A MODEL FOR THE INTEGRATION OF MULTI-SOURCE DATA AND AUTOMATIC QUALITY CONTROL IN EMERGENCY-SITUATION MONITORING
DOI:
https://doi.org/10.51699/pjpnp042Keywords:
emergency situations, monitoring, data integration, quality control, multi-hazard approachAbstract
This article proposes a model for converting multi-source heterogeneous data into a single format and automatically controlling its quality in the monitoring of emergency situations (ES). The model covers five sources (seismic, hydrometeorological, satellite, IoT-sensor, and institutional) and performs range checking, missing-value and duplicate detection, unit normalization, statistical outlier detection (IQR), and domain-specific reliability checks. The model was tested on real open data — 267 records from the USGS earthquake catalog: 88.4% of records were recognized as valid, while 31 records (including 29 of low reliability — azimuthal gap > 180°) were automatically flagged. The results show that the model performs identically on real and simulated data and provides clean, ready input for a forecasting model.
References
1. United Nations Office for Disaster Risk Reduction (UNDRR). Sendai Framework for Disaster Risk Reduction 2015–2030. Geneva, 2015. undrr.org
2. Tiggeloven T., Pfeiffer S., Matanó A. et al. The role of artificial intelligence for early warning systems: status, applicability, guardrails // iScience. 2025. Vol. 28, no. 11. Art. 113689. DOI: 10.1016/j.isci.2025.113689
3. Du S., Chen S. A multi-sensor data fusion algorithm based on consistency preprocessing and adaptive weighting // Automatika. 2023. Vol. 65, no. 1. P. 82–91. DOI: 10.1080/00051144.2023.2284033
4. Wang M., Zhang Q., Liu X. et al. Research progress on multimodal data fusion in forest resource monitoring // Frontiers in Plant Science. 2026. Vol. 16. DOI: 10.3389/fpls.2025.1710618
5. Haruna M., Kotopulos De Angelis F., Gebremeskel K.G. et al. Sensor fusion-based machine learning algorithms for meteorological conditions nowcasting in port scenarios // Sensors (MDPI). 2025. DOI: 10.20944/preprints202510.1802.v1
6. Ghaffarian S. Rethinking digital twin: introducing digital risk twin for disaster risk management // npj Natural Hazards. 2025. Vol. 2, no. 1. DOI: 10.1038/s44304-025-00135-x
7. Leong W. Internet of Things for enhancing public safety, disaster response, and emergency management // Engineering Proceedings (MDPI). 2025. Vol. 92, no. 1. Art. 61. DOI: 10.3390/engproc2025092061
8. U.S. Geological Survey (USGS). Earthquake Catalog (FDSN web service). URL: earthquake.usgs.gov