Jiaxuan Li¹ and Jonathan Sahagun², ¹USA, ²California State University, USA

Food insecurity is increasingly understood to involve not only access to food, but the nutritional literacy required to make healthful decisions, a literacy that is unequally distributed among low-income households, older adults, and people managing diabetes or hypertension. Existing nutrition apps assume time, connectivity, and the willingness to type every meal, which limits their reach. NutriLens is a wearable smart-glasses system that delivers real-time nutritional guidance hands-free by combining a Raspberry Pi camera, a Flutter iOS application, a custom Bluetooth Low Energy image-transfer service, Google Gemini vision-language inference, and a Vufine heads-up display. Challenges in BLE framing, JSON robustness, and per-user data isolation were resolved through chunked typed packets, schema-constrained prompts, and UID-scoped Firebase paths [5]. Across two experiments the system achieved a mean 5.5% calorie estimation error and a 13-second image transfer latency at default settings. NutriLens reframes nutrition tracking from a typing task into an ambient one

Gemini, Vision-language Model, Bluetooth Low Energy, Flutter, Raspberry Pi