Analyzing Farm Data for Better Decisions

📊 Analyzing Farm Data - From Numbers to Action

📈 How to Use Your Sensor Data:

📊 Example Analysis - Tomato Farm:

Data for past week:
- Soil moisture: Average 35% (below 55% threshold)
- Temperature: Average 28°C (optimal range 20-25°C)
- Humidity: Average 45% (optimal 65-75%)
- Rain detected: None

Actions taken:
1. Increased irrigation frequency (was every 3 days, now daily)
2. Added shade cloth to reduce temperature
3. Installed misters to increase humidity

Results after 1 week:
- Soil moisture: 65% ✓
- Plant stress reduced ✓
- New growth visible ✓

📊 Key Metrics to Track:

Water usage trend: Are you saving water compared to last month?
Crop yield correlation: Does higher moisture always mean better yield?
Weather patterns: When do temperatures typically peak?
Alert history: What conditions trigger most alerts?

📱 Setting Up OceanRemote Alerts:

Example alert rules:
1. IF soil_moisture < 30% → Send SMS "Water now!"
2. IF temperature > 35°C AND humidity < 30% → "Heat stress alert"
3. IF rain_detected = true → "Skip irrigation cycle"
4. IF device_offline > 2 hours → "Check sensor battery"

💡 Pro Data Tips:

Export data weekly to Excel/Google Sheets for trend analysis
Track water usage vs rainfall to measure irrigation efficiency
Compare this year's data to last year's for improvement tracking
Share reports with agricultural extension officers for advice

🎉 Congratulations!

You now know how to use ALL agricultural sensors! With this knowledge, you can build complete farm monitoring systems, save water, increase yields, and make data-driven decisions.

💡 Key Takeaways:

Apply these concepts directly to your farm or project.
Take notes on important details for the quiz.
Use the button below to track your progress.

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