

gAIze, an AI-enabled GAZE detection for lightweight driver monitoring systems that will allow AI systems in cars to know which on-screen element a person is looking at, led by Austrian-based VIRTUAL VEHICLE Research GmbH.

EENAKWS, an energy-efficient, noise-aware keyword spotting initiative for the robotics industry led by Zürich-based D-ITET Center for Project-Based Learning.

AWoid, a project led by Italy’s Elif Lab srl that will solve challenges related to Context-Aware Artificial Intelligence for Collision Avoidance in the robotics industry.

3Dlocator, by Spanish company LOGICMELT TECHNOLOGIES SL will develop novel solutions for object location in 3D space and other object detection challenges in the Manufacturing industry through the use of depth estimation networks.

MNE_OQC is led by 5 AI Talents from Montenegro and will seek to tackle high-speed defect detection in the Manufacturing industry using deep learning. methodologies.

Artificial, led by Artificialy SA from Switzerland, will attempt to solve the remote vital signs challenge in the Health Industry. 

PULSE, led by THINGENIOUS PC from Greece, this project will deal with heart rate detection and estimation in the Health industry via PPG and IMU signal fusion for heart rate estimation.

SensoBody, a project led by Portuguese-based SENSOMATT Lda. that will seek to come up with novel ways to create 3D body detection methods through 2D images.