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Documentation Index

Fetch the complete documentation index at: https://docs.appliedaifoundation.org/llms.txt

Use this file to discover all available pages before exploring further.

The platform persists everything in PostgreSQL (Google Cloud SQL). Three tables drive the whole experience:

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1. Vessels

common_vessel_details (configurable via TABLE_VESSELS) One row per vessel:
  • imo — primary key
  • vesselName
  • vesselType — used for CII ship-type mapping (e.g. “Container”, “Crude Oil Tanker”)
  • Fleet, manager, operational status, classification society — soft metadata

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2. Consumption logs

common_consumption_log (configurable via TABLE_CONSUMPTION) The heart of the system. One row per reporting period (typically 1 record per day per vessel). 40+ fields covering:
  • Identity: imo, voyageName
  • Time: timestampUtc (always UTC)
  • State: event (BOSP / EOSP / etc), state (In Port / At Sea)
  • Ports: portOfOrigin + portOfOriginUnloc, portOfDestination + portOfDestinationUnloc
  • Position: lat, lng
  • Distance: distanceOverGroundNm
  • Speed: averageSpeedOverGroundCorrectedKn
  • Emissions: totalCo2T plus breakdowns
  • Fuel: totalFocT plus by-type (HFO HS/LS, LFO, MDO, MGO, LNG, methanol, biofuel)
  • CII (if pre-computed by source): ciiAttainedGTNmCo2, ciiRequired, ciiRating
  • Cargo: cargoWeightT, cargoTeu
  • Reefer: activeReefers
Indexed on imo and timestampUtc for the fleet-wide queries that drive the dashboard.

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3. Vessel particulars

vessel_particulars_data (configurable via TABLE_PARTICULARS) Rich vessel-master data — DWT, GT, flag, engine type, build year, classification society, etc. Stored as a JSONB array of name/value pairs (vesselParticulars column). The platform extracts specific fields on demand using helpers like getDWTFromParticulars() and getGrossTonnageFromParticulars(). This is what feeds the EU MRV report vessel header and informs CII calculations when a precise DWT is needed.

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What’s deliberately not stored

  • Pre-computed yearly summaries. The platform computes everything on demand (with React Query caching) so a single source of truth exists. No risk of drift between reports and dashboards.
  • User accounts. No authentication layer is implemented in this build.
  • Audit logs. No history of changes is kept; data is treat-as-read after upload.

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Source

  • Schema: there’s no SQL DDL in the repo — tables are managed externally and connected via the configurable names above
  • Models: src/lib/models/VesselParticulars.ts (helpers for the JSONB particulars column)
  • Connection: src/lib/db/postgres.ts
  • Table names: src/lib/db/tables.ts