
🌾 Agriculture · Deployment · Pro
Where each part of a precision farming system runs: soil and weather sensors in the field, a solar-powered LoRaWAN gateway, and cloud services for irrigation and advice.
Deployment diagrams are part of Pro. Anyone can view this one; generating and editing it needs Pro.
Drawing diagram…
Deployment for precision farming: soil moisture sensors, a weather station and irrigation valve controllers in the field communicate over LoRaWAN with a solar-powered gateway, which connects over 4G to the cloud. In the cloud: a LoRaWAN network server, an IoT ingestion service, a time-series database, a rules engine that opens and closes valves, a crop advisory service using satellite imagery (NDVI), and a farmer mobile app with SMS alerts.
flowchart TB
subgraph Field[Farm Field]
S1[Soil Moisture Sensors]
WS[Weather Station]
V[Irrigation Valve Controllers]
GW[LoRaWAN Gateway - solar powered]
end
subgraph Cloud[Cloud Region]
NS[LoRaWAN Network Server]
ING[IoT Ingestion Service]
TS[(Time-series DB)]
RULES[Irrigation Rules Engine]
ADV[Crop Advisory Service]
SAT[(Satellite NDVI Imagery)]
API[App API]
end
APP[Farmer Mobile App]
S1 -.LoRa.-> GW
WS -.LoRa.-> GW
GW -->|4G| NS
NS --> ING
ING --> TS
TS --> RULES
RULES -->|Open / close| NS
NS -.LoRa.-> V
SAT --> ADV
TS --> ADV
ADV --> API
API --> APPHow produce moves from the farm to the buyer: harvest, grading, collection centre, mandi or online market, and payment to the farmer.
How satellite and drone imagery plus field sensors become crop health alerts and advice for farmers.
The states of an automated drip irrigation controller: idle, scheduled watering, moisture-based watering, rain delay and fault handling.
How a farmer checks crop prices across nearby mandis and books a sale: live prices, transport cost, best net price and booking.
A schema for a farm management app: farmers, plots, crop cycles, inputs applied, activities and harvests.
A platform farmers use to plan crops, record field work and inputs, and get advisory and market prices.