An augmented reality and machine learning iOS educational application
Tran, Dinh Linh (2018)
Tran, Dinh Linh
Metropolia Ammattikorkeakoulu
2018
All rights reserved
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2018112618348
https://urn.fi/URN:NBN:fi:amk-2018112618348
Tiivistelmä
The objective of this paper is to provide better understanding about augmented reality as well as machine learning technology. The study demonstrates the popularity and importance of these technologies at the time this paper is written. ARKit and Core ML are mainly discussed throughout the study. However, a few alternatives are also briefly examined. Furthermore, the study shows comprehensive information about how to train a machine learning model for iOS application. Together with thorough gained knowledge, a practical trailing goal is to create an appealing educational iOS application based on prevailing technologies.
The research is carried out with extensive explanations of the technologies. In addition, the paper provides a broad plan of how to create iOS application utilised ARKit and Core ML . Besides, details about how to train Core ML models that are compatible for iOS are discussed thoroughly.
During the time that this project was carried out, Camera Translator, an iOS application was under construction. The app is developed in Swift with support of CoreML and ARKit. Camera Translator was created as the final product of this project. The application targets youngsters with the age of six and above. With help of this application, for example a field trip to zoo would would be quite exciting to pupils. It is not only providing advanced new experience but also implicitly helping users to gain better knowledge about animals.
Camera Translator brings brand-new sense to zoo visitors by offering modern touch as well as informative observation. With supported functionalities, application is expected to gain wide-spread usage. What is more, improvements about information presentation as well as recognition accuracy are considered for further development.
The research is carried out with extensive explanations of the technologies. In addition, the paper provides a broad plan of how to create iOS application utilised ARKit and Core ML . Besides, details about how to train Core ML models that are compatible for iOS are discussed thoroughly.
During the time that this project was carried out, Camera Translator, an iOS application was under construction. The app is developed in Swift with support of CoreML and ARKit. Camera Translator was created as the final product of this project. The application targets youngsters with the age of six and above. With help of this application, for example a field trip to zoo would would be quite exciting to pupils. It is not only providing advanced new experience but also implicitly helping users to gain better knowledge about animals.
Camera Translator brings brand-new sense to zoo visitors by offering modern touch as well as informative observation. With supported functionalities, application is expected to gain wide-spread usage. What is more, improvements about information presentation as well as recognition accuracy are considered for further development.