| Issue |
E3S Web Conf.
Volume 399, 2023
International Conference on Newer Engineering Concepts and Technology (ICONNECT-2023)
|
|
|---|---|---|
| Article Number | 01013 | |
| Number of page(s) | 8 | |
| Section | Electronics and Electical Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202339901013 | |
| Published online | 12 July 2023 | |
MEM Based Hand Gesture Controlled Wireless Robot
1 Department of Electronics And CommunicationEngineering Prince shri Venkateshwara Padmavathy Engineering College, Chennai, India
2 Department of Electronics & Communication Engineering, IES College Of Technology, Bhopal, MP 462044 India
3 Tashkent State Pedagogical University, Tashkent, Uzbekistan
4 Assistant professor, Department of mechanical Engineering, K. Ramakrishnan college of technology, Tiruchirappalli
* Corresponding author: mercilinraajini.eee@psvpec.in
research@iesbpl.ac.in
boby_1986@bk.ru
yokesys@gmail.com
The robustness of MEMS based Gesture Controlled Robot is a kind of robot that can be by our hand gestures rather than an ordinary old switches or keypad. In Future there is a chance of making robots that can interact with humans in a natural manner. Hence our target interest is with hand motion-based gesture interfaces. An innovative Formula for gesture recognition is developed for identifying the distinct action signs made through hand movement. A MEMS Sensor was used to carry out this and also an Ultrasonic sensor for convinced operation. In order to full-fill our requirement a program has been written and executed using amicrocontroller system. Upon noticing the results of experimentation proves that our gesture formula is very competent and it’s also enhanced the natural way of intelligence and also assembled in a simple hardware circuit.
Key words: Mems / Zigbee / Ultrasonic Sensor
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.