Sight Seer

Description: Developed an assistive device named "Sight Seer" to support visually impaired and blind

individuals in their daily activities through face recognition, obstacle detection, and text recognition.

Features:

• Face Recognition: Implemented with ESP32 cam for face registration and recognition, integrated with a

mobile app via HTTP requests.

• Obstacle Detection: Utilized Arduino Uno for real-time obstacle detection to aid navigation.

• Text Recognition: Leveraged Google ML Kit's Text Recognition in Flutter to recognize text and convert

it to speech using Flutter TTS.

• Mobile Integration: Created a Flutter mobile application that streams video from the ESP32 cam using

MJPEG and captures screenshots via MQTT protocol. The app allows users to select functionalities

through speech-to-text commands and manages all processing models. Technologies Used: ESP32 cam,

Arduino Uno, Visual Studio Code, Dart, Flutter, Google ML Kit, HTTP requests, MQTT protocol.

Outcome: Delivered a highly accurate and effective assistive device with seamless hardware-software

integration, providing a practical solution with minimal UI but reliable performance for visually

impaired individuals.