SBIR-STTR Award

Our product is a crop monitoring design that can be mounted on any moving vehicle going through the farm. The entire process of collecting the images and operating on those images to extract the insights is done on the vehicle itself in real-time eliminating the time-consuming process of uploading images to a central server for processing. The system be completely owned and operated by the grower themselves without requiring the involvement of the company providing the technology. This affordable easy to use technology provides the farmer a flexible monitoring schedule reduced labor costs and crop yield prediction. The Phase I objectives involve (i) improving video streaming for real time analysis of crops (ii) developing counting algorithms that can accurately count objects in streaming images considering intermittent occlusion for accurate yield prediction (iii) developing an camera harness which can isolate or dampen the kind of vibrations felt on farm vehicles protect the camera from overheating during operations on hot sunny days and generally rugged for the field operation. Our technology overcomes the limitations of offline monitoring and will benefit growers shippers crop advisors companies and industry consortiums by providing affordable real time monitoring of crops to predict yield and identify area of concern within the fields. Our project advances the goals of Topic 8.13 Plant Production and Protection (Engineering).

Agrofocal has developed a crop monitoring system that can be mounted on any moving farm vehicle. The entire process of collecting the images and operating on those images to extract the insights is done on the vehicle itself in real-time eliminating the time-consuming process of uploading images to a central server for processing. The system be completely owned and operated by the grower themselves without requiring the involvement of the company providing the technology. This affordable easy to use technology provides the farmer a flexible monitoring schedule reduced labor costs and crop yield prediction. Agrofocal succesfully developed the system during Phase I for farm operations. During Phase II the team will conduct field trials to assess the systems ability to determine crop yield and accuracy while monitoring operational robustness. In addition the team will evaluate and refine the AI models based on the field trial data. Successful completion of the Phase II objectives will set the stage from product launch and commercialization. Our technology overcomes the limitations of offline monitoring and will benefit growers shippers crop advisors companies and industry consortiums by providing affordable real time monitoring of crops to predict yield and identify area of concern within the fields. Our project advances the goals of Topic 8.13 Plant Production and Protection(Engineering).