In this work, an attempt was made to find a suitable gripping pattern for a 3D-printed finger gripper made of PLA material. Experiments were conducted to measure the bending angle and recovery time for different geometric gripping patterns to evaluate the finger gripping performance. The performance of different geometric patterns, namely circular, square and triangle, was evaluated based on the maximum bending angle achieved and the minimum time required for the fingers to recover their original shape. The optimized gripping pattern is then used for the specific application in the current work, and the results of this work were further used to develop a robotic gripper using a shape memory nitinol alloy as a tactile sensor. Integrating nitinol wires into the finger gripper, this study can measure the deformation of the wires upon contact with an object and use this information to create a feedback system that can adjust the gripping force appropriately. It was found that there is a significant change in two voltage groups that cause the soft gripper to respond with and without object at 95% confidence level, and the P-value is found to be less than 0.05. This approach allows the use of the Arduino IoT cloud for remote control of the gripper to adjust objects of different shapes and sizes and apply the appropriate force for safe and effective manipulation remotely.