The Ray Deep Project – Cosmic Ray Detection using Deep Learning (A DIH4AI Experiment) seeks to use Deep Learning techniques and FPGA technology to develop an autonomous system that can monitor cosmic ray activity in real time.

Project objectives

The main objective is to detect ionizing particles from cosmic rays, such as muons, electrons and photons, through image processing. The system will use convolutional neural networks implemented in FPGA devices to achieve high-speed analysis in less than 50 ms.

The project has a triple impact on the scientific, industrial and societal community, strengthening existing databases, supporting autonomous systems and crews exposed to radiation, and enabling muon tomography.

By combining FPGA technology with Deep Learning models, it will be possible to generate real-time alerts on increases in cosmic ray activity and generate routes to avoid areas of high activity, which can have a significant impact on the health and safety of people and control systems.

Potential additional applications of project results:

  • Control of autonomous vehicle connectivity failures
  • Incidence on sensitivity of quantum computers

Project partners

ADA AI Solutions

Project leader

This consortium involves the union of a spanish start up technology provider, supported by an AI expert knowledge center (ITCL Technology Center), a regional DIH integrated in DIGIS3 EDIH (DIHBU), with a valuable industrial ecosystem that provides support to the SME, and CeADAR, leader of EDIH Ireland, to provide technical mentoring and technical support for testing and validation.


DIH4AI Grant agreement: 101017057

  • Duration: may 2023-nov 2023
  • Total budget: 115.687 €
  • Maximum aid intensity: 70% to ADA AI, 100% to DIHBU and CeADAR
  • Total funding: 93.937 €
  • Specific funding granted to DIHBU: 25.250 €

Project team at DIHBU

DIHBU news related to the project

RAY DEEP: Video – Project progress & results- October 2023

See all DIHBU funded projects