A Food Recommendation System is an artificial intelligence-driven platform that provides personalized food suggestions based on user preferences, dietary requirements, and nutritional goals. The system utilizes machine learning algorithms to provide accurate food recommendations from a large database of food choices. The system also takes into account user-specified preferences, dietary restrictions, and nutrition goals. The overall goal of the system is to help users make better food choices that are tailored to their individual needs.
Abstract
Eateo aims to explore the needs and preferences of customers who travel regularly for work, studies, or other purposes, and how to better meet their needs for food options. It will also consider how to optimize their experience with food choices and explore options that cater to their individual tastes and preferences
Eateo has great potential for development in India. The growth of the mobile app helping markets to grow. The food Recommendation system will become popular among people who search for relevant information about food. In this paper, the EATEO food recommendation application is studied in detail. Users could find food that matches their tastes in the shortest time. This app-based on AI Chatbot that can efficiently manage time and finances by making it easy for consumers to easily access the information they want anytime, anywhere. By analyzing the customer needs Eateo will work for the customer’s convenience. For the recommendation system, we put forward a recommendation algorithm based on the rank-centroid/analytic hierarchy process. In this paper, an artificial intelligence chatbot-based food recommendation app using personalized information is proposed. The recommendation service app utilizes personalized information such as gender, age, interests, occupation, favorite dish search records, visit records, wish lists, reviews, and real-time location information. Through the recent dishes that the user likes to have, transforming it to preferences of the user into the Eateo app and using this algorithm, we will establish a model, so that users can get recommendations for food that fit their mood through chatting AI chatbot. Furthermore, EATEO makes possible to check real-time information about restaurants famous dish and can write reviews. The proposed app uses a collaborative filtering recommendation system, through users dining out information using artificial intelligence chatbots. Through chatbots, users can receive customized taste food using personal information while minimizing time and space limitations.
Introduction
While India has always been a food-loving country with each region having its own special cuisine, Indians have never been very big on eating out. But all that is changing now. As everything is going to be digital now and consumer’s want everything at one click.
So EATEO is here which will understand the mood of consumer and recommend food that matches their tastes in the shortest time. This app-based on AI Chatbot that can efficiently manage time and finances by making it easy for consumers to easily access the information they want anytime, anywhere. By analyzing the consumer mood at particular time. As consumer may have different mood at different period of time. Such that at night consumer mood is diiferent comparing to day time and consumer wants something else in afternoon. This varies in mood, time, taste, places and people which is a very huge data and deep concept of understanding consumer needs. it can take very long time to understand the customer. But EATEO systematic algorithm will understand the consumer preference by analyzing answers of different categories from user. To make it efficient for customer to take what they want.
The restaurant industry in India has been growing at a rapid pace over the last decade or so and the growth story is set to continue for the next foreseeable future. EATEO has a very vast scope in food app. As with EATEO sales can be increased by 25% as it covers main needs of customers. By food Recommendation system. There were nearly 22 lakh hotel and restaurant establishments in India in 2002. The food service or restaurant industry was worth a whopping Rs. 43,000 crores in 2010 and growing at a healthy rate of 15-20 percent annually. Solving customer’s need and fulfilling their demand is our first priority and Eateo will work for the customer’s convenience.
Literature survey
EATEO will be designed to drive those customers attention who travel for work, job, studies on daily basis or who wants to take food according to his taste and preferences.
This research aims to develop a system that enables users to quickly and accurately identify food items that match their tastes in the shortest possible time. The system will explore various data sources to create a personalized food recommendation engine, which will utilize machine learning algorithms to analyze user preferences and provide tailored food suggestions. Additionally, the system will incorporate user feedback to continually refine and improve its food recommendation capabilities. The ultimate goal is to provide users with an efficient and customized food discovery experience.
EATEO focuses on the customers who are confused in choosing between different types of dishes. According to our research there is no such or similar patent for this issue.
This research aims to develop a method for quickly and accurately identifying food choices that match a user’s individual tastes. The method will analyze individual user preferences and offer suggestions for food items that match the user’s taste. The goal is to provide users with a streamlined and efficient process for quickly finding food that is tailored to their personal taste.
Eateo
SAHIL NEGI.COM 