Project URl : http://foodcoin272.mybluemix.net/#/
Python Flask URl for Machine learning of Input Data : http://foodcoin.mybluemix.net/
Project Yelp dataset Link https://drive.google.com/open?id=0BxgoF01Bp1G5Z1h1TWVsV1RyQmc
Problem Statement:
Huge amount of food is wasted in restaurants. The wastage is caused because of the following reasons:
- Improper use of Inventory
- Incorrect estimation of customers
- Inappropriate utilization of prepared food
- Food Items not as per expectations of consumers.
Such wastage results in extra cost to the restaurants and inefficient estimates while preparing food or managing inventory make these restaurants spend extra money and resources.
Moreover, the food items that are wasted could have been used to facilitate someone in need.
Proposed Solution:
To overcome such problem, we are planning to build an application that uses TensorFlow, a machine learning software, to find the pattern in the daily activities of restaurants. Further, we will create a Dashboard for the Manager that will show the current scenario of restaurant to him and suggest ways to how the wastage of resources can be minimized.
Benefits of analytics include: - Efficient use of raw materials:
a) Manager would be able to purchase inventory wisely.
b) Rotation of items in the inventory will lead in better utilization. - Using fresh menu items:
a) Better assistance to Chef to decide daily menu by making him more aware about the inventory and customers’ count. - Ensuring quality of food:
a) Help the manager to know about the factors to ensure better food quality. - Assist in meeting diner’s expectation:
a) Help management to decide the quantity of food item to be served to user.
b) Assist in predicting the likes and dislikes of users.
## Project Deliverables
[Presentation Slides] (/Team Project - FoodCoin/FoodCoin Demo.pdf)
[Project Report] (/Team Project - FoodCoin/Report FoodCoin Team 8.pdf)
# Flow Chart:
