Projecti-RASE – Intelligent Radiation Sensor Readout System
Basic data
Acronym:
i-RASE
Title:
Intelligent Radiation Sensor Readout System
Duration:
01/03/2024 to 29/02/2028
Abstract / short description:
The i-RASE project aims to design, build, test, and implement the first on-the-fly photon-by-photon radiation detector with transformational potential for various radiation applications, such as medical imaging, industrial inspection, scientific space instrumentation, environmental monitoring, and more.
The i-RASE project will develop physics-inspired artificial neural networks (ANNs) for comprehensive sensor signal processing (SP) and real-time (RT) measurement of radiation interactions. It will compact this technology into an ultimate vision for SP embedded in hardware (HW) as an "all-in-one" SIP, enabling cost- and energy-efficient detection and intelligent radiation data output with unparalleled accuracy and speed. This approach enhances measurement precision and speed by utilizing complex SP, event characterization, and on-the-fly processing of incident radiation-induced signals in near real-time. As a result, it facilitates the retrieval of comprehensive information on incident radiation, ultimately improving measurement accuracy and speed while reducing digital data output.
The i-RASE project will develop physics-inspired artificial neural networks (ANNs) for comprehensive sensor signal processing (SP) and real-time (RT) measurement of radiation interactions. It will compact this technology into an ultimate vision for SP embedded in hardware (HW) as an "all-in-one" SIP, enabling cost- and energy-efficient detection and intelligent radiation data output with unparalleled accuracy and speed. This approach enhances measurement precision and speed by utilizing complex SP, event characterization, and on-the-fly processing of incident radiation-induced signals in near real-time. As a result, it facilitates the retrieval of comprehensive information on incident radiation, ultimately improving measurement accuracy and speed while reducing digital data output.
Keywords:
artificial intelligence
radiation detector
FPGA
Involved staff
Managers
Institute of Astronomy and Astrophysics (IAAT)
Department of Physics, Faculty of Science
Department of Physics, Faculty of Science
Local organizational units
Institute of Astronomy and Astrophysics (IAAT)
Department of Physics
Faculty of Science
Faculty of Science
Funders
Brüssel, Belgium
Cooperations
Kongens Lyngby, Denmark
Milano, Italy