Transform your fish farming operation with this cutting-edge n8n workflow that combines Indonesia's official BMKG weather data with IoT-powered feeding automation. This system intelligently reduces feed by 20% when rain probability exceeds 60%, preventing overfeeding during adverse weather conditions that could compromise water quality and fish health.
🌦️ Real-time BMKG Integration: Fetches official Indonesian weather forecasts every 12 hours using BMKG's public API with precise ADM4 regional targeting
🤖 Smart Decision Engine: Advanced JavaScript algorithms analyze 6-hour and 12-hour rain probabilities to make optimal feeding decisions automatically
📱 ESP8266 IoT Control: Seamlessly sends HTTP webhook commands to your ESP8266/ESP32-based fish feeder hardware with JSON payloads
💬 Rich Telegram Notifications: Comprehensive reports including weather analysis, feeding decisions, hardware status, and next feeding schedule
⏰ Precision Scheduling: Automated execution at 05:30 and 16:30 WIB (Indonesian Western Time) with cron-based triggers
📊 Activity Logging: Complete audit trail with timestamps, weather data, and feeding decisions for operational monitoring
Core Node Components:
✅ n8n Instance: Self-hosted or cloud deployment
✅ Telegram Bot: Create via @BotFather for notifications
✅ ESP8266/ESP32: Hardware with servo motor for automated feeding
✅ Arduino Skills: Basic programming knowledge for hardware setup
✅ Indonesian Location: Uses BMKG API with ADM4 regional codes
📍 Location Settings: Update latitude, longitude, and BMKG ADM4 code in the Config node
🤖 Telegram Bot: Configure bot token and chat ID in credentials
🔗 ESP8266 Webhook: Set your device's IP address for hardware communication
📊 Feeding Parameters: Customize rain threshold (default: 60%) and feed reduction (default: -20%)
🏭 Commercial Aquaculture: Large-scale fish farming operations requiring weather-aware feeding
🏠 Hobbyist Enthusiasts: Home aquarium and pond automation projects
🌱 Smart Agriculture: Integration with comprehensive farm management ecosystems
🔧 IoT Learning: Educational platform for weather-based automation development
🌍 Environmental Research: Combining meteorological data with livestock care protocols
The workflow generates detailed Telegram reports featuring:
Designed for ESP8266-based feeders accepting HTTP POST commands. The workflow transmits structured JSON containing:
{
"command": "FEED_REDUCE_20",
"feed_ratio": -20,
"rain_prob": 75,
"timestamp": "2024-09-18T10:30:00Z",
"location": "Main Pond"
}
Indonesia-Optimized: Built specifically for BMKG's official weather API with ADM4 regional precision
Global Compatibility: Easily adaptable for international weather services by modifying HTTP requests and parsing logic
Scalable Architecture: Supports multiple pond locations with separate ADM4 configurations
{{PLACEHOLDER}} format for secure credential management