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AgAi

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Specialty crop farmers depend on reliable, accurate, and affordable crop forecasts to allow them to diligently plan their energy, labor, storage, shipping, and packaging needs, in addition to setting their pricing. This is especially true in blackberry and strawberry crops. Current forecasting methods are unfortunately slow and rely on small sample sizes, reducing their potential for accuracy. This leads to lost time and money by every stakeholder downstream relying on these forecasts. Using computer vision and a smartphone based camera, AgAi enables anyone in the field to collect information. This will allow farmers to increase their forecasting sample sizes and get accurate and higher quality data faster and cheaper, ultimately improving their forecasting capabilities, resource management, and margins.

Team Members

Edward Silva (MBA/MS, GSB E-IPER) and PI: Prof. Stefan Reichelstein (GSB)