https://github.com/priyankkalgaonkar/electronically-connected-intelligent-shelves

Inventory automation prototype using NXP FRDM-K64F MCU, ultrasonic sensors, cloud server and predictive analytics using machine learning techniques.
https://github.com/priyankkalgaonkar/electronically-connected-intelligent-shelves

Last synced: 4 days ago
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Inventory automation prototype using NXP FRDM-K64F MCU, ultrasonic sensors, cloud server and predictive analytics using machine learning techniques.

• Host: GitHub
• URL: https://github.com/priyankkalgaonkar/electronically-connected-intelligent-shelves
• Owner: priyankkalgaonkar
• Created: 2019-11-10T06:28:02.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2021-01-20T22:39:59.000Z (almost 4 years ago)
• Last Synced: 2024-05-20T19:12:28.748Z (6 months ago)
• Language: C
• Homepage: https://os.mbed.com/users/priyank12p/code/Electronically-Connected-Intelligent-She//file/45dc700211a7/FinalVersionECISsystem/
• Size: 1010 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Electronically-Connected-Intelligent-Shelves

Inventory automation prototype using NXP FRDM-K64F MCU, ultrasonic sensors, cloud server and predictive analytics using machine learning techniques.

www.ecissystem.ml

Project Description: Our design of ECIS system prototype includes an array of ultrasonic sensors, which can be retrofitted in existing shelves with minimal modifications or built-in in to new shelves, connected wirelessly to a central cloud server from where the inventory of goods on the shelf can be monitored in real-time as well as data acquired from these sensors can be used to perform predictive analysis using data mining, feature engineering and machine learning techniques to better predict future product sales and minimize inaccurate forecasting instances.

A copy of our Final Report can be accessed via this link: https://drive.google.com/open?id=1NSAnWObxRHyr0hpXWuKvOtI-dzXI2MXL .

Video of our working prototype: https://youtu.be/yUNbQFOUya4 .

Machine Learning Repo: https://github.com/priyankkalgaonkar/Predictive-Analysis-Using-Feature-Engineering (part of this ECIS project).