Unknown Organization (20240282218). A PORTABLE ASSISTIVE DEVICE FOR CHALLENGED INDIVIDUALS simplified abstract
Contents
- 1 A PORTABLE ASSISTIVE DEVICE FOR CHALLENGED INDIVIDUALS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 A PORTABLE ASSISTIVE DEVICE FOR CHALLENGED INDIVIDUALS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Sign Language Translation Devices
- 1.13 Original Abstract Submitted
A PORTABLE ASSISTIVE DEVICE FOR CHALLENGED INDIVIDUALS
Organization Name
Inventor(s)
Aishwarya Karnataki of Pimple Saudagar, Pune (IN)
Parikshit Sohoni of Warje, Pune (IN)
A PORTABLE ASSISTIVE DEVICE FOR CHALLENGED INDIVIDUALS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240282218 titled 'A PORTABLE ASSISTIVE DEVICE FOR CHALLENGED INDIVIDUALS
Simplified Explanation
This patent application describes a portable assistive device that can convert sign language into text and speech. It consists of three wearable devices and a handheld device that communicate with each other. The first wearable device displays gestures, the second wearable device emits and captures audio, and the third wearable device receives gesture input. A server hosted on a cloud environment converts gesture data into text or speech using machine learning and artificial intelligence algorithms.
Key Features and Innovation
- Portable assistive device converting sign language to text and speech
- Three wearable devices and a handheld device that communicate with each other
- First wearable device displays gestures, second wearable device emits and captures audio, third wearable device receives gesture input
- Server hosted on a cloud environment converts gesture data into text or speech using machine learning and artificial intelligence algorithms
Potential Applications
This technology can be used in:
- Education settings for deaf or hard of hearing individuals
- Communication assistance for those who use sign language
- Accessibility tools for public spaces and events
Problems Solved
- Barrier to communication for deaf or hard of hearing individuals
- Lack of real-time translation of sign language
- Limited accessibility options for sign language users
Benefits
- Improved communication for deaf or hard of hearing individuals
- Real-time translation of sign language to text and speech
- Enhanced accessibility in various settings
Commercial Applications
- Title: "Sign Language Translation Device for Enhanced Communication"
- Potential commercial uses in education, healthcare, customer service, and public events
- Market implications include increased accessibility and inclusivity for sign language users
Prior Art
There may be prior art related to sign language translation devices, gesture recognition technology, and assistive devices for individuals with disabilities.
Frequently Updated Research
Stay updated on advancements in machine learning algorithms for gesture recognition and artificial intelligence for language translation.
Questions about Sign Language Translation Devices
How does this technology improve communication for deaf individuals?
This technology enables real-time translation of sign language into text and speech, allowing for better understanding and communication.
What are the potential applications of this sign language translation device?
This device can be used in education, healthcare, customer service, and public events to enhance communication for sign language users.
Original Abstract Submitted
a portable assistive device converting sign language to text and speech includes a first wearable device a second wearable device a third wearable device and a handheld device the first wearable device and second wearable device receives gestures input through plurality of sensors and the first wearable device the second wearable device the third wearable device and the handheld device independently communicate with each other. the first wearable device displays gestures on the display unit the second wearable device emits and captures audio through a speaker and a microphone respectively. the server preferable hosted on cloud environment converts the gesture data into text or speech using machine learning and artificial intelligence algorithms.
