Automatic voice detection of baby cry plays an outstanding role in different applications for smart monitoring of smart baby condition. In this proposed model, a baby’s cry is being detected and a music player will be played after detection in order to create a soothing environment for the baby. This system employs a machine learning approach to recognize newborn cry sounds in a variety of residential settings under difficult situations. The automatic detection of a baby cry can be used in a variety of situations involving various types of sounds in the environment. The proposed system also provided with alert-based notifications to parents. Also, in commercial used products such as remote monitoring of baby, baby facial recognition as well as in medical applications. Also, evaluate K-Nearest Neighbours (KNN) algorithm for baby cry detection and perform priority queue functions for playing music. In this system, the input consists of the cry sound with k nearest training samples in the database. The output is depended on analysis of the cry-detection performance with KNN which is used for classification.