No abstract

No abstract

No abstract

Most important part in human’s life is our six senses, if we are not having any one of the senses, it will be more difficult to run our day to day life. Here we are going to help the visually impaired peoples to listen where there are and what are they going to do next as a sense in our body. visually impaired usually get information for their next move from others, this may create a inferiority complex to them that they can’t be like normal human beings, they are always dependent on others. To make them fell self-confident and to face their obstacles by themselves we have specially customized a smart cap for visually impaired peoples, as they can help them in their day to day life. Vision plays a significant role. Persons without vision can gather information through their hearing skills. The proposed system is an innovative implementation of a smart guidance system for those with vision. The system is a novel and real-time cost-effective technique. The system consists of three modules: voice search module, image processing module and voice processing module. These modules are executed using the keyword function search, which is in voice form, provided by the user. The system combines the concept of optical character recognition and the text to speech synthesizer. It involves extracting text from the image and translating the text into speech; this makes it easier for the user to read the text. From a computer standpoint, extracting text from color images is a difficult task. It can also be used to identify the bus name and bus number at the bus stop or bus stand for the blind and prevents it from being used by an ultrasonic sensor and is communicated to the user by the vibration sensing mechanism.

Drowsiness is a major cause of vehicle collisions and it most of the cases it may cause traffic accidents. This condition necessitates the need to develop a drowsiness detection system. Generally, the degree of sleep may be assessed by the number of eye blinks, yawning, gripping power on the steering wheel, and so on. These methods simply compute the actions of the driver. Henceforth, this research work proposes a Brain Computer Interface (BCI) technology to evaluate the mental state of brain by utilizing the EEG signals. Brain signal analysis is the main process involved in this project. Depending on the mental state of the drivers, the neurons pattern differs. Different electric brain signals will be produced in every neurons pattern. The attention level of brain signal varies from general state when the driver is sleeping mentally with eyes open. Various frequency and amplitude of EEG based brain signal are collected by using a brain wave sensor and the attention level is analyzed by using a level splitter section to which the brain signals are made into packets and transmitted through a medium. Level splitter section (LSS) figures out the driver’s state and provides a drowsiness alarm and retains the vehicle in a self-controlled mode until the driver wakes up. Additionally, this research work will provide an alert to the users and control the vehicle by employing the proposed model.