KUBO: a mobile-based food planner and recipe app with object detection/
Suerte, Jake Andrey F.
KUBO: a mobile-based food planner and recipe app with object detection/ Jake Andrey F. Suerte, Lovelyn C. Tapales, Jerico C. Villariza, Marcial B. Zipagan jr. -- - Manila: Technological University of the Philippines, 2022. - xii, 164pages: 29cm. +1 CD-ROM (3/4in.)
Thesis (undergraduate)
College of Science--
Includes bibliography.
The study, Kubo: A Mobile-Based Food Planner and Recipe App with Object Detection, is a mobile application developed to lessen the time spent by individuals on menu planning and scheduling by assisting both experienced and aspiring cooks to access a variety of cuisines, manage and observe proper mealtime, and help to keep track of foods that they eat. This study specifically aims to design a Food Planner and Recipe App with the following features: (a) AI model to detect ingredients belonging to the classes of Ampalaya, Carrot, Kamatis, Kangkong, Okra, Repolyo, Sayote, Sitaw, Talong, and Upo using user’s mobile camera; (b) Generate Menu schedule according to user’s time availability and the scanned available ingredients; (c) Custom menu schedule according to
user’s preference; (d) Menu History for reference; and (e)Alarm Schedule based on Menu Schedule. The mobile application is developed using Flutter Framework with Dart Programming Language for its frontend, Visual Studio Code as an IDE, GCP for server hosting, Colab with TensorFlow 2.0 for AI Training, ExpressJS Framework, and NodeJS for the backend, and MongoDB and HIVE for the database. Before deployment, the developed mobile application undergone a series of Functionality and Portability Testing
wherein results indicate that the designed features of the app effectively and efficiently perform its tasks and responsibilities. Also, the performance of the developed mobile application is evaluated in conformance to ISO 25010 where the system garnered an overall mean rating of 3.68 with a descriptive equivalence of “Highly Acceptable” indicating that the system successfully passes all the criteria given by ISO 25010.
Artificial intelligence
Vegetables
Recipe generator
BTH QA 76 / S84 2022
KUBO: a mobile-based food planner and recipe app with object detection/ Jake Andrey F. Suerte, Lovelyn C. Tapales, Jerico C. Villariza, Marcial B. Zipagan jr. -- - Manila: Technological University of the Philippines, 2022. - xii, 164pages: 29cm. +1 CD-ROM (3/4in.)
Thesis (undergraduate)
College of Science--
Includes bibliography.
The study, Kubo: A Mobile-Based Food Planner and Recipe App with Object Detection, is a mobile application developed to lessen the time spent by individuals on menu planning and scheduling by assisting both experienced and aspiring cooks to access a variety of cuisines, manage and observe proper mealtime, and help to keep track of foods that they eat. This study specifically aims to design a Food Planner and Recipe App with the following features: (a) AI model to detect ingredients belonging to the classes of Ampalaya, Carrot, Kamatis, Kangkong, Okra, Repolyo, Sayote, Sitaw, Talong, and Upo using user’s mobile camera; (b) Generate Menu schedule according to user’s time availability and the scanned available ingredients; (c) Custom menu schedule according to
user’s preference; (d) Menu History for reference; and (e)Alarm Schedule based on Menu Schedule. The mobile application is developed using Flutter Framework with Dart Programming Language for its frontend, Visual Studio Code as an IDE, GCP for server hosting, Colab with TensorFlow 2.0 for AI Training, ExpressJS Framework, and NodeJS for the backend, and MongoDB and HIVE for the database. Before deployment, the developed mobile application undergone a series of Functionality and Portability Testing
wherein results indicate that the designed features of the app effectively and efficiently perform its tasks and responsibilities. Also, the performance of the developed mobile application is evaluated in conformance to ISO 25010 where the system garnered an overall mean rating of 3.68 with a descriptive equivalence of “Highly Acceptable” indicating that the system successfully passes all the criteria given by ISO 25010.
Artificial intelligence
Vegetables
Recipe generator
BTH QA 76 / S84 2022