HearNear vs EyeSearch

HearNear is an AI-assisted application specially designed for visually impaired friends, acting as a thoughtful companion that transforms the surrounding environment into voice descriptions anytime, anywhere. Through simple photo captures, videos, voice or text inputs, visually impaired individuals can easily navigate various scenarios in daily life. At home, HearNear helps you locate everyday items, assists with kitchen operations, and even provides outfit suggestions. Reading books, newspapers, and product instructions becomes simple and convenient. When going out, HearNear helps you navigate paths, avoid obstacles, find shops, and identify bus stops. While shopping, it can recognize products, check price tags, and read product descriptions - these are all ways HearNear can provide assistance. HearNear is simple to operate, using voice-guided interfaces and prompts that are easy to learn. More importantly, it is available 24/7, ready to describe your surroundings anytime, anywhere. HearNear, exploring a wider world with you! ※ Friendly Reminder ※ HearNear App's assistance functions are based on AI information recognition and processing technology. Environmental interpretation results may contain errors, so it's recommended to use them in conjunction with actual situations. In scenarios involving personal safety, we suggest using the app with family members or friends present to ensure safety.

EyeSearch uses your iPhone camera to detect a specific stickered items in real time, helping you quickly locate the object it's attached to. Designed for people with low vision, EyeSearch gives you a visual guide without requiring you to rely on small text or fine details. Simply open the app, point the camera, and let it do the searching. Key features: • Real-time sticker detection using camera. • Works entirely offline, no data is sent to any server • Privacy-first: your camera feed is never stored or shared EyeSearch is built with accessibility in mind, providing a simple and fast experience for everyone. A project developed at Apple Developer Academy | UCB by Victória Martins, Raquel Souza, Daniela Carvalho, Paulo Henrique, and Manoel Pedro, under the mentorship of Felipe Carvalho and Júlio Santos.