Live greenhouse data: https://benb0jangles.github.io/Remote-greenhouse-monitor/
Reddit Community: https://www.reddit.com/r/Grovia/
This project implements a long-range wireless environmental monitoring system for precision agriculture and horticultural research. It enables real-time tracking of critical growing conditions in a greenhouse located 3 kilometers away from the monitoring station, using low-power LoRa mesh networking technology.
Understanding optimal growing conditions for different plants requires comprehensive environmental data collection over extended periods. Traditional greenhouse monitoring systems are limited by:
- Range limitations: WiFi and Bluetooth don’t reach beyond ~100 meters
- Power requirements: Continuous monitoring needs reliable power in remote locations
- Data accessibility: Local storage requires physical access to retrieve data
- Long-term analysis: Studying seasonal patterns requires months or years of data
This project solves these challenges using long-range radio technology, solar power, and cloud-based data storage.
The system continuously monitors five critical environmental parameters that directly impact plant growth and health:
- Why it matters: Controls photosynthesis rates, respiration, germination, and flowering
- Insights gained: Identify optimal temperature ranges for different crops, detect frost risk, understand seasonal variations
- Growing applications: Determine which vegetables tolerate cool springs, when to plant heat-loving crops, thermal mass requirements
- Why it matters: Affects transpiration, disease susceptibility, pollination, and water uptake
- Insights gained: Prevent fungal diseases (caused by high humidity), optimize watering schedules, understand vapor pressure deficit (VPD)
- Growing applications: Select humidity-tolerant plants, plan ventilation needs, prevent blossom-end rot in tomatoes
- Why it matters: Correlates with weather patterns, affects plant stress responses
- Insights gained: Predict incoming weather changes, correlate plant growth with atmospheric conditions
- Growing applications: Understand how pressure changes affect transplant success, correlate yield with weather patterns
- Why it matters: Drives photosynthesis, controls photoperiod responses, affects stem elongation
- Insights gained: Calculate daily light integral (DLI), understand seasonal light availability, identify shading issues
- Growing applications: Determine if supplemental lighting is needed, understand which crops suit low-light periods (leafy greens vs. fruiting crops)
- Why it matters: Essential for nutrient uptake, controls plant water stress, affects root development
- Insights gained: Optimize irrigation schedules, understand soil water retention, detect drainage issues
- Growing applications: Prevent over/under-watering, select drought-tolerant varieties, optimize potting mix composition
By analyzing year-long environmental data, you can:
- Determine which crops thrive in each season (e.g., lettuce in cool spring, tomatoes in summer)
- Identify “shoulder seasons” where transitional crops perform best
- Plan succession planting based on historical temperature and light data
- Select varieties suited to your microclimate
Historical data helps identify causes of poor growth:
- Low yields? Check if light levels were sufficient
- Disease problems? Review humidity patterns during the growing period
- Slow germination? Compare soil temperature to optimal ranges
- Wilting plants? Analyze soil moisture trends
Over time, you can:
- Understand thermal mass effects (how materials store/release heat)
- Optimize ventilation timing based on temperature/humidity patterns
- Plan shading strategies based on summer light intensity
- Design heating systems based on winter temperature data
- Compare growth rates under different environmental conditions
- Test microclimates within the greenhouse (north vs. south side)
- Validate growing guides against actual local conditions
- Share data with other growers in your climate zone
Look at your historical data:
- When does temperature reliably stay above 15°C at night? → Safe to transplant
- When does light exceed 40,000 lux consistently? → Good fruit set
- Does summer humidity stay below 75%? → Blossom end rot prevention
- Soil moisture patterns → How often to water (target 65-75%)
Analyze your annual patterns:
- December-February (low light): Microgreens, hardy salads (with grow lights)
- March-April (warming up): Start transplants, cool-season crops
- May-September (peak season): Warm-season fruiting crops
- October-November (cooling down): Second crop of cool-season vegetables
Set up alerts for:
- Temperature : Frost warning (protect crops or add heat)
- Temperature > 32°C: Heat stress (increase ventilation, shade)
- Humidity > 85% for 6+ hours: Disease risk (improve air circulation)
- Soil moisture : Irrigation needed
- Soil moisture > 85%: Drainage issue (reduce watering)
- Light average in growing season: Consider supplemental lighting
- Alerts: SMS/email notifications for frost warnings, low soil moisture, etc.
- Automation: Control irrigation, fans, heaters based on sensor data
- Machine learning: Predict optimal harvest times, yield forecasting
- Multi-node: Monitor multiple zones within the greenhouse
- Integration: Export data to spreadsheets for detailed analysis
License: MIT
Author: Greenhouse Grower benb0jangles
Last Updated: 2026-01-30