The main aim of this project is to design and develop a smart glove that converts Indian Sign Language (ISL) into voice output to help deaf and mute people communicate easily with others. The proposed system uses MEMS and flex sensor technology to recognize different hand gestures and convert them into corresponding voice messages through a speaker. An ultrasonic sensor is also used to detect obstacles in front of the user, while a vibration motor provides an alert to warn the user about nearby obstacles. This device is also helpful for people with physical disabilities and communication difficulties. The flex sensor is a unique component whose resistance changes according to the degree of bending. When the sensor is in a flat position, it has a nominal resistance. As the sensor bends, its resistance increases proportionally. The system consists of five flex sensors, an ADXL345 MEMS sensor, an ultrasonic sensor, and a vibration motor. These sensors are connected to an Arduino Nano, which collects the sensor data and sends the processed information to the Raspberry Pi 4. The Raspberry Pi 4 acts as the main controlling unit of the system. The speaker and LCD are connected to the GPIO pins of the Raspberry Pi 4. Based on the recognized hand gestures and predefined Indian Sign Language patterns, the Raspberry Pi processes the sensor data using a Python program and generates the corresponding voice output through the speaker. The LCD displays the recognized gesture or message. When the ultrasonic sensor detects an obstacle within the specified distance, the Arduino Nano activates the vibration motor to alert the user. At the same time, the Raspberry Pi provides a voice alert through the speaker. The entire system is mounted on a wearable glove and operates using a battery-powered supply. Thus, this project provides an effective, portable, and user-friendly solution for improving communication and obstacle awareness for visually independent movement.        

The main objectives of the project are:  

  To design a smart glove for converting Indian Sign Language into voice output.

  To help deaf and mute people communicate easily with others.

  To use five flex sensors to detect different finger movements and hand gestures.

  To use the ADXL345 MEMS sensor to identify hand movements and orientation.

  To use Arduino Nano for collecting and processing sensor data.

  To use Raspberry Pi 4 for gesture recognition and voice generation.

  To provide voice output through a speaker based on recognized hand gestures.

  To display the recognized messages on an LCD.

  To detect nearby obstacles using an ultrasonic sensor.

  To activate a vibration motor and voice alert when an obstacle is detected.

  To develop a portable, battery-operated system for easy use.          

The major building blocks of this project are:  

• Power supply.
• Raspberry pi4.
• Arduino nano.
• Five Flex sensors.
• ADXL335 MEMS.
• Vibration sensor.
• Ultrasonic sensor.
• Speaker.
• SD Card.
• LCD display.
• Glove.

        Software’s used:  

• Python programming.
• Raspbian OS.
• Express SCH for Circuit design.

            Block diagram:            

video: