Every time you move anything, there is a process of inspection where the items getting moved are recorded for finding the total truck size and to generate the quotation for the movement.
We build a yolo based DL model using imagenet and our customer dataset to find the items ON THE GO.
The person moving uses our app to point at the items and it gets recognized.
They can then either mark the qualitative data like damaged/fragile/dismantlable to further give us insights.
These items are pre-marked with the CFT, such that we build the truck requirement in real-time thus predicting the quote for the movement instantly.
This solution is used in our android application linked above.