We developed a production-ready IoT smart farming system deployed across multiple agricultural sites, integrating over 200 IoT sensors per farm including soil moisture sensors (capacitive and tensiometric), NPK sensors, pH meters, weather stations, and crop imaging cameras. The platform collects sensor data every 15 minutes via LoRaWAN gateways and cellular backup, processing over 50,000 data points daily per farm. Real-time dashboards display soil moisture maps, weather forecasts, crop growth indices (NDVI), and irrigation status. Automated irrigation controllers activate based on soil moisture thresholds, weather predictions, and crop water requirements. Machine learning models trained on 3+ years of historical data predict optimal irrigation schedules, detect early signs of disease through leaf analysis, and recommend fertilizer application timing. The system integrates with existing farm equipment via Modbus RTU and CAN bus protocols. Mobile apps enable farmers to receive push notifications for critical alerts and remotely control irrigation zones. Edge computing nodes process data locally during connectivity outages, with automatic synchronization when connection is restored. The platform supports multiple crop types (corn, wheat, tomatoes, lettuce) with crop-specific algorithms and thresholds.