Restaurant Business Analytics for the price, discount, etc prediction with people counting web app
Innovative solution for gaining profit in standalone startup restaurants. According to many reports, the main factor that determines a restaurant's profit is the people count. So we have proposed a solution where a restaurant's past history of prices, dishes, and such factor's transaction has been taken into account and providing a recommendation for the price to be fixed for a particular day, the dish quantity to be prepared, etc.
Trend analysis is much more important, for that we use tableau, which provides real-time public inference on data, here the owners can check their past transaction and analyze the trend.
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Data gathering and cleaning
Handpicked data of restaurant prices, dish count, etc, and preprocessing using pandas and NumPy would give us clean data for modelling, the data is raw, formatting for our use is the key to good accuracy.
People Counting
After done with the data, we can use the pre-trained model and tune it to do non-max suppression to get prediction only for people. And get predictions as the people count, in selected areas. Tracking is necessary to know when people come into the frame and track them till they move out, for that Dlib and OpenCV libraries are used.
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Recommendation and Time series
The main idea here is to recommend prices to restaurant owners with respect to the people count for the future. So with the cleaned data, we model it using the prophet model from the Facebook research do time series analysis i.e to predict the future values and then apply dlrm a recommender system model and recommend people the right dish with respect to the past history, and recommend a price to the owners with respect to the people count.
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Deployment
The detection model(counting model) with the price recommendation model, all wrapped and connect as a single application(a web app). Streamlit is an easy-to-use deployment framework, particularly for machine learning.
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Application
The above process is deployed as a web app, this repo contains the structure to be made for creating a new one, the app is deployed, check out the repo!