The Covid’19 pandemic system affects the human life in worldwide and present artificial intelligent (AI) technology to save human lives and reduce the virus spread. Covid’19 virus affected large number of humans. So doctors and caretakers are not able to maintain the social distance to patients. In this paper, our proposed work is a automatic ultra sound imaging for detecting the lungs to find the covid-19 lung injury to compare monitoring modalities like radiographic or auscultation imaging, In “ultra sound” technology provides high diagnostic accuracy. In depth of data and color control using Multinomial Tactic Regression (MTR) algorithm for better performance a automatic lung image extraction using Convolutional Structural Network (CSN) and Natural Language Processing (NLP) technique are easily detect and improve performance for lung sound image noise reduction comparison an deep learning algorithm annotation process for ultra sound images is a complex and time consuming task, but NLP can increase its efficiency and speed.