Abstract
With the increase of individuals having an interest in the culinary world, the demand for recipe and lifestyle applications have increased. As we adapt to the changes around us during these trying times, many have also taken an interest in home-cooking. However, it may be challenging, especially for beginners to brainstorm recipes for cooking as they may not be equipped with the proper ingredients to do so. In this paper, we propose Feast In, a platform for web and mobile devices which aims to meet a user’s needs for home-cooking. The platform focuses on three unique features which make Feast In more than just the average recipe platform. Firstly, an improved search algorithm which goes beyond searching for keywords would help users narrow down recipes which they can use in their kitchen. Next, customization features which would create a personalized experience, specifically towards recipes results. This would provide individuals who may face allergies or dietary restrictions an improved experience as they would not have to browse through recipes which do not meet their needs. Lastly, the search-by-image function which utilizes image recognition and machine learning technologies. Users will be able to upload an image of food that they have come across and Feast In will return a list of results which matches the image uploaded. By conducting this research, we were able to propose a unique lifestyle and recipe application which would aid users in searching for the perfect recipe.
Highlights
Subang Jaya, Selangor, Malaysia with the influx of individuals choosing to cook at home during the Movement Control Order (MCO), there is a distinct demand in recipe and cooking tools
A search algorithm resulted in 1,000 recipes, and when users filter out the recipe from the client-side, their device would have to process the details of all 1,000 recipes, filter out the unwanted recipes, and display them again
This study aims to develop an image recognition model which would be used in conjunction with the platform to aid users in identifying a recipe from an image uploaded by the user
Summary
Subang Jaya, Selangor, Malaysia with the influx of individuals choosing to cook at home during the Movement Control Order (MCO), there is a distinct demand in recipe and cooking tools. Similar platforms in the market offer search functionalities whereby users are allowed to search-by-ingredient This has proven to return inaccurate results as users can input any type of word or character they wish, even if it is not a relevant term. This can be improved by implementing a search algorithm which allows users to select from a dropdown list of ingredients instead of allowing users to enter any word of their liking. This would increase the accuracy of the search function as it eliminates the potential for error during user input
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