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Object Detection Learning for Intelligent Self Automated Vehicles

Ahtsham Alam1, Syed Ahmed Abdullah1, Israr Akhter1, Suliman A. Alsuhibany2,*, Yazeed Yasin Ghadi3, Tamara al Shloul4, Ahmad Jalal1

1 Department of Computer Science, Air University, Islamabad, 44000, Pakistan
2 Department of Computer Science, College of Computer, Qassim University, Buraydah, 51452, Saudi Arabia
3 Department of Computer Science and Software Engineering, Al Ain University, Al Ain, 15551, UAE
4 Department of Humanities and Social Science, Al Ain University, Al Ain, 15551, UAE

* Corresponding Author: Suliman A. Alsuhibany. Email:

Intelligent Automation & Soft Computing 2022, 34(2), 941-955. https://doi.org/10.32604/iasc.2022.024840

Abstract

Robotics is a part of today's communication that makes human life simpler in the day-to-day aspect. Therefore, we are supporting this cause by making a smart city project that is based on Artificial Intelligence, image processing, and some touch of hardware such as robotics. In particular, we advocate a self automation device (i.e., autonomous car) that performs actions and takes choices on its very own intelligence with the assist of sensors. Sensors are key additives for developing and upgrading all forms of self-sustaining cars considering they could offer the information required to understand the encircling surroundings and consequently resource the decision-making process. In our device, we used Ultrasonic and Camera Sensor to make the device self-sustaining and assist it to discover and apprehend the objects. As we recognize that the destiny is shifting closer to the Autonomous vehicles that are the destiny clever vehicles predicted to be driver-less, efficient, and crash-fending off best city vehicles of the destiny. Thus, the proposed device could be capable of stumbling on the item/object for easy and green running to keep away from crash and collisions. It could additionally be capable of calculating the gap of the item/object from the autonomous car and making the corresponding decisions. Furthermore, the device can be tracked-able by sending the location continuously to the mobile device through IOT using GPS and Wi-Fi Module. Interestingly. Additionally, the device is also controlled with the voice using Bluetooth.

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Cite This Article

A. Alam, S. Ahmed Abdullah, I. Akhter, S. A. Alsuhibany, Y. Yasin Ghadi et al., "Object detection learning for intelligent self automated vehicles," Intelligent Automation & Soft Computing, vol. 34, no.2, pp. 941–955, 2022.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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