How does it work?

• Sensor at each facing measures amount of light. Light readings are different when covered by product, and when loading inventory vs. removing inventory. • Camera at each shelf - takes a photo and stores locally • Connected coolers: Data from controller is sent to Bluemix at configurable intervals • Occasionally connected coolers: Data from controller is loaded onto mobile device for sending at later time to Bluemix • Data sent in via MQTT for identification by Watson Visual Recognition service • Data is fed to Bluemix application for inventory adjustments

What does it measure?

• Was something added or removed from a row? • What was added or removed. • If inventory was added, then increment; if subtracted, decrement count. • Is what was added according to planogram? if no,flag system that an inappropriate item was added and show picture • Is the row empty (regardless of what we believe the count to be)

Does the retailer/bottler/distributor have to do anything different to make your solution work? (if yes, please explain)

• gravity fed or spring loaded trays • There are no connectivity changes required because we were advised that all sellers have mobile devices to download/transmit data

What materials does your solution require?

• Controller (1 per cooler) • Memory for controller (i.e., SD card) • Sensor (1 per facing) • Camera (1 per shelf) • Cloudant Sync • Cloudant • Bluemix • Watson Visual Recognition

Best guess on cost to implement

• $20 - $40 per cooler

Challenges you/your team ran into

• staying under $20 per cooler

What you/your team learned

• Watson is cool

Next steps

• Functional prototype • Phased approach (biggest win for least cost)

Anything else you want to add:

Analytics to proactively predict future inventory. Capable of providing real-time notifications (i.e., when product is removed, stocked, running low, etc)
Social interaction (twitter/instagram/etc) and sentiment analysis enabled

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