Design a tool to help optimize the shopping mall experience either considering the shoppers’ or owners’ point of view.
Time isn't always by your side, yet it is capable of making you pull out the best of your capabilities in a time crunch, leading you to develop visibly clean and polished products in the blink of an eye.
Credit also goes to: Eleonora Avanzolini, Andrea Tampella and Matteo Padovan.
moodmap was designed during the two-day NOI Hackathon SFScon Challenge held in Bozen, Italy. It is conceived as an information visualization system capable of tailoring the mall shopping experience on the basis of a mood analysis obtained through Machine Learning (TensorFlow). Given that in shopping malls it is possible to either encounter a great amount or a true lack of information, the shoppers' viewpoint was taken into account in order to help them move with ease through the stores.
moodmap provides shoppers with helpful information in a fresh, essential, and innovative manner. Concepts for indoor navigation and image recognition were used and open data was included in the Machine Learning algorithm employed. This project won First Place in the category of Innovative Mall Experiences for ACS. For more information please contact me directly.
