scholarly journals Electronic Travel Aid for Visually Impaired People based on Computer Vision and Sensor Nodes using Raspberry Pi

2016 ◽  
Vol 9 (47) ◽  
Author(s):  
Ram Tirlangi ◽  
Ch. Ravi Sankar
Author(s):  
Tejal Adep ◽  
Rutuja Nikam ◽  
Sayali Wanewe ◽  
Dr. Ketaki B. Naik

Blind people face the problem in daily life. They can't even walk without any aid. Many times they rely on others for help. Several technologies for the assistance of visually impaired people have been developed. Among the various technologies being utilized to assist the blind, Computer Vision-based solutions are emerging as one of the most promising options due to their affordability and accessibility. This paper proposes a system for visually impaired people. The proposed system aims to create a wearable visual aid for visually impaired people in which speech commands are accepted by the user. Its functionality addresses the identification of objects and signboards. This will help the visually impaired person to manage day-to-day activities and navigate through his/her surroundings. Raspberry Pi is used to implement artificial vision using python language on the Open CV platform.


Author(s):  
Puru Malhotra and Vinay Kumar Saini

he paper is aimed at the design of a mobility assistive device to help the visually impaired. The traditional use of a walking stick proposes its own drawbacks and limitations. Our research is motivated by the inability of the visually impaired people to ambulate and we have made an attempt to restore their independence and reduce the trouble of carrying a stick around. We offer a hands-free wearable glass which finds it utility in real-time navigation. The design of the smart glasses includes the integration of various sensors with raspberry pi. The paper presents a detailed account of the various components and the structural design of the glasses. The novelty of our work lies in providing a complete pipeline for analysis of surroundings in real-time and hence a better solution for navigating during the day to day activities using audio instructions as output.


—Technology is best when it brings people together. Today technology plays a vital role in humanity. Also applied science can make the impossible possible. The proposed project aims to show equality in the safe navigation of visually impaired people just like a normal person. The project aims to help the secure guidance of humans with bad eyesight. This system support the sole in attaining the landing place, leading them across the way and alert them about the barrier that are expected in their path through the vibration and generate simulated speech output through headset. Therefore, this technology hold back them from striking the barrier. It add on value to conventional canes with barrier predicting, preventing human from accident and reducing difficulties in navigation. An ultrasonic sensor is execute to determine the distant of obstacles from the person. It is a Raspberry Pi based platform that is used to alert the person of impending obstacles. Also can create the place for all other components and it has functioning code. Here, a vibration motor is used to warn the person from the collision. Combined with the role of guiding, it also has aid preventing plan in case of emergency. The GPS is included to find the location of person and the location is sent to the person’s family through the notification by means of Blynk app. Accordingly, The project convince the visually impaired people can travel alone without getting fear or accidents at the moment.


The object detection is used in almost every realworld application such as autonomous traversal, visual system, face detection and even more. This paper aims at applying object detection technique to assist visually impaired people. It helps visually impaired people to know about the objects around them to enable them to walk free. A prototype has been implemented on a Raspberry PI 3 using OpenCV libraries, and satisfactory performance is achieved. In this paper, detailed review has been carried out on object detection using region – conventionaal neural network (RCNN) based learning systems for a real-world application. This paper explores the various process of detecting objects using various object detections methods and walks through detection including a deep neural network for SSD implemented using Caffe model.


Author(s):  
Ali Hojjat

Indoor navigation systems must deal with absence of GPS signals, since they are only available in outdoor environments. Therefore, indoor systems have to rely upon other techniques for positioning users. Recently various indoor navigation systems have been designed and developed to help visually impaired people. In this paper an overview of some existing indoor navigation systems for visually impaired people are presented and they are compared from different perspectives. The evaluated techniques are ultrasonic systems, RFID-based solutions, computer vision aided navigation systems, ans smartphone-based applications.


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