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In the era of machine intelligence, dynamic gesture recognition is assumed to be a difficult and challenging problem because it involves the human element. Moreover, the gestures formed for a particular problem vary from person to person. Therefore, the accuracy of classification sometimes becomes inappropriate. Also, gesture recognition is affected by lag in detection; however, a negative lag is assumed to be favorable. In this paper, an attempt has been made to control the system volume through hand gesture recognition which may help in the remote operation of a device and differently-abled people. The YOLO algorithm will deep learning approach is used in this paper, which detects hand movement and its direction. Based on the direction of hand movement, the volume can be increased or decreased. [ABSTRACT FROM AUTHOR]