We created a robot to run through warehouses, evaluate pallet size, and run precise calculations of pallet dimensions — ensuring proper product count and allowing warehouses to operate at optimal efficiency.
Instead of K-Means validation, all results are tested through a neural network with values showing significant variation flagged for a second iteration. This solution creates clear consistency through pallet configuration data. The integration of hardware and AI facilitates not only more efficient workflow, but helps revolutionize the future of large-scale product management.
This addresses a real problem: large companies such as Loblaws employ over 27,300 individuals in distribution centers for tasks including pallet configuration and testing. wAIRhouse targets that category of manual labour with AI-driven automation.
