Intercessor

_The Smart Warehouse Management system

Intercessor is a smart warehouse management tool that uses machine learning to reduce the wastage of perishable goods. The main goal is to make a system that can forecast the upcoming sales for a warehouse and then use the same to restock according to the predicted sales. So this is the main idea behind the project.

Tech Stack and major libraries used

• MongoDb for managing and storing the csv files
• Flask web framework for webapp
• Tensorflow for using ARIMA model
• R programming for estimating the prediction variables
• Pandas and numpy for other miscellaneous

To deploy the app, follow the steps

• Customize the data present in the CSV files as per your choice
• Adjust the variable of forecast using the R file.
• Change the variables for the particular commodity in the app.py file
• Change the mongodb credentials with your credentials in the app.py file
• To run the app, use flask run after installing the requirements
• Please raise an issue if you face any issue in running the app or forecasting

The app is currently deployed on heroku server- https://intercessor555.herokuapp.com/