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Author: search.filters.author.Juhong, AniwatSubject: search.filters.subject.Raspberry Pi

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    Design and Development of an Assistive System Based on Eye Tracking
    (2022-02-01)
    Paing, May Phu
    ;
    Juhong, Aniwat
    ;
    Pintavirooj, Chuchart
    This research concerns the design and development of an assistive system based on eye tracking, which can be used to improve the quality of life of disabled patients. With the use of their eye movement, whose function is not affected by their illness, patients are capable of communicating with and sending notifications to caretakers, controlling various appliances, including wheelchairs. The designed system is divided into two subsystems: Stationary and mobile assistive systems. Both systems provide a graphic user interface (GUI) that is used to link the eye tracker with the appliance control. There are six GUI pages for the stationary assistive system and seven for the mobile assistive system. GUI pages for the stationary assistive system include the home page, smart appliance page, eye-controlled television page, eye-controlled air conditional page, i-speak page and entertainment page. GUI pages for the mobile assistive system are similar to the GUI pages for the stationary assistive system, with the additional eye-controlled wheelchair page. To provide hand-free secure access, an authentication based on facial landmarks is developed. The operational test of the proposed assistive system provides successful and promising results.
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    Smart eye-tracking system
    (2018-05-30)
    Juhong, Aniwat
    ;
    Treebupachatsakul, T.
    ;
    Pintavirooj, C.
    This project is a smart eye tracking system which is designed for people with disabilities and elderly people. The concept of this research is to apply eye movement to control appliances, wheelchair and communicate with caretaker. This system comprises four components, imaging processing module, wheelchair-controlled module, appliances-controlled module and SMS manager module. The image processing module consists of webcam and C++ customized image processing, the eye movement image is captured and transmitted to Raspberry Pi microcontroller for processing with OpenCV to derive the coordinate of eye ball. The coordinate of eye ball is utilized for cursor control on the Raspberry Pi screen to control the system. Besides the eye movement, the eye blink is applied in this system for entering a command as when you press Enter button on keyboard. The wheelchair-controlled module is a cradle with two servos that can be moved to two dimensions and also adaptable to other wheelchair joysticks. This system also remotely controls some appliances and communicate with caretaker via send message to smartphone.
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    Smart wheelchair based on eye tracking
    (2017-02-21)
    Wanluk, Nutthanan
    ;
    Visitsattapongse, Sarinporn
    ;
    Juhong, Aniwat
    ;
    Pintavirooj, C.
    This project is a smart wheelchair based on eye tracking which is designed for people with locomotor disabilities. The add-on controlled module can be used with any electrical wheelchair. The smart wheel chair consists of four modules including imaging processing module, wheelchair-controlled module, SMS manager module and appliance-controlled module. The image processing module comprises of a webcam installed on the eyeglass and C++ customized image processing software. The captured image which is transmitted to raspberry Pi microcontroller will be processed using OpenCV to derive the 2D direction of eye ball. The coordinate of eyeball movement is then wirelessly transmitted to wheelchair-controlled module to control the movement of wheel chair. The wheelchair-controlled module is two dimensional rotating stages that installed to the joystick of the electrical wheelchair to replace the manual control of the wheelchair. The motion of eyeball is also used as the cursor control on the raspberry Pi screen to control the operation of some equipped appliance and send message to smart phone.