What are farm remote weather stations?
What is a farm remote weather station?
Farm remote weather stations use sensors to collect, record and analyze information about farm conditions. These systems allow farmers to automatically collect real-time, local data on temperature, humidity, rainfall, wind speed, soil moisture and more. The cost of implementing these sensor systems has fallen significantly over the past few years. Now, using easy-to-use cloud software, all of this data can be automatically analyzed and turned into actionable information and predictions. These technologies are helping farmers prevent losses and increase crop yields.
How are farmers using it today?
Farmers have been early adopters of technology. When you work hard every day, you want to make sure you get all the rewards you’ve earned. Farmers are currently using these remote weather stations to protect their crops, livestock and workers.
Real-time data collection and local forecasting services allow farmers to more accurately predict the weather at their farms. This can help to ensure OSHA compliance by scheduling workers and their tasks for times before conditions become hazardous and a potential legal liability. Farmers can, for example, schedule workers to perform certain tasks earlier in the day when the personalized forecasts show that temperatures will spike above 100 degrees in the afternoon.
This technology can also help farmers to ensure crops are properly watered. The remote weather station system can determine if soil moisture is too low and can estimate how the forecasted rain, or sunshine, will affect soil moisture. The remote weather station can sync with automated irrigation systems. If it’s going to rain shortly, the system won’t water the crops. If the soil is only going to get dryer, it will begin to water them. This can have a measurable impact on crop yield and water usage.
Farm weather stations are also a powerful tool for preventing catastrophic damage to crops. As they gather more information about the farm’s microclimate, they can help predict threats from heat wilting, frost, high winds, and flooding. These technologies can give farmers the advanced warning they need to best prepare their crops and livestock.
What does this mean for the future?
• Generalized weather forecasts cannot protect crops from frost
If you don’t have a remote farm weather station, you know how inaccurate more generalized, gridded weather forecasts can be. The specific microclimate of a farm may be quite different from what is predicted in a general area, particularly if it’s a large farm with diverse conditions, or near a large body of water. Especially in the case of predicting frost, bad forecasting can lead to severe negative consequences. A few degrees difference in temperature can be the difference between a great yield and disaster. Most weather forecasts are only accurate for two to four days ahead and that is often not enough time to prepare for a frost or other adverse weather event.
• Internet-of-things weather stations help protect crops
Small on-farm weather stations can decrease these risks by improving forecasting. By collecting localized, real-time data with a remote farm weather station, farmers are able to get the accurate forecasts they need. Benchmark Labs helps farmers to turn their data into actionable information. We integrate the farmer’s data with gridded weather data and use machine learning to create 10 days forecasts which are more accurate and useful. The farms that have the most accurate forecasts have one weather station for every five to ten acres of land. By providing farmers with more personalized and accurate ten-day forecasts, we can give them an extra three to five days of response time. Those three to five days make all the difference when there’s a need for frost mitigation or even an early harvest.
• Machine learning can create personalized, accurate forecasts that only improve over time
There is an immense amount of data being collected by these remote weather stations. Every day farmers all throughout the world are adopting and implementing these systems. Machine learning enables Benchmark Labs to process the remote weather station data, analyze it alongside the gridded weather data, and create personalized models and forecasts for farms. Our machine learning models improve over time as the stream of real-time data allows the software to compare its predictions to reality and update.
Putting it into practice
As weather patterns continue to shift, accurate weather forecasts only become more important. These days, farmers never quite know what the next week might bring them. By implementing their own remote weather station system, farmers can get the information they need to adapt to the weather and prevent catastrophic loss. Benchmark Labs’ software uses machine learning to generate personalized weather forecasts for a farm, or even per acre of land. By providing farmers with credible information days earlier, we help them to prepare for the worst: frost, powerful winds, and flooding.