Undergraduate YPEC 2022

UG09 – Traffic Analysis Visualisation Algorithm (TAVA)

Traffic Analysis Visualisation Algorithm (TAVA) aims to provide full sales funnel metrics to vending machines & SMEs to enable better decision-making by analyzing consumer behavior patterns. Nowadays, the majority of retailers only record sales volume and revenue. Foot traffic metrics such as the number of people showing interest in the machine and passers-by are unknown. Without these important metrics, vendors and shop owners cannot adjust their sales strategies according to the market conditions accurately. By adopting people recognition, people tracking and IoT technologies, our team has developed a mini device that can be mounted on top of a vending machine or any wall surface. Together with our web platform, vending machine/ shop owners can visualize foot traffic trends easily. By comparing the foot traffic data with the sales record, more precise decisions could be made to boost the revenue. Currently, we have prototype systems running in Wada Bento, a Forbes Asia 100-to-Watch start-up selling bento through vending machines. The company is leveraging our data to improve its inventory and marketing decision-making. While this proves the feasibility of our ideas, we are constantly receiving user feedback to improve our system. It is our goal to apply our systems to arcade machines shortly.