Today there are immense opportunities of Artificially Intelligent solutions in every possible field owing to TensorFlow’s open-source models that can be easily trained and implemented in innovative projects.
In the Agriculture field, there is a tried and tested method by Google to intelligently automate the process of sorting farm produce with the help of TensorFlow.
The sorting process of fruits and vegetable post-production is very lengthy. Time spent by a farmer in classifying the produced cucumbers is much more than that used in the farming process. It’s a task that requires intricate precision, so not anyone can take this task up. One needs to be trained and experienced to approve quality and classify the cucumber.
However, with the help of TensorFlow’s Machine Learning in agriculture a process can be taken up by a machine, farmers can convey all their efforts in their upscale task of farming.
Here, Artificial Intelligence can be used to automate the sorting of produced cucumbers that would not require an experienced farmer.
A customized machine can be made, fed with the machine learning program using TensorFlow’s open-source neural network model (code) with some modifications.
This use case shows the possibility of sorting and classifying farm produced cucumbers according to varying lengths, shapes, and colors using the Image Recognition technique of AI using TensorFlow’s machine learning in agriculture.
If you like we can notify you each time a new interesting content is uploaded.
__________
Custom-built machine using Arduino and Raspberry Pi 3 micro controllers, attached with conveyor belt, and sorting arms arranged at distinct positions to classify cucumbers in varied categories. Depending on the number of categories of cucumbers, collector bins should be placed below the conveyor, where the sorting arm disposes the classified cucumbers.
__________
One that places cucumber on the Arduino machine at regular intervals. And to feed training data-sets into this program of machine learning in agriculture.