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Conference Paper Exploiting Heterogeneous Monitoring Data for Spatiotemporal Algal Bloom Prediction
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Authors
Taewhi Lee, Miyoung Jang, Jang-Ho Choi, Jongho Won, Jiyong Kim
Issue Date
2022-02
Citation
International Conference on Artificial Intelligence in Information and Communication (ICAIIC) 2022, pp.443-445
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICAIIC54071.2022.9722642
Abstract
Harmful algal blooms need to be mitigated because they can cause significant negative effects to humans and other organisms. If such algal blooms can be predicted in advance by monitoring water quality, they can be suppressed at an early stage by making decisions to take actions. We describe our ongoing work on integrating the heterogeneous water quality monitoring data and on recovering the missing data using tensor completion techniques. We also discuss the challenges in carrying out this study.
KSP Keywords
Bloom prediction, Harmful Algal Blooms, Missing data, Monitoring data, Negative effects, Tensor completion, Water quality monitoring