dr.ing. R. Kromanis (Roland)

Engineering & Materials Science

# Anomaly Detection
# Cameras
# Computer Vision
# Damage Detection
# Hot Temperature
# Monitoring
# Smartphones
# Structural Health Monitoring

Faculty of Engineering Technology (ET), Market Dynamics (MD)

Borah, S., Al-Habaibeh, A. , & Kromanis, R. (2023). Measuring Thermal Response of Bridges Using Vision-Based Technologies and LVDTs. In P. Rizzo, & A. Milazzo (Eds.), European Workshop on Structural Health Monitoring - EWSHM 2022 - Volume 2 (pp. 496-505). (Lecture Notes in Civil Engineering; Vol. 254 LNCE). Springer Science + Business Media. https://doi.org/10.1007/978-3-031-07258-1_51

Lydon, D. , Kromanis, R., Lydon, M., Early, J., & Taylor, S. (2022). Use of a roving computer vision system to compare anomaly detection techniques for health monitoring of bridges. Journal of Civil Structural Health Monitoring. https://doi.org/10.1007/s13349-022-00617-w

Kromanis, R. , & Elias, S. (2022). Measuring Dynamic Response of the Wilford Suspension Bridge with a Vision-Based Measurement System: A Case Study. In P. Rizzo, & A. Milazzo (Eds.), European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 1 (pp. 280-289). (Lecture Notes in Civil Engineering; Vol. 253 LNCE). Springer Science + Business Media. https://doi.org/10.1007/978-3-031-07254-3_28

Voordijk, H. , & Kromanis, R. (2022). Technological mediation and civil structure condition assessment: the case of vision-based systems. Civil engineering and environmental systems, 39(1), 48-65. https://doi.org/10.1080/10286608.2022.2030318

Kromanis, R., & Buchanan, C. (2021). Initial investigations into the thermal response of the first metal 3D printed bridge. In Proceedings of the 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure (pp. 1593-1599)

Borah, S., Al-Habaibeh, A. , & Kromanis, R. (2021). Thermal response measurement of bridges using vision-based monitoring. In Proceedings of the International Conference on Structural Health Monitoring of Intelligent Infrastructure (pp. 1121-1126)

Obiechefu, C. B. , Kromanis, R., Mohammad, F., & Arab, Z. (2021). Vision-Based Damage Detection Using Inclination Angles and Curvature. In C. Rainieri, G. Fabbrocino, N. Caterino, F. Ceroni, & M. A. Notarangelo (Eds.), Civil Structural Health Monitoring: Proceedings of CSHM-8 Workshop (pp. 115-127). (Lecture Notes in Civil Engineering; Vol. 156). Springer. https://doi.org/10.1007/978-3-030-74258-4_7

Kromanis, R. (2021). Characterizing Footbridge Response from Cyclist Crossings with Computer Vision-Based Monitoring. In C. Rainieri, G. Fabbrocino, N. Caterino, F. Ceroni, & M. A. Notarangelo (Eds.), Civil Structural Health Monitoring: Proceedings of CSHM-8 Workshop (pp. 83-95). (Lecture Notes in Civil Engineering; Vol. 156). Springer. https://doi.org/10.1007/978-3-030-74258-4_5

Obiechefu, C. B. , & Kromanis, R. (2021). Damage detection techniques for structural health monitoring of bridges from computer vision derived parameters. Structural Monitoring and Maintenance, 8(1), 91-110. https://doi.org/10.12989/smm.2021.8.1.091

Kromanis, R., & Kripakaran, P. (2021). A multiple camera position approach for accurate displacement measurement using computer vision. Journal of Civil Structural Health Monitoring, 11(3), 661-678. https://doi.org/10.1007/s13349-021-00473-0

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