In areas where water is scarce, water management is critical. This has an impact on agriculture, as a significant amount of water is used for that purpose. As a result of the potential impacts of global warming, water adaptation methods are being considered to assure the availability of water for food production and consumption. As a result, the number of studies aiming at reducing water usage in the irrigation process has increased over time. Typical commercial sensors for agriculture irrigation systems are quite expensive, making it hard for smaller farmers to use this type of system. However, manufacturers are currently developing low-cost sensors that may be connected to nodes to construct economical systems for irrigation management and crop monitoring.
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Our team figures out exactly how much to irrigate the field by providing an irrigation prescription that is constantly adapting to the changing field conditions. By factoring in thousands of data points from previous cases, we can predict water-uptake patterns, detect faulty irrigation systems and burst pipes, and improve the decision-making process.
By analyzing crop growth against crop models, we can predict the crop’s needs and expected growth, can detect any deviation, and can identify early-stage field variability and non-uniformity of crop growth. We provide crop-specific recommendations and send alerts about field segments that need attention due to potential risk from pests or diseases.
We take crop loss very seriously; ensuring that nitrogen is available to crops when they most need it is one important step to reducing crop loss. We integrate crop models, satellite imagery, and weather forecast data alongside the soil data we analyze to optimize fertilizer availability and create crop-specific application recommendations.
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