Indoor Positioning and Predicting the Most Suitable Boutiques in Shopping Malls for Customers

Written by mrcrambo | Published 2020/05/09
Tech Story Tags: technology | iot | machinelearning | data-science | startups | programming | development | big-data

TLDR Indoor navigation and machine learning combination both for helping users to find the most suitable stores and for helping stores to advertise their products. The more beacons you add, the better the quality of positioning and navigation you will get. The story will go on how we can use this data, what things and events we can predict and what interesting functionality we can add to the Shopping Mall application. The most interesting part is using Navigine SDK to add indoor navigation, push notifications and tracking functions. Even if we don’t have user information, we can achieve great results.via the TL;DR App

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Published by HackerNoon on 2020/05/09