| Summary: | 碩士 === 國立交通大學 === 電機資訊國際學程 === 106 === In-store customer b ehavior tracking is a new area. On this topic, a large amount of work has
b een done in this direction. To track the customer activities on shopping existing approaches
have used cameras, smart phones, and smart shopping carts (abrv. SSC). All these approaches
have their own limitations. To overcome these limitations we came up with our unique SSC
design. In this work, we design and implement a prototyp e of smart shopping carts based on
Raspb erry Pi, which features SSC tracking, Queue recognition, and Queue prop erty estimation. BLE b eacon technology and item logs are used for SSC tracking. Queue recognition
is done with the help of SSC micro-cavity features and BLE b eacon proximity information.
Queue prop erty estimation includes estimation of service time and waiting time estimation.
For queue prop erty estimation we take into consideration, the numb er of items in every SSC
and historical information of queue prop erties. We integrate several functionalities in SSC to
improve customer shopping exp erience. We have also done an extensive amount of exp eriments
by considering several practical scenarios.
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