Dr Susan Rea
Research Fellow & Group Lead
Susan Rea is a Group Lead for Network Management and Principle Investigator at the Nimbus Centre at Cork Institute of Technology where her current research interests focus on IoT & CPS, specifically embedded infrastructure management using distributed ledger technology and cybersecurity for large scale next generation networks.
Susan is an Athena Swan champion and advocate for the promotion of women in STEM and is actively engaged with a wide network across the HEI sector to support her commitment to leading and advancing gender inequality in CIT.
Susan Rea is a Group Lead for Network Management and Principle Investigator at the Nimbus Centre at Cork Institute of Technology where her current research interests focus on IoT; CPS, specifically embedded infrastructure management using distributed ledger technology and cybersecurity for large scale next generation networks. Susan is an Athena Swan champion and advocate for the promotion of women in STEMM and is actively engaged with a wide network across the HEI sector to support her commitment to leading and advancing gender inequality in CIT.
Susan holds a PhD in Electronic Engineering from Cork Institute of Technology. Her thesis was entitled “Dynamic Route Management
Strategies for Mobile Ad Hoc Networks” and a MENG from Cork Institute of Technology having investigated “Uniform Random Number Generation Using Pseudorandom Binary Sequences”. She also holds a Diploma in Project Management, from Cork Institute of Technology, a MSc in Information Theory, Coding; Cryptography, University College Cork, (1999) and a Bachelor of Engineering in Electronic Engineering, Cork Institute of Technology (1998).
Roshany-Yamchi, K. Witheephanich, J. Manuel Escano, A. McGibney, S. Rea. 2017. Selective Distributed Model Predictive Control for Comfort Satisfaction in Multi-Zone Buildings. ICSTCC 2017 – 21st International Control on System Theory, Control and Computing, Sinaia, Romania
Marfievici, P. Corbalan, D. Rojas, A. McGibney, S. Rea, D. Pesch. 2017. Tales from the C130 Horror Room: A Wireless Sensor Network Story in a Data Center. In Proceedings of the 1st ACM International Workshop on the Engineering of Reliable, Robust, and Secure Embedded Wireless Sensing Systems (FAILSAFE), pp.23-30
McGibney, A.; Pusceddu, D.; Rea, S.; Pesch, D.; Geron, M. & Keane, M. (2012), A methodology for sensor modeling and placement optimization to support temperature monitoring., in George J. Pappas, ed., ‘BuildSys@SenSys’ , ACM, , pp. 88-90 .
Guinard, A.; Aslam, M. S.; Pusceddu, D.; Rea, S.; McGibney, A. & Pesch, D. (2011), Design and deployment tool for in-building wireless sensor networks: A performance discussion., in Chun Tung Chou; Tom Pfeifer & Anura P. Jayasumana, ed., ‘LCN’ , IEEE Computer Society, , pp. 649-656 .
Aslam, M. S.; Guinard, A.; McGibney, A.; Rea, S. & Pesch, D. (2011), Wi-design, Wi-manage, why bother?, in Nazim Agoulmine; Claudio Bartolini; Tom Pfeifer & Declan O’Sullivan, ed., ‘Integrated Network Management’ , IEEE, , pp. 730-744 .
Wallace, J.; Rea, S.; Pesch, D. (2005), Fuzzy Logic Optimization of MAC Parameters and Sleeping Duty-Cycles in Wireless Sensor Networks., in Proc. of IEEE 62nd Bi-Annual Vehicular Technology Conference.
INSPEX- Integrated Smart Spatial Exploration System
The INSPEX objective is to develop a portable/wearable, multi-sensor, miniaturised, low power spatial exploration system. The INSPEX system will be used for real-time, 3D detection, location and warning of obstacles under all environmental conditions in indoor and outdoor environments with unknown static and mobile obstacles. INSPEX use applications include mobility for the visually impaired, safer human navigation in reduced visibility conditions (smoke, dust, fog, heavy rain/snow, darkness or combinations of these), small robot/drone. The INSPEX system will adapt obstacle-detection capabilities common in autonomous cars for portable and wearable applications including guidance for the visually impaired and blind, robotics, drones and smart manufacturing. It will be used for real-time, 3D detection, location and warning of obstacles under all environmental conditions. These include smoke, dust, fog, heavy rain/snow, and darkness, and in indoor and outdoor environments with unknown stationary and mobile obstacles.
This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement no 730953.
This work was supported in part by the Swiss secretariat for education, research and innovation (SERI) under grant 16.0136 730953.
SFI Centre for Research Training in Advanced Networks for Sustainable Societies: “ADVANCE CRT”
DIGIBLOCKS (SEAI RD; 2018, 18/RDD/262)
Trusted IoT Energy Ecosystems; Robust Wireless Automation for
Factories of the Future
Start Q4 2019 under SFI ADVANCE CRT (working titles): Mobile Trust for IoT;
Gender Analysis for IoT Ecosystems; Personalised; Connected Healthcare