Digital Forensics and Internet of Things. Группа авторов

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Digital Forensics and Internet of Things - Группа авторов


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circuit diagram. We used the Arduino IDE for programming for the desired outcomes.

A photograph of the complete hardware and the components used. A photograph of the complete hardware and the components used.

      3.2.1 Data Analysis

      Table 3.1 shows how we use an algorithm to regulate the motion of a wheelchair. The method is very simple, as previously mentioned, for a wheelchair whose motion is controlled with your index finger. The system was carried out with the same finger posture for the purpose of referring to it as the stable movement or “neutral position”. The wheelchair is propelled by electric motors that are operated by hand gloves that have a movement sensing system attached to them and are set to start mode.

Index finger Input from Arduino Directions
D1 D2 D3 D4
Stable 0° 0 0 0 0 No movement
Bend to Right 45° 0 0 0 1 Right movement
Bend to Left 45° 0 0 1 0 Left movement
Bend to Backward 45° 1 0 0 0 Reverse movement
Bend to Forward 45° 0 1 0 0 Forward movement

      The future scope of this work is to use this gesture-based wheelchair in old age homes where the implementation will be useful for the people who find difficulty in their movements. This can be improved by many advancements such as, for physically challenged people who are unable to move their hands, they may have a wheelchair developed with a tongue motion driver to drive the wheelchair’s motors. It is also possible to have a speed control feature. For safety measures, we can implement high-power sensor like ultrasonic sensor for object detection. Self-power generation from the rotation of the wheel could be possible in the future, with the device being charged by solar power. Therefore, the stress associated with charging the battery may be alleviated. Artificial Intelligence can also be included to make wheelchair more technically advance.

      2. Kazerooni, H., Fairbanks, D., Chen, A., Shin, G., The Magic Glove, University of California Berkeley, Berkeley, California, 2006.

      3. Zimmerman, T.G. et al., A Hand Gesture Interface Device. II Proc. Human Facttors in Computing System and Graphics Interface, ACM Press, New York, April 1987.

      4. Anoop, K.J., Ezhilan, I., Raj, S., Seenivasan, R., Pandian, C., Designing and modeling of controlled wheel chair incorporated with home automation. Int. J. Adv. Res. Electr. Electron. Instrum. Eng., AnISO 3297:2007 Certified Organization). 3, 2, 2014.

      5. S. Interactive Glove - International Journal of Industrial Electronics and Electrical Engineering,

      6. International Journal of Engineering and Computer Science, 4, 9, pp. 14439–14442, Sep 2015.

      7. World Health Organization, World report on disability, 2011.

      8. Chowdhury, SM Mazharul Hoque, Smart wheelchair for disabled people, Diss. Jahangirnagar University, 2019.

      9. Warad, S., Hiremath, V., Dhandargi, P., Bharath, V., Bhagavati, P.B., Speech and flex sensor-controlled wheelchair for physically disabled people. Proceedings of 10th IRF International Conference, Pune, India, 01st June-2014.

      10. Shayban, N. and Muhammad, A.G.K., Wireless Head Gesture Controlled Wheelchair for Disable Persons presented by Shayban Nasif & Muhammad Abdul Goffar Khan (EEE Department Rajshahi University).

      * Corresponding author: [email protected]

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