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.
| Mualliflar | Mahfiza Khabibovna, Razokova, Rashid Amirovich, Absalamov |
|---|---|
| Jurnal | Innovative Multidisciplinary Journal of Applied Technology |
| Nashr sanasi | 2026-05-28 |
| Jild | 4 |
| Son | 4 |
| Betlar | 188-192 |
| Til | Ingliz |
| DOI | 10.51699/pjpnp042 |
DOI: 10.51699/pjpnp042 · Maqolaning asl sahifasi
emergency situations, monitoring, data integration, quality control, multi-hazard approach
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