TY - GEN
T1 - IRES Program in Sensors and Machine Learning for Energy Systems
AU - Jaskie, K.
AU - Martin, J.
AU - Rao, S.
AU - Barnard, W.
AU - Spanias, P.
AU - Kyriakides, E.
AU - Tofis, Y.
AU - Hadjidemetriou, L.
AU - Michael, M.
AU - Theocharides, T.
AU - Hadjistassou, S.
AU - Spanias, A.
N1 - Funding Information:
ACKNOWLEDGEMENTS This program was supported in part by the NSF IRES program award 1854273. Logistical support was provided by the ASU SenSIP center and the UCy KIOS center.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/7/15
Y1 - 2020/7/15
N2 - The international research experiences for students (IRES) program addresses multidisciplinary research at the overlap of sustainability, power systems, and signal processing with the aim of improving efficiency in PV power generation. The IRES program engages faculty at the ASU SenSIP Center and at the University of Cyprus' (UCy) KIOS Center to address fault detection and other research problems in solar energy arrays. IRES participants are tasked with studying algorithms and software to monitor and control solar arrays. Research involves using data from programmable sensors embedded in smart monitoring devices (SMDs) that are attached to solar panels. The SMDs have sensors, actuators and radios that enable researchers to work with a solar array where every panel provides data. IRES participants are trained to use machine learning to assess the solar array condition. The program also trains the students to perform research and present results in international settings. In the first year of the project, four students travelled to the University of Cyprus and worked with UCy faculty on fault detection. The program included weekly research presentations by the students at UCy, presentations at a local workshop and continued engagement after the summer experience at ASU. Two of the students were able to present and publish their work in international conferences.
AB - The international research experiences for students (IRES) program addresses multidisciplinary research at the overlap of sustainability, power systems, and signal processing with the aim of improving efficiency in PV power generation. The IRES program engages faculty at the ASU SenSIP Center and at the University of Cyprus' (UCy) KIOS Center to address fault detection and other research problems in solar energy arrays. IRES participants are tasked with studying algorithms and software to monitor and control solar arrays. Research involves using data from programmable sensors embedded in smart monitoring devices (SMDs) that are attached to solar panels. The SMDs have sensors, actuators and radios that enable researchers to work with a solar array where every panel provides data. IRES participants are trained to use machine learning to assess the solar array condition. The program also trains the students to perform research and present results in international settings. In the first year of the project, four students travelled to the University of Cyprus and worked with UCy faculty on fault detection. The program included weekly research presentations by the students at UCy, presentations at a local workshop and continued engagement after the summer experience at ASU. Two of the students were able to present and publish their work in international conferences.
KW - IRES
KW - fault detection
KW - machine learning
KW - radial basis networks
KW - solar energy
UR - http://www.scopus.com/inward/record.url?scp=85099207183&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099207183&partnerID=8YFLogxK
U2 - 10.1109/IISA50023.2020.9284359
DO - 10.1109/IISA50023.2020.9284359
M3 - Conference contribution
AN - SCOPUS:85099207183
T3 - 11th International Conference on Information, Intelligence, Systems and Applications, IISA 2020
BT - 11th International Conference on Information, Intelligence, Systems and Applications, IISA 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Information, Intelligence, Systems and Applications, IISA 2020
Y2 - 15 July 2020 through 17 July 2020
ER -