Design of Low-Cost Object Identification Module for Culinary Applications

• Published in: Journal of physics. Conference series Vol. 1964; no. 6; pp. 62088 - 62096
• Main Authors: Pranav Vijay Chakilam, B, Revanth, Muppirala, Vyshnavi, Anilet Bala, A, Maik, Vivek
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.07.2021
• Subjects: Algorithms; Cameras; Deep Learning; Image processing; Machine learning; Modules; Object Identification; Object recognition; prediction accuracy; Python; Recipes; Vegetables
• ISSN: 1742-6588; 1742-6596; 1742-6596
• DOI: 10.1088/1742-6596/1964/6/062088

Using up one’s fridge’s contents often requires touch creativity, which is typically hard to come by in a very busy world. This aim is to style a model that may scan the things in one’s fridge and recommend recipes that supported what one has got, even taking one’s preferences and dietary restrictions under consideration. Computers are commencing to process globe objects without the requirement for codes or human intervention in their language. This project aims to create a module that uses object recognition to detect vegetables and fruits and display recipes that include those foods. This concept uses a camera that is installed in a refrigerator to show it into a sensible one. The system identifies objects that are placed inside using complex object recognition algorithms using the camera. If a vegetable or fruit is placed inside, the system will identify it and displays its name on the screen. It creates an indication of the chances of object recognition. The platform enables users to put any number of various vegetables into the refrigerator. The system then checks a list of recipes that contain the ingredients inside the refrigerator and filters those that feature the vegetables available. Together with this, we also aim to watch the refrigerator’s contents and find the freshness and age using various sensors and provide inventory and warnings when they are on the verge of completion.