International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1425 Data Centric Smart Restaurant Management System Utkarsh Ravekar 1 , Shashank Singh 2 1,2 Student, Department of Computer Science & Engineering, G.H. Raisoni Academy of Engineering & Technology, Nagpur, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Bringing the power of data analysis and digitization to the restaurant business will not only empower the business owners to better serve their customers but also allow them to be able to provide a streamlined and personalized service to each customer. The primary objective of this project is to create a system that will enable any restaurant to serve as a data-centric service provider for its customers and also automate the process of ordering the food items. Every customer who enters the restaurant needs to have the restaurant’s app installed on their phone which can be downloaded by scanning a QR code in the restaurant. The user needs to sign up or sign in to the app and connect to the restaurant Wi-Fi. The entire menu will be available on the app of the user from which the users can select the dishes they’d like to order. The ordered food items will be displayed to the kitchen staff over on a kitchen screen which can also serve as the local server (host). The food ordered by each customer can be tracked through live status along with a live video feed of the kitchen so that the users can get real-time updates about their orders. Also, each order will be recorded per customer which will help the restaurant owner to directly predict the kind of food each user might order and also provide similar recommendations to the customers based on their tastes and choices. On average there, our target restaurant gets anywhere between 1500 to 2200 customers per month and this number increases to around 3000 during festive seasons. Thus, being able to predict the customer’s orders beforehand and providing a recommendation to them so as to help them decide on their orders sooner will not only save time but also help the restaurant serve more customers in less time. Key Words: Restaurant automation, Recommender System, Predictor System, Food ordering app. 1. INTRODUCTION With the rise in the number of people who opt to eat out regularly, the restaurant business is on the rise. Though it’s a good thing for both the business owners and the customers, the restaurant owners find themselves in a situation where they need to serve all their customers as fast as possible while ensuring that the quality of the food and service remains of top quality. But this requires more human labor to accomplish which in turn requires more capital. Thus there is a need for a system that can help fulfill these requirements while keeping the cost low. Our proposed system tries to reduce part of this burden by digitizing some common aspects of every restaurant business. The main objective of our project is to automate the task of selecting and ordering food thus eliminating the need of any waiter to take the orders. Once customers enter the restaurant, they can log in to their app or download and sign up into the app if it’s their first time. The app will display an interactive menu from which the users can select/deselect their desired item and place the order. Customers can also write special instructions with their orders for the chef to follow such as using special oil or using less spice, etc. Once the order is placed, the order will be immediately displayed on a screen inside the kitchen. The kitchen staff who decides to attend to this order will select the order under his/her name. Upon the assignment of the order to particular staff, the customer will get a confirmation update about the chef’s name and order status along with the option to view their order getting prepared through the kitchen cameras. Once the order has been prepared, based on the restaurant’s policy, the customers can either have it picked up from the serving window (if it’s a self-service restaurant) or a waiter can serve it to the customers. Another interesting feature of our system is that based on all the data from the past, it can learn to recommend food items to the customers based on their previous orders or based on their calories counts to provide a balanced and nutritious diet. The customers can also enter their budget to ensure that the recommendations do not cross their budget. The aim of providing recommendations to the customers is that it will encourage the customers to try new dishes while also helping them make their decisions faster. The recommendations can be classified into deserts, main course, starters, etc. Along with the recommendations, the system will also try to predict the immediate future orders of the customers so that the kitchen staff can be prepared for the upcoming orders. After finishing their meals, e-bill will be displayed on the app. The customers will have the option to pay it at the counter or through mobile payments. 2. LITERATURE SURVEY Khairunnisa K. [1] proposed the application of wireless food ordering system. This work presented in-depth on the technical operation of PDA based Wireless Ordering System (WOS) including systems architecture, function, limitations, and recommendations.