Research Projects

What is next???

Security.AI: security from the sensor to the cloud. Top notch solutions involving FPGAs, IoTs, and Edge(Raspberry Pi and SnapDragon)

Towards a Universal Stethoscope: beyond StarTrek Tech. But first heart and brain.

Cardiobell+AI: AI+PCG for congenital heart disease detection for neonates. Presented at EAPS 2022.

Sonification+AI: Sonification + AI + visualisation of EEG for improved seizure detection, EDGE computing like no other. Lowest power CNN inference and AI-assisted sonification reported at IEEE IWASI 2023

Neurobell(2016-2022): Acquisition of EEG using low power platforms, AI on microcontrollers. Ultra low power implementation on Ambiq Apollo3 microcontroller (02/2019, Marie Laure Chiodin, Tharmika Sathirupan), ultra low power(16.5mA) CNN inference implementation on STM32 Microcontroller (01/2020, Alan Power), scalable low energy CNN inference on FPGA(09/2020, Alan Power) 

i-RISC: Innovative, Reliable Chip Designs from Unreliable Components (FP7 FET-Open): collaborative project with ENSEA, CEA-LETI, UPT, U. Nis, TU Delft.

i-BEES: Intelligent Bee Hives using Wireless Sensor Networks (Irish Research Council): collaborative project with Dr. Padraig Whelan, School of BEES. 

i-LUX: Intelligent Lighting Systems using Wireless Sensor Networks (Irish Research Council + Verde-Led)

ECO: Marine Energy Control and Optimisation using Embedded Systems (SFI Marei Centre + Analog Devices)

Genesi: Green Sensor Networks for Structural Monitoring (FP7 STREP): collaborative project with Tyndall.

U-Play2: Unified Networks for Playing with Toys for Children with Disabilities (looking for funding partners): collaborative project with applied psychology(Prof. John McCarthy), and education(Dr. Mary Horgan, Prof. Kathy Hall)

iBAN-Med: Intelligent Body Area Networks for Medical Applications (Enterprise Ireland): collaborative project with Dr. Liam Marnane(EEE), Dr. John O'Donoghue(BIS)

Low Power Design for Systems on a Chip and Networks on a Chip (Synopsys): a collaborative project with Prof. Michel Schellekens(CEOL, CS)

CEOL: Efficiency Oriented Languages/Design for Predictable Performance: a collaborative project with Prof. Michel Schellekens(CEOL, CS)