The critical stress problem is a crucial issue that needs considerations and requires a solution. A number of methods are used to identify and control the stress which includes different counseling programs and medication. But the diagnosis and identification of the stress and its levels is an important issue which does not have an on-time and accurate solution. Therefore, a non-invasive stress identification system is required that can identify stress and it's level. In this work, we have proposed and developed a non-invasive smart system for stress identification (SSSI). The SSSI takes human iris image and applies machine learning techniques to identify the level of stress based on the iridology map. While testing with 50 subjects having stress, the results confirm that the SSSI identifies the stress with an accuracy of 98%.