Choudhary, Monika and Kumari, Sushma and Chaulya, Swades Kumar and Mohan Prasad, Girendra and Kumar, Vikash and Kumar , Naresh (2022) Perceptive Driving Assistant System for Opencast Mines During Foggy Weather. Mining, Metallurgy & Exploration.

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Abstract

During harsh weather conditions, the presence of fog, dust in the environment degrades the image’s quality, which affects the visibility of drivers of heavy earth-moving machinery in opencast mines. Due to low visibility, mining operations cannot be carried out as drivers are easily prone to accidents. This paper proposes a technique that includes developing a vision enhancement system called perceptive driving assistant system for increasing visibility of real-time video of the road in front of the vehicle for operators of heavy earth-moving machinery at opencast mines during harsh weather conditions to overcome the problem. The system consists of high-quality Internet Protocol cameras and thermal cameras for real-time image processing and other well-defined devices, which is quite capable of enhancing the visibility of the image, outlining edges of the road, and detecting obstacles present on the path of operators for smooth driving and reducing threat of accidents. A high-speed graphical processing unit has been used for quality-performance parallel computing, which is well suited for real-time operations to empower fast real-time operations. The calculated frame per second (fps) of image enhancement, object detection, and edge detection is 17.91, 15.91, and 25.09 fps, respectively. The actual frame rate is 26.07 fps, and after applying the algorithm, the final frame rate is 19.65 fps. The calculated accuracy of the object detection model is 81.23%. Field trials indicate that the developed system has performed adequately during foggy weather.

Item Type:	Article
Uncontrolled Keywords:	Convolution neural network Edge detection Image defogging Object detection Foggy weather
Subjects:	Instrumentation
Divisions:	UNSPECIFIED
Depositing User:	Mr. B. R. Panduranga
Date Deposited:	22 Sep 2022 04:41
Last Modified:	22 Sep 2022 04:41
URI:	http://cimfr.csircentral.net/id/eprint/2534

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