We always wanted a solution for shopping malls business places to see how a customer reacts when we searches for a particular product which he tends to find hence we started working on a solution which integrates customers emotion data and then do useful analytics for our application
What it does
We have made a smart trolley that tracks customer faces while they are shopping and push that into Ibm Bluemix the data is then trained by Apache Spark to give meaningful insight to the business establishment.
How we built it
The system tracks customer faces and emotions while they are shopping puts that into IBM no-sql cloudant database then this data is being seen from realtime data monitoring system at the same time this data is being analysed by ipython notebook using Apache Spark to give meaningful aggregation of emotion data.It updates the time series data using internet of things services.we put the live data to cloudant db the data inputs are anger,smile,sadness and surprised then generate a pandas data frame.Several aggregated data visualization can be performed that significantly understanding the customer needs and increases the sales of the business.
Challenges we ran into
Getting the emotion data back to the Ibm Bluemix was a challenge as it was not updating at all some rigorous amount of hard-work and testing then lead us to success.
Accomplishments that we're proud of
Integration of IoT stack(node-red),emotion recognition and then finally putting the data for analysis
What we learned
Using emotion tracking and then analyzing the data using Apache Spark
What's next for Emometric
We want to market it as a product of our own give this solution and service to the retail businesses.