Inspiration
A food delivery service has to dealwith a lot of perishable raw materials which makes it all the more important for such a company to accurately forecast daily and weekly demand.Food wastage is the major problem in the world . 70% of food waste comes from restaurants due to lack of knowledge. Demand forecasting is a key component to every growing online business. Without proper demand forecasting processes in place,it can be nearly impossible to have the right amount of stock on hand at any given time. Too much invertory in the warehouse means more risk of wastage,and not enough could lead to out-of-stocks - and push customers to seek solutions from your competitors.
What it does
We have developed a Machine Learning Model for predicting the future demands for specific restaurents using previous weeks(0-145) data with that you can forecast the demand of product upto 11 weeks and we made inventory management for specific food industry and we added blockchain technology for tracing the food we made it.We used Flask framwork for developing web and Firebase for database.
How we built it
We build the Web application using Flask ,html,css and for forecasting the demand we used Gradientboosting algorithm ,for managing the message transfer between we used firebase based database and for blockchain for tracing the food done using hashlib
Accomplishments that we're proud of
In this challenge, I get a taste of demand forecasting challenge using a real datasets.
What's next for FOODCAST
To develop a mobile application such that communication between the inventory management will be easy and feed more with data for more accuracy
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