Priyank Kalgaonkar / Electronically Connected Intelligent Shelves

The main objective is to reduce loss in revenue due to delayed shelf-restocking (when product is in-stock in the store but not stocked on the shelf) and inaccurate forecasting (under-estimating future product sales) practices. The result is to demonstrate inventory automation using ECIS system by enabling the means to monitor and track store inventory in real-time, perform data analysis remotely in cloud, improve shopping experience for the consumers and increase revenue for the retailers in the retail industry. Machine Learning code can be found on my GitHub: https://github.com/priyankkalgaonkar

Dependencies:   mbed

ECE 53301: Wireless and Multimedia Computing Final Project Report – Group 1

Inventory Automation Using Electronically Connected Intelligent Shelves.

Code Developed by: Priyank Kalgaonkar.

Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology at IUPUI.

Submitted as partial fulfillment for the requirement of Fall 2019 - ECE 53301-26877: Wireless and Multimedia Computing course.

Date of Submission: December 12, 2019.