Data becomes information when it is organized into a form that can be acted upon. The SensorSentry remote monitoring solution lets you collect data on a variety of environmental conditions from many locations at one property. Our clients can monitor temperature, rainfall, and soil moisture at one location using one CropSense unit. They gather information from different monitoring locations throughout the property using multiple CropSense units. DataSense, the on-line data management software, integrates sensors from different field devices (e.g. soil moisture, water, weather) to create one unified Location Report for the property.
These reports are a valuable tool for comparing soil moisture, water and weather information from different monitoring locations. This functionality allows clients to view data from multiple locations on the same graph in order to make a direct comparison between the information.
For example, a report can be created using data from a rain gauge at nearby public weather station and all of the soil moisture devices on the property. Daily precipitation and soil moisture can displayed on the same graph, providing essential information to help achieve optimal irrigation scheduling.
Additionally, a report can be created by integrating sensors from several soil moisture monitoring devices with solar radiation, wind speed, relative humidity, and air temperature sensors from a nearby weather station. This would enable daily ETO values to be calculated and displayed on the same graph as the soil moisture devices' summed lines, providing you with the ability to track the effect of daily ETO on soil moisture depletion. This report is particularly useful for monitoring on-farm water balance using soil moisture, water level, water flow, and weather sensors.
Weather sensor data can be aggregated from multiple devices to create reports that assist with crop management. Statistical models that are available with the SensorSentry system can then be used to process this integrated weather information and facilitate decision-making.
For example, the SensorSentry Grape Downy Mildew model can be run to provide specific disease information for each field on the property. This precise approach enables the client to monitor specific disease risks for each field, ensuring more accurate modeling and more efficient spraying.