Smart Agriculture IoT Platform — Precision Farming with LoRa & AI
A LoRa mesh precision farming system covering 5km² per gateway with soil NPK sensors, automated drip irrigation, on-device crop disease AI, and a multilingual app — deployed across 12 farms in Punjab.
⚠The Problem
Smallholder farmers in rural Punjab had no access to precision agriculture tools. Irrigation was done on fixed schedules — either too early (waterlogging) or too late (crop stress). Soil nutrient levels were unknown, leading to over-fertilization costing ₨40,000 per acre per season. Crop disease was identified only after visible damage — typically 7–10 days after onset, when 20–40% of yield was already lost. Cellular connectivity was absent in most fields.
💡Our Solution
We deployed ESP8266 sensor nodes on LoRa mesh (no cellular required). Each node measures soil moisture at 3 depths, NPK levels, soil temperature, and local microclimate. A Dragino gateway per 5km² bridges LoRa to MQTT/AWS IoT Core via GSM. A TinyML model running on the ESP8266 analyzes NPK ratios and moisture patterns to detect early disease signatures — alerting farmers 5–7 days before visible symptoms. Automated relay triggers drip irrigation when soil moisture drops below the crop-specific threshold. The Flutter app provides full offline-first operation in Urdu and English.
🔗System Architecture
ESP8266 Nodes (LoRa) → Dragino Gateway → AWS IoT Core → Lambda → InfluxDB + Firebase → Flutter AppTech Stack
- ESP8266 sensor nodes
- NPK soil sensor
- Soil moisture & temperature probe
- Davis weather station
- LoRa gateway (Dragino LPS8)
- Drip irrigation actuator relay
- Solar power + lithium battery
- LoRa 868MHz mesh
- MQTT to AWS IoT Core
- GSM fallback for gateways
- AWS IoT Core + Rules Engine
- Firebase (mobile sync)
- InfluxDB (sensor history)
- Python ML service (disease detection)
- Flutter app (iOS + Android, Urdu + English)
- React admin dashboard
- Automated irrigation scheduling UI
Key Features
Results Delivered
- 38% reduction in water usage from precision irrigation
- 25% reduction in fertilizer cost from NPK-guided application
- Crop disease detected 6 days earlier on average vs. visual inspection
- 5km² coverage per LoRa gateway — entire farm covered with 1–2 gateways
- Deployed across 12 farms, 850+ sensor nodes active
Technologies
Who This Is For
Agricultural cooperatives, large farms, agritech companies, government agriculture departments
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Frequently Asked Questions
What technology does this smart agriculture iot platform use?+
Smart Agriculture IoT Platform — Precision Farming with LoRa & AI is built on ESP8266, LoRa, Flutter, Firebase, TinyML. The stack was chosen for real-world reliability in a production deployment — full details are in the tech stack section.
Can CodeCaracal build a similar system for us?+
Yes. The same team that designed and deployed this agriculture / precision farming system takes on new projects across the stack — firmware, connectivity, cloud and dashboards. Tell us your requirements and we will architect a solution for your environment.
Is this case study a real deployed system?+
Yes — every case study on this site describes a production system we designed and shipped. The problem, architecture, features and metrics are from the actual deployment.
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