Offline AI

The scan does not depend on a live cloud connection.

CropVox is designed so the essential crop identification, visible-symptom analysis, guidance lookup and selected speech output can run locally on the device.

Offline flow

The core path stays inside the device.

This architecture reduces latency and keeps the system usable across farms where mobile data is weak or unavailable.

1. CameraCapture crop image
2. Vision modelAnalyze crop and symptoms
3. ConfidenceEstimate reliability
4. Guidance libraryRetrieve curated next steps
5. SpeechPresent text and local-language audio
What remains offline

A farmer can still complete the practical field workflow.

CropVox keeps essential models, guidance content and scan records on local storage. The exact model package can vary by device generation and supported crop catalogue.

Vision

Crop and condition inference

Supported models run locally on edge hardware.

Knowledge

Stored field guidance

Curated recommendations can be retrieved without the internet.

Access

Local-language output

Selected language packs and speech assets can remain available on-device.

When connectivity returns

Online access expands the system instead of enabling the basic scan.

Connected operation can synchronize field records, download updated models and guidance, submit difficult cases for review, and contribute permissioned data to larger crop-health analytics.

  • Model and knowledge-base updates
  • Cloud backup and fleet synchronization
  • Expert review for uncertain cases
  • Regional crop-health analytics
  • Optional stronger cloud inference
CropVox in a cassava field