API Documentation

Capture and normalize

Field telemetry, image frames, weather feeds, and site metadata are normalized into one event fabric.

Score and enrich

MosqAI enriches the event with model outputs, thresholds, contextual overlays, and governance metadata.

Publish operational action

Dashboards, alerts, maps, and exports update so analysts and field crews can act from the same signal.

Design intent

The MosqAI API is intended to expose mosquito intelligence that is already normalized, enriched, and context-aware. Consumers should not need to reverse-engineer raw trap telemetry just to answer operational questions.

• Prefer zone and event summaries over raw packet streams
• Keep environmental context attached to operational records
• Support agency, GIS, and research consumers with the same base model

Core resource families

Most integrations start with four resources: traps, zones, alerts, and observations. Together they describe where signals originated, how MosqAI interpreted them, and what operational significance they may carry.

• `traps`: hardware identity, health, and deployment context
• `observations`: species, density, and environmental events
• `alerts`: scored or thresholded events requiring attention
• `zones`: geographic rollups used for reporting and coordination

Recommended integration patterns

Use polling for dashboards and periodic reporting, then enrich downstream systems with MosqAI zone logic rather than re-implementing surveillance semantics outside the platform.

• GIS systems should consume zone and hotspot summaries
• Research pipelines should use event exports with provenance intact
• Operational tools should subscribe to alert state and intervention history

Reliability and governance

API consumers should treat MosqAI as a curated source of mosquito intelligence, not an infinitely mutable data hose. Provenance, timestamps, and contextual fields are included so downstream teams can preserve meaning as data moves.

• Store source timestamps alongside ingestion timestamps
• Do not discard zone and weather context when exporting
• Retain lineage metadata when generating third-party reports

Is the API meant for real-time dashboards or bulk export?

Both, but through different access patterns. Most operational dashboards consume summarized resources, while research or archival systems usually work from scheduled exports that preserve more lineage and context.

Should downstream systems recalculate mosquito risk?

Usually no. MosqAI is designed to provide already-interpreted surveillance outputs. Recalculating outside the platform often drops context and creates competing definitions of the same event.

How opinionated is the data model?

Intentionally opinionated enough to keep mosquito intelligence usable. The API aims to reduce ambiguity, not expose a bag of disconnected sensor fields.