The paper presents a smart approach for a real time inspection and selection of objects in continuous flow. In the proposed approach, parallel channels are carved on a planar substrate to contain object flow. Each channel operates independently by processing and selecting objects one by one using multiple sensing units. The sorting process is based on a 2 phase operative methodology defined 1) a self-learning step where the apparatus “learns” to identify objects ; 2) an operative selection process where objects are detected, classified using a decisional algorithm and selected in real time. The Project deals with an automated material handling system. It aims in classifying the colored objects by colour, size, which are coming on the conveyor by picking and placing the objects in its respective pre-programmed place. Thereby eliminating the monotonous work done by human, achieving accuracy and speed in the work. The project involve sensors that senses the object’s colour, size and sends the signal to the microcontroller. The microcontroller sends signal to circuit which drives the various motors of the robotic arm to grip the object and place it in the specified location. Based upon the detection, the robotic arm moves to the specified location, releases the object and comes back to the original position  .