International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 03 | Mar 2023
p-ISSN: 2395-0072
www.irjet.net
GLOVE BASED GESTURE RECOGNITION USING IR SENSOR J. Bharath Krishnaa1, R. Haritha2, G.D. Haritha3, J. Shri Lekha4, S.R. Malathi5 12345
Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, Tamil Nadu ---------------------------------------------------------------------***--------------------------------------------------------------------to communicate in real time. Hardware and software are Abstract - In recent times, thanks to the support of cutting-
combined to create technologies. Hardware and software are combined to create technologies. Before producing speech and a display, the device will use the micro-controller to process human gesture input. The only method to share our opinions is through communication. It is not anticipated that this will limit them in any manner. As a result, those who are deaf and dumb find it difficult to communicate with others, so it is crucial to create a model that is both practical and appropriate for them. As a result, we primarily communicate through hand gestures and a tool called SMART SPEAKING GLOVE. This technology uses an embedded IR sensor in gloves to enable and detect hand gesture recognition. This is accomplished by measuring the quantity of light that strikes the receiver, which is positioned in front of the transmitter, and conveying the meaning of the hand gesture in the form of an output in the form of a display and voice. People with speech impairments have trouble verbally speaking, whereas those with hearing impairments have trouble hearing what other people are saying. Both communication and safety-related issues are our focus. Speech-impaired people must deal with both problems as a result, which is where our smart speaking glove comes in. In the actual world, using this glove will be both immensely advantageous and demanding. The deaf and dumb have more security challenges than social contact problems. This project's originality derives from resolving this problem.
edge technology interfaces, the development of hand gesture recognition systems has drawn greater attention. Additionally, sign language recognition was primarily created to aid in communication between dumb and deaf people. Various image processing approaches, including segmentation, optimization, and classification, are used in conventional works to recognize hand gestures. Although it takes more time to recognize patterns, there are fewer false positives, higher error rates, and incorrect computation outputs as a result of the primary issues with inefficient processing of huge dimensional datasets. Therefore, the goal of this project is to create an effective hand gesture recognition system employing an inexpensive but effective IR sensor that is integrated into the gloves. The light obtained by the IR sensor, which is positioned across from the light emitting diode, is used to recognize the hand gesture. The LCD screen shows the hand gesture's meaning, and an audio message is also played through the speaker. Comparing the suggested method to the current ones reveals that it is more accurate and has a lower error rate. People with communication impairments have more interaction and security difficulties. The importance of this endeavour resides in finding solutions to these issues. By pushing a buzzer button, the suggested smart speaking glove can notify users of alerts and their current location. Our main goal is to address both the safety-related and communication-related problems. The proposed system's experimental results show that both have been accomplished. The gap between normal people and speech-impaired persons will be greatly improved by implementing the same method in real-time apps.
2. LITERATURE REVIEW In their study described in [1], A. Z. Shukor et al focused-on individuals who are deaf and mute, emphasizing their reliance on sign language for communication. However, communicating with non-sign language users poses a significant challenge for them, particularly in educational, social, and work environments. To address this issue, the researchers aimed to develop a sign language translation system that would facilitate communication between hearing or speech-impaired individuals and those who do not understand sign language. Additionally, they sought to evaluate the accuracy of this system in interpreting sign language. The sign language translation system they developed utilized a data glove configuration. It incorporated 10 tilt sensors to capture finger flexion, an accelerometer to detect hand motion, a micro-controller, and a Bluetooth module to transmit interpreted information to a mobile phone. The researchers conducted several experiments to assess the performance of the tilt sensors and the overall
Key Words: GSM & GPS module, Arduino Nano, Hand gesture recognition, Speaker & Display output, IR sensor.
1.INTRODUCTION The World Federation of the Deaf and the WHO estimate that 70 million persons worldwide are both deaf and mute. There are 300 million people in the globe, 32 million of whom are deaf. Most people with speech and hearing issues cannot read or write in commonly used languages. In order to communicate with others, deaf and mute people utilise sign language (SL), which is their native speech. More often than speaking, gestures in sign languages—including the use of finger movements, hand motions, and facial expressions— are used to convey messages. This project's major goal is to make it possible for hearing and speech-impaired individuals
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