Coming soon: Next-generation AIoT applications – VEDLIoT-Open Call opens 1 March

VEDLIoT – “Very Efficient Deep Learning in IoT” is driven by challenging use cases in key sectors like automotive, automation, and smart home. The main objective of VEDLIoT is to develop the next generation of connected IoT devices utilising distributed deep learning.

The upcoming funding opportunity, which opens on 1 March, will fund around ten research experiments incorporating additional use cases in the project utilising the developed technologies. The submission deadline is 8 May 2022 at 23:59 CEST.

This open call for cascaded funding is foreseen to explore new opportunities by extending the application of the VEDLIoT platform to a more extensive set of new and relevant use cases. It is expected that open call projects leverage VEDLIoT technologies for their own AI-related IoT use case, thereby broadening the VEDLIoT use-case basis and help making the overall concept more robust.

VEDLIoT -Open Call in a nutshell

For this Open Call, the types of activities to perform that qualify for receiving financial support are the next generation of AIoT applications in areas such as wearables, transportation, agriculture, homes, health, energy, and manufacturing.

Call identifier: VEDLIoT – Open

Call title: Next-generation AIoT applications – VEDLIoT-Open

Publication date: 01/03/2022

Deadline: 08/05/2022 at 23:59h CEST.

Indicative budget for the call: 840.000 €

Expected duration of participation: 9 to 12 months

Indicative budget for each proposal: up to 120,000 € (including 25 % indirect costs, at a funding/reimbursement rate of 70 %)

Language in which proposal must be submitted: English

Official project site:

Questions: vedliot-open-support@vedliot.[eu|ai|io]

All OC-application documents can be found here, starting from 1st of March 2022:

VEDLIoT – “Very Efficient Deep Learning in IoT” is an EU H2020 ICT-56-2020 funded research project by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 957197.