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AgriSense AI
Divine Intelligence for Farmer Prosperity
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โ–ธ PREDICTIVE RISK DASHBOARD

๐ŸŽฏ Know the loss before it happens.

Six AI models continuously score your farm against six risks โ€” crop failure, rain damage, market crash, storage spoilage, pest outbreak, water shortage. Each ring shows current risk + preventive actions in Telugu.

โš–๏ธ Risk rings ยท your farm ยท 22 May 2026

Ramesh Reddy ยท 2.5 ac ยท Madikonda ยท Warangal ยท paddy + turmeric

78%

๐ŸŒง๏ธ Rain damage

URGENT

Hailstorm Thu 14:00. Your 12 q paddy on bund. Move to drying marketplace within 4 hours.

40%

๐Ÿ’ง Water shortage

Watch

Groundwater dropped 8 m last 90 days. Switch to AWD irrigation now to save 22% water.

31%

๐Ÿ“‰ Market crash

Watch

Mandi arrivals up 38% this week. Sell within 14 days or expect โ‚น120/q drop.

12%

๐ŸŒพ Crop failure

Low

NDVI healthy (0.78). Yield projection 11% above 5-year mean. Stay course.

16%

๐Ÿฌ Storage spoilage

Low

Moisture 12.4%. RH 62%. AI spoilage score 0.08. Safe for 9 months.

37%

๐Ÿ› Pest outbreak

Watch

Brown plant-hopper rising in adjacent villages. Apply preventive spray within 5 days.

โšก Preventive actions in order of priority

๐ŸŒง๏ธ
Move paddy to covered drying
Hailstorm 14:00 ยท 12 q exposed ยท 4 hours window
Save โ‚น38,400
Book drying โ†’
๐Ÿ’ง
Switch to AWD irrigation today
Alternate Wetting & Drying โ€” saves 22% water, no yield loss
Save 1.8 lakh L
AWD guide โ†’
๐Ÿ“‰
List 8 q paddy on auction this week
Best buyer Kohinoor at โ‚น2,290/q ยท close within 14 days
Lock โ‚น18,320
Open auction โ†’
๐Ÿ›
Preventive Imidacloprid spray
0.5 ml/L ยท drone spray โ‚น450/ac ยท 3 days from now
Avert 15% damage
Services

๐Ÿง  The risk stack

Six models run in parallel: Random Forest for crop failure (weather ร— variety ร— soil), Logistic + GraphCast for rain damage, XGBoost on mandi arrivals for market crash, LSTM on IoT moisture for storage spoilage, EfficientNet-V2 on phone photo + neighbour cluster for pest outbreak, and a Random Forest on CGWB aquifer + rainfall + draft for water shortage. Each model retrains weekly on accruing data.