Additional Funding Sources
The project described was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant No. P20GM103408.
Presentation Date
7-2022
Abstract
One of the tools for precision agriculture is yield monitoring in which the crop yield is analyzed. Previously, a yield monitoring system using machine vision was developed to estimate the fruit yield of a given tree early on in the season. This yield monitoring system was created as an iOS mobile application. In continuing this project, the development of an Android mobile application is now in progress. In this way, any farmer will have access to a farmer-friendly tool for farm management. Predicting yield early in the season helps farmers in the marketing of their product and in the production logistics. The Android application currently has a user interface that’s caught up to the iOS version. The machine vision system which uses a color camera to acquire images of the trees during their blossom period is also in place. However, image processing isn’t yet implemented. Soon, the image segmentation algorithm will be translated and implemented to recognize and count the blossoms on an image.
Blossom Counter Mobile Application (Android)
One of the tools for precision agriculture is yield monitoring in which the crop yield is analyzed. Previously, a yield monitoring system using machine vision was developed to estimate the fruit yield of a given tree early on in the season. This yield monitoring system was created as an iOS mobile application. In continuing this project, the development of an Android mobile application is now in progress. In this way, any farmer will have access to a farmer-friendly tool for farm management. Predicting yield early in the season helps farmers in the marketing of their product and in the production logistics. The Android application currently has a user interface that’s caught up to the iOS version. The machine vision system which uses a color camera to acquire images of the trees during their blossom period is also in place. However, image processing isn’t yet implemented. Soon, the image segmentation algorithm will be translated and implemented to recognize and count the blossoms on an image.