CIDSA Smart Crop Analytics AI
Models that read every leaf.
Module Role
AI-driven crop insights and predictions
Smart Crop Analytics AI runs computer-vision and time-series models across satellite, drone, and ground-image streams to detect anomalies the human eye misses. Output is one number per block: a crop-health index updated daily, with the contributing factors broken out so the agronomist knows what to fix.
CIDSA Analytics · Akasha
Model Confidence & Insights
60 farms · 1.4 M observations
Model AUC
0.93
health classifierYield MAE
6.4%
per blockAnomaly lead
9.2 days
vs. visibleFalse alarms
< 3%
What this module delivers
Crop health index · 60-day trend
0-100 across 4 sample blocks
- Block A
- Block B
- Block C
- Block D
Anomaly type mix
Last 90 days
- Disease
- Nutrient
- Other
- Pest
- Water
Predicted vs. realised yield
q/acre · 12 blocks
- Actual
- Predicted
CIDSA Smart Crop Analytics AI
Snap or upload a photo of your crop, tell us what it is, and the CIDSA Agri-Bot (powered by Claude Sonnet 4.5) returns a ranked disease / pest / stress verdict with a smallest-intervention management plan. Prefer to answer questions instead? Use the guided flow below.
JPEG / PNG / WEBP · up to 6 MB. On mobile, “Take a photo” opens the rear camera directly.
Your photo will appear here
Attach one to run the AI diagnosis
No photo handy? Answer three quick questions and get the most likely stress, disease or pest — same knowledge base, no image required.
Related Akasha modules
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DataCIDSA Agri Digital Asset Hub
Centralized farm data and asset management
PathologyCIDSA Crop Stress & Disease Intelligence
Early detection of crop stress and diseases
LifecycleCIDSA Crop Lifecycle Management Pro
End-to-end crop lifecycle tracking