A novel approach as an AID for blind, deaf and dumb people

Rajapandian, B; Harini, V.; Raksha, D.; Sangeetha, V.

doi:10.1109/ssps.2017.8071628

Cited by 17 publications

(5 citation statements)

References 4 publications

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“…Figure 1 shows the block diagram of wind energy system used. Generator is very difficult to connect with grid directly, Converter is an interface between that two sections [9]. DFIG being a variable speed generator possess a distinct advantage over the fixed speed generators with regards to its variable speed capability.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of DC-DC converter using renewable energy sources

Rajapandian

Rajan

2020

IJPEDS

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This work analyses and evaluates the performance of renewable energy sources-based converters using Intelligent techniques. The objective of the research is to maintain the reliability of the converters such that it decreases the switching losses, high duty cycle and recycles the leakage energy. To accomplish the high output voltage gain converters are designed with different intelligent methods. Due to heavy demands, the cost of fossil fuel has gone up.so the need for the time is identifying and developing renewable energy sources along with developing new technologies for energy saving in renewable energy system to fight the issues plaguing the environment.

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Section: Methodsmentioning

confidence: 99%

Evaluation of DC-DC converter using renewable energy sources

Rajapandian

Rajan

2020

IJPEDS

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“…The second set of challenges involved user comfort, as a using of sensory glove required the user to wear a bulky glove contain of sensors , cables and circuit board which limited the user's hand mobility [8], [39], [14]. Wearable technology is often used with Arduino boards, sensors, and circuits, making the system a little bulky and huge [56]. The third set of challenges is related to the user is the difference in the size of the user's hand, which affects the system of hand gesture recognition such as in the case of a user with a smaller sized hand has less discrepancy when compared with a user with larger hands [57].…”

Section: ) the Challenges Related To Usersmentioning

confidence: 99%

“…Firstly, in terms of new technology, it is clear that many recommendations are dedicated to using a wireless connection technology through the employment of Wi-Fi technology [ 27 ] , Bluetooth technology [ 56 ] between devices, and the use of a microcontroller to solve the problem of cables that can disturb the hand movements [8], [ 101 ] . On the other hand, incorporating a processing unit together with Wi-Fi connectivity will give the system the ability to use online free translation engines and increase the speed and accuracy of the resulting words, sentences, and phrases .…”

Section: ) Recommendations Related To Developersmentioning

confidence: 99%

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A Systematic Review on Systems-Based Sensory Gloves for Sign Language Pattern Recognition: An Update From 2017 to 2022

et al. 2022

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Sign language is the predominant mode of communication for the Deaf community. For the millions of people who suffer from hearing loss around the world, interaction with people who have the ability to hear and do not suffer from hearing impairment or loss is considered as complicated. In line with this issue, technology is perceived as a crucial factor in being an enabler of providing solutions to enhance the quality of life of the Deaf and people with hearing impairment by increasing accessibility. This research aims to review and analyze articles related to sign language recognition based on the sensor-based glove system, in order to identify academic motivations, challenges, and recommendations related to this field. The search for the relevant review materials and articles was performed on four major databases ranging from 2017 to 2022: Science Direct, Web of Science, IEEE Xplore, and Scopus. The articles were chosen based on our inclusion and exclusion criteria. The literature findings of this paper indicate the dataset size to be open issues and challenges for hand gesture recognition. Furthermore, the majority of research on sign language recognition based on data glove was performed on static, single hand, and isolated gestures. Moreover, recognition accuracy typically achieved results higher than 90%. However, most experiments were carried out with a limited number of gestures. Overall, it is hoped that this study will serve as a roadmap for future research and raise awareness among researchers in the field of sign language recognition.

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“…G.F. Lourenço et al [27] designed an assistive device for VIP based on user satisfaction. Rajapandian et al [29] proposed an innovative tactic AID for blind, deaf and dumb people. [31] Foley A et al presented a review on Technology for people, not disabilities: ensuring access and inclusion.…”

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confidence: 99%

VisiSense: A Comprehensive IOT-based Assistive Technology System for Enhanced Navigation Support for the Visually Impaired

Pydala,

Kumar,

Baseer

2024

SCPE

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The field of visually impaired assistive technology looks for novel approaches to enhance independence and navigation. In this field, systems have to reliably identify and transmit environmental data in order to facilitate visually impaired users' safe and effective navigation. Developing a sophisticated framework for assistive technology that significantly enhances visually impaired navigation is the goal of this research. Make object detection and environmental awareness more efficient, dependable, and intuitive. This study introduces VISISENSE, "A Comprehensive IoT-Based Assistive Technology System for Enhanced Navigation Support for the Visually Impaired." VISISENSE is an IoT-based system with multiple components that enhances object detection. For primary environmental sensing, a handstick with implant sensors, a visual capture and transmission unit for processing visual data, and edge computing for object detection and classification are used. The system makes use of the R-CNN global computer vision model hosted on a cloud server, Mobinet computer vision models, and Logistic Regression with Iterative Learning. VISISENSE's effectiveness is demonstrated by a performance analysis of its object detection accuracy, processing speed, resource utilization, energy consumption, latency, and false positive rate. In all of these categories, VISISENSE performs better than Smart Stick and Smart Navigation. The data includes the fastest processing time of 17 ms, the most efficient resource utilization of 41%, and object detection accuracy of up to 99% at 2 Mbps load. Across all load conditions, VISISENSE has the lowest false positive rate, energy consumption, and latency. The VISISENSE assistive technology system is developed for the visually impaired. Its excellent object detection and navigation accuracy, speed, and efficiency enhance user experience and hold the potential to increase the independence and quality of life for visually impaired people. This research contributes to a significant advancement in assistive devices-smart, responsive technologies for the visually impaired.

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A novel approach as an AID for blind, deaf and dumb people

Cited by 17 publications

References 4 publications

Evaluation of DC-DC converter using renewable energy sources

Evaluation of DC-DC converter using renewable energy sources

A Systematic Review on Systems-Based Sensory Gloves for Sign Language Pattern Recognition: An Update From 2017 to 2022

VisiSense: A Comprehensive IOT-based Assistive Technology System for Enhanced Navigation Support for the Visually Impaired

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