€8 Million VEDLIoT Project Looks to Use Machine Learning to Improve the Internet of Things

Bielefeld University has announced it is to coordinate a new European Commission project aimed at using machine learning to improve the robustness, power, and energy efficiency of future Internet of Things initiatives ranging from autonomous vehicles to smart homes: Very Efficient Deep Learning in the Internet of Things (VEDLIoT).

"Computer and IoT systems are getting more and more efficient. This is enabling us to solve more challenging problems and accelerate automation in order to improve our quality of life," explains Professor Dr. Ulrich Rückert, VEDLIoT project coordinator. "But the volume of the data that is collected and processed is enormous — and the computing power required for this is very high. In addition, the algorithms are often too complex to quickly generate solutions in an appropriate amount of time."

The core concept of the project, which is being funded by the European Commission to the tune of €8 million (around $9.45 million) over the next three years, is to use deep learning and other machine learning approaches to improve efficiency and performance. "We provide the information," explains engineer Jens Hagemeyer, "the machines learn and decide for themselves."

To support that, the VEDLIoT platform is based on a modular hardware system with "microservers" attached to a flexible carrier. "Depending on the demands of the application, the servers can be individually configured on the carrier, resulting in a platform suitable for universal use," notes Hagemeyer. "If a server fails, e.g., due to a weak wireless network, the entire device can still be operated. In the best case, the user of a self-driving car wouldn’t even notice the server failure."

While the VEDLIoT project already has twelve partners working on it, there's room for more: "We expect to finance at least 10 additional use cases in the context of this project – in addition to the existing applications in the sectors of Automotive, Automation, and Smarthomes," notes project manager Dr. Carola Haumann. "That’s why we want to get more companies involved."

A workshop for project partners is planned for December this year, with a functional prototype scheduled for mid-2022. More information is available on the EU CORDIS system, along with a link to the call for proposals for interested parties looking to apply.