The client is a leading business intelligence company based in Australia having customers in New Zealand, South Africa and South East Asia. It enables bricks and mortar retail stores to grow and thrive by understanding and adapting to changing consumer behavior.
The client was using a smart cam application for counting foot traffic in stores. But the solution was not scalable and was inefficient to be used in multiple stores by multiple companies and by multiple level of users. Moreover, it was meant to be used on proprietary desktop machines and hence it could not be used remotely via browsers. The client approached Medma for developing an IoT solution with Analytics dashboard capable of managing multiple devices, stores, users and companies – all from cloud.
After few rounds of discussions and analyzing the data export of the smart cam device, we decided that the XML data has to be parsed & compiled automatically for immediate availability in the cloud. For analytics & reporting this data was be sent to MongoDB and MySQL database hosted on different servers for integration with client dashboards. The enter and exit data has to be separated but at the same time data from multiple devices in one store has to be aggregated to show a real picture of the traffic. We planned to use Laravel for building cloud based Administrator panel. This was to provide an easy interface for Admin to manage companies, manage multiple devices in each store, manage users and manage upto 300 multiple stores for each company.
This IoT solution provides a very secure dashboard & analytics to users. All user activities are logged including verification of their account, failed login attempts, last access etc. The traffic data from multiple IoT devices are aggregated and displayed on an interactive chart capable of further drilled down for details. Store owners can see enters and exits numbers together with benchmarks and percentage of increase / decrease in traffic for a particular period of time. The application provides location and business intelligence to stake holders who can quickly identify peak periods of high foot-fall and can then related it to Sales data. They can upload sales data of their stores via CSV and the correlate it with traffic metrics to analyze sales conversions. The company Admins can view all their stores on interactive zoom-able map, which can be further clicked to get analytics like traffic count, visitor type, busiest day, slowest day etc.