Raspberry Pi Based Real-Time Hand-Gestures Recognition Using Flex Sensors

One of the most emergent field of research now-a-days is recognition of sign language and it?s the best way to communicate with mute/deaf people. Hand gesture recognition system provides an opportunity to deaf and dumb people to express their feelings and to properly communicate with other vocal/nor

Project Title

Raspberry Pi Based Real-Time Hand-Gestures Recognition Using Flex Sensors

Project Area of Specialization

Internet of Things

Project Summary

One of the most emergent field of research now-a-days is recognition of sign language and it’s the best way to communicate with mute/deaf people. Hand gesture recognition system provides an opportunity to deaf and dumb people to express their feelings and to properly communicate with other vocal/normal people without any interpreter or intermediate between them. The aim of this project is to provide such a source to the deaf and dumb so that they can easily express what they want to express. It also helps other people to understand the deaf and dumb by converting those sign gestures into text and voice. Our project consists of a hand glove which is internally equipped with five Flex sensors, one each for a finger. With the help of this glove we can easily recognize gestures in real-time. We recognize some gestures which include 0-9 numbers and some operational signs i.e. plus, minus, multiply and divide. With the afore said operational signs, we can also perform operations like addition, subtraction, multiplication and division. The results of these operations are then shown in the text as well as voice form.

Project Objectives

• To make communication easier between deaf and dumb people and normal people.
• To remove communication gap between deaf and dumb people and normal people.
• To provide efficient and user friendly product to users so it could be helpfull to deaf and dumb people.
• To create such an effective product which help and which is also cheap in cost so it can be accecable to everyone. 

Project Implementation Method

The design of our proposed methodology is based on a micro-processing unit and scalar sensors. The micro-processing unit which we are using in our proposed system is raspberry pi, with raspberry pi we can easily process and control other sensors. The sensors which we are using in our system are flex sensors. Flex sensors are scalar sensors which generates analog signals in real time. Analog signals are then converted into digital values by means of analog to digital converter (PCF-8591+ ADC0804 chip), we use analog to digital converter because raspberry pi is not capable to read analog signals. In order to combine sensors with each other in fix module or prototype we construct a hand glove which consist of five flex sensors among of which four flexes are directly connected to PCF-8591 and fifth flex is connected with ADC0804 chip because PCF can only take four inputs that’s why ADC0804 chip is used to take input from the fifth flex and convert the analog signals into digital values.Usually most of the deaf and dumb people in the world use/follow ASL (American Sign Language). ASL is a complete language for deaf and dumb people and it is used world widely. Here we are using the numbers (0, 1, 2, 3…., 9) from ASL and we will recognize the numbers by the help of digital values which are produced by flex sensor and converted by ADC sensors.

Benefits of the Project

• It will remove the communication gap between deaf and dumb person and normal person.
• it will be avalible in market as a product so that it could be usefull in real to deaf and dumb people.
• It would be not just helpfull to deaf and dumb people but it could also used for HCI (humen computer interaction).

Technical Details of Final Deliverable

• Raspberry pi is required as controlling and processing system.
• Flex sensors are required according to each finger (5 forone hand and 10 for both hands)
• Analog to digital converter is also required for converting flex sensors analog signals in to digital values.
• For further future work MPU6050 (gyroscope+acceleratometer) is also required.
• In future arduino mega is also required as analog to digital converter.

Final Deliverable of the Project

Hardware System

Type of Industry

IT

Technologies

Artificial Intelligence(AI), Internet of Things (IoT)

Sustainable Development Goals

Quality Education

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com