From vacuuming 4 hours evenly to cleaning only where and when it's needed.
Neighborhood supermarket chain · 800m² · 8 employees · 12 cameras
An 800m² supermarket spent 4 hours every night cleaning every aisle equally. The robotic vacuum passed through the canned goods aisle (low traffic) just as often as the fresh produce zone (3x more traffic). Result: dirty aisles in high-demand zones at midday, and unnecessary wear on the machine in nearly empty zones.
VIKI Vision processes the supermarket's cameras with anonymous AI and detects how many people pass through each zone at each hour. It cross-references that information with: historical revenue by section, cleaning staff hours, and the robotic vacuum's status. Every night VIKI generates the optimal route: more passes in fresh produce and checkout areas, fewer in canned goods, none in empty zones.
In 3 months the supermarket has cut daily cleaning time by 35%, extended the robotic vacuum's lifespan by 40% by reducing wear, and staff now dedicate those 2 saved hours to restocking shelves and serving customers.
This is just one specific case.
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