JUN 2018 ||| Skills: Raspberry Pi, Object Recognition ||| URL: wAIrhouse
We created a robot to run through warehouses, evaluate palette size, and run precise calculations of palette dimensions. This machine ensures proper product count and allowes warehouses to operate at optimal efficiency.
Instead of K-Means validation, all results are tested through network and values with significant variation taken out for second iteration.
This solution solves this issue by creating a clear consistency of dimension due to pallet configuration data. The integration of hardware and AI facilitates not only more efficient workflow in the current economic environment, but revolutionizes the future of large-scale product management.
This is an important issue given that large companies such as Loblaws employ over 27,300 individuals in distribution centers for tasks including palette configuration and testing. Dozens of corporations follow that model and employ an equivalently excessive number of employees. Canadian economy is not production, but service based. Not only that, a key element to services provided by a number of distributors requires the usage of warehouses and manual labour. Several physical tasks are being automated across Canada and that is where wAIrhouse comes in hand.