Super-linear speedup for real-time condition monitoring using image processing and drones

Real-time inspections for the large-scale solar system may take a long time to get hazard situations any failures that place in panels normal operations, where prior hazards detection is important. Reducing execution and improving system’s performance are ultimate goals of multiprocessing or multicore systems. video processing analysis from two camcorders, thermal charge-coupling devices (CCD), mounted on drone compose embedded being proposed inspection. The inspection method needs more capturing frames detecting faulty panels. can determine longitude latitude defect position information real-time. In this work, we investigate parallel image operations which reduces results show super-linear speedup real-time condition monitoring Using module Python, execute fault algorithms using streamed both cameras. experimental CCD processing, efficiently reduced with an average 3.1 times 6.3 2 processes 4 respectively.