Plantar gait monitoring is an important aspect of clinical monitoring as diagnosis to determine the existence of walking abnormalities in patients. The current procedure followed within clinics is physical observation or making the use of platform systems. These methods are prone to bias and the psychological phenomena of Hawthorne Effect. Other more sophisticated methods prove to be expensive or infeasible to the average consumer class. To this end, we have developed a novel gait monitoring system: I-Gressus that can be worn by the patient for natural gait monitoring over long periods of time with an additional cloud based data logging capability. The system makes use of resistive pressure sensing array mounted on an insole controlled via an ESPS266 WiFiSoC which logs data wirelessly on a cloud based web application. This footwear can be worn throughout the day for continuous monitoring and is relatively inexpensive to manufacture and maintain. To evaluate the devised prototype testing scenarios with various control cases have been performed. The resulting analysis shows that the model is capable of rapid diagnosis and data logging that outperforms the utility offered by various other gait monitoring frameworks under the price of 135. © 2020 IEEE.