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AgriSync v2.0 โ€” Archive

The field finally speaks data.

Version 2.0 introduced the Field Digital Twin โ€” a 10m spatial grid of the entire farm from one sensor node plus satellite data. A self-calibrating feedback loop improves model accuracy every month on the specific field.

Explore

The AgriSync v2.0 Pipeline

7-layer architecture introducing the Field Digital Twin and satellite data fusion.

sensors 01 / Sensing

Multi-Modal Field Node

Sensors measurig from a single node at field centroid.

settings_input_antenna 02 / Transmission

LoRa Connectivity

Direct LoRa up link, Local buffering during connectivity gaps.

satellite 03 / Satellite Feeds

Multi-Source Data Assimilation

Sentinel-1 SAR soil moisture through cloud cover every 6 days. NASA POWER API for ET0 and solar radiation.

grid_on 04 / Field Digital Twin

Spatial Intelligence Layer

SRTM DEM topographic model builds a 10m x 10m grid of the entire field.

science 05 / Physics Engine

Hard Constraint Layer

Penman-Monteith equation computes reference evapotranspiration per zone. Van Genuchten model simulates soil moisture movement.

psychology 06 / ML Ensemble

Weighted Prediction Stack

LSTM neural network for 12h and 72h time-series forecasting.

notifications_active 07 / Output

Dashboard + Fast2SMS Alerts

Threshold-triggered SMS alerts via Fast2SMS with cause explanation.

Prediction v2.0

The AgriSync
Intelligence Stack

Three independent ML models fused through a weighted ensemble. Disease risk predicted per 10m zone. Self-calibrating via Sentinel-2 NDVI validation and farmer SMS feedback.

72h

Forecast Horizon

90%

Accuracy Target

v2.0

Archive

3

ML Models

neurology

Weighted Ensemble Active

3 Models ยท Self-Calibrating ยท v2.0
Model 01

LSTM

72-hour time-series forecasting of soil and atmospheric conditions across the growing season.

Model 02

XGBoost

Disease risk classification per field micro-zone. Trained on synthetic ICAR thresholds plus accumulating real field data.

Model 03

MobileNetV2 CNN

Leaf disease detection from ESP32-CAM. Pre-trained on PlantVillage Brassica dataset. Runs on Raspberry Pi 5.

The Resolve

Built from a village,
designed for millions.

cottage

Hyper-local Roots

Born from the practical needs of rural farming communities, where internet is a luxury and precision is a necessity for survival.

language

Global Scalability

A platform-agnostic architecture designed to scale from a single backyard plot to thousand-acre commercial plantations.

handshake

Democratized Tech

Reducing the cost of entry for precision agriculture. High-end intelligence accessible to anyone with a browser and a sensor.

developer_mode
Integrated Logic
Archive โ€” v2.0
Status: Archive โ€” superseded by v3.0

Field intelligence,

the groundwork.

The Foundation for v3.0.

v2.0 introduced the Field Digital Twin and satellite data fusion. Self-calibrating AI that improves every month on your specific field. The groundwork for v3.0.

Under the Hood

The AgriSync v2.0 Stack

memory ESP32
sim_card SIM7600G
developer_board Raspberry Pi 5
database MongoDB Atlas
cloud Azure IoT Hub
model_training TensorFlow Lite
auto_awesome XGBoost
satellite_alt Sentinel-2
wb_sunny NASA POWER
sms Fast2SMS
terminal Python 3.11

Ready to sync your field?

Join the movement of digital agronomists transforming global food security through data-driven resolve.

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