NutriLens is an AI-powered food analysis and recipe assistant designed to address the growing need for convenient and accurate nutritional information. Traditional methods of tracking food intake can be cumbersome and lack accuracy, leading to challenges in making informed dietary decisions. Our project aims to provide users with an easy-to-use tool that analyzes food items from images or descriptions and delivers comprehensive nutritional information.
Our research focuses on leveraging AI to accurately analyze food, provide personalized insights and recommendations, and make this information accessible and user-friendly. By combining the latest advancements in AI with a user-centric design approach, NutriLens aims to empower individuals to make healthier choices and improve their overall well-being.
The background for our project lies in the increasing prevalence of health issues related to diet and the rising interest in personalized nutrition. We believe that NutriLens can be a game-changer in how people interact with food, offering a painkiller solution that not only addresses a pressing need but also has the potential to significantly impact people's lives for the better.
| Name | Bangkit ID | Path | University | Contact |
|---|---|---|---|---|
| Zidan Qurosey Sabilla | M008D4KY3252 | Machine Learning | Universitas Gadjah Mada | LinkedIn,Kaggle |
| Adyuta Indra Adyatma | M214D4KY1952 | Machine Learning | Universitas Islam Indonesia | |
| Salsabila Sofia Azzahra | M011D4KX2131 | Machine Learning | Universitas Padjadjaran | |
| Faisal Ikhwan Arianto | C297D4KY1250 | Cloud Computing | UPN "Veteran" Yogyakarta | |
| Audito Onny Saputra | C297D4KY1258 | Cloud Computing | UPN "Veteran" Yogyakarta | |
| Ardy Fahriansyah | A012D4KY3869 | Mobile Development | Telkom University | |
| Pavel Manaf El Zaky | A012D4KY4057 | Mobile Development | Telkom University |
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