The web-enabled awareness research network (WARN) project early earthquake and tsunami warning at Ocean Networks Canada
Notice bibliographique
Résumé
The Web-enabled Awareness Research Network project (WARN) implements the data acquisition, event detection and correlation aspects of an integrated geo-hazard alert system. Among its innovative aspects, it enables a rapid integration of real or simulated data with research and operational models of tsunami and earthquake impacts prediction. The intent of the project is to lead to the delivery of early warning to urban areas, coastal communities and key infrastructure operators. Figure 1 provides the overview of a generic alert system toplevel architecture and situates WARN in this context. WARN relies on the existence of sensors installed both underwater and on land. Warn also relies on data acquisition performed by Ocean Networks Canada's Oceans 2.0 data management system. Event detection/correlation are the key parts of WARN. The Ocean Networks Canada (ONC) infrastructure, consisting among other assets of the NEPTUNE and VENUS observatories around Vancouver Island in British Columbia is host to the various sensors required to perform the detections. The sensors include, but are not limited to, accelerometers (installed off- and on-shore), coastal radars to detect incoming near-field tsunami waves, bottom pressure recorders and other underwater pressure sensors to complete the network. This infrastructure can be expanded geographically both on land and WARN takes the quasi real-time data sources and performs on-the-fly identification and filtering of telltale signs of earthquakes and tsunamis in each individual data stream. The individual detections are subsequently matched against those obtained from different sensors during a constrained time window. This coordination of events avoids false positives and allows for the calculation of an epicentre and of a magnitude assessment in the case of an earthquake; or of a direction, speed and amplitude in the case of a tsunami. WARN's specification is to perform all detections and confirmation calculations within 2 seconds for earthquake and 2 minutes for tsunamis. Running impact assessment models is not in WARN's scope. Impact assessments are the subject of other projects in and outside of ONC. Those models are however the primary consumers of confirmed events as detected by WARN. The models use WARN's event notifications as triggers to quickly look up databases of pre-calculated impacts scenarios and notify authorities of the predicted impact. Notification of detected events are transmitted in the XML-based “Common Alerting Protocol” (CAP) format (see www.oasis-open.org/standards#capv1.2). This data payload structure (adapted to Canada's standard CAP-CP) is transmitted following a publisher-subscriber model. This project is supported in full by CANARIE Inc. (www.canarie.ca), through its Network-Enabled Platform program.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».