International Journal of Electrical and Computer Engineering (IJECE) Vol. 12, No. 2, April 2022, pp. 1548~1557 ISSN: 2088-8708, DOI: 10.11591/ijece.v12i2.pp1548-1557  1548 Journal homepage: http://ijece.iaescore.com Super-linear speedup for real-time condition monitoring using image processing and drones Moath Alsafasfeh 1 , Bradley Bazuin 2 , Ikhlas Abdel-Qader 2 1 Department of Computer Engineering, College of Engineering, Al-Hussein Bin Talal University, Ma’an, Jordan 2 Department of Electrical and Computer Engineering, College of Engineering and Applied Sciences, Western Michigan University, Kalamazoo, United States Article Info ABSTRACT Article history: Received Sep 30, 2020 Revised Oct 20, 2021 Accepted Nov 4, 2021 Real-time inspections for the large-scale solar system may take a long time to get the hazard situations for any failures that may take place in the solar panels normal operations, where prior hazards detection is important. Reducing the execution time and improving the system’s performance are the ultimate goals of multiprocessing or multicore systems. Real-time video processing and analysis from two camcorders, thermal and charge-coupling devices (CCD), mounted on a drone compose the embedded system being proposed for solar panels inspection. The inspection method needs more time for capturing and processing the frames and detecting the faulty panels. The system can determine the longitude and latitude of the defect position information in real-time. In this work, we investigate parallel processing for the image processing operations which reduces the processing time for the inspection systems. The results show a super-linear speedup for real-time condition monitoring in large-scale solar systems. Using the multiprocessing module in Python, we execute fault detection algorithms using streamed frames from both video cameras. The experimental results show a super- linear speedup for thermal and CCD video processing, the execution time is efficiently reduced with an average of 3.1 times and 6.3 times using 2 processes and 4 processes respectively. Keywords: Large-scale solar system Multiprocessing Real-time inspection Superliner speedup Thermal video This is an open access article under the CC BY-SA license. Corresponding Author: Moath Alsafasfeh Department of Computer Engineering, Al-Hussein Bin Talal University University Road King Hussien Bin Talal University Str، Ma'an, Jordan Email: moath.alsafasfeh@ahu.edu.jo 1. INTRODUCTION Many real-time applications including video processing need an algorithm to be executed in parallel on multicore or a multiprocessor system. Multicore or multiprocessor with parallel programming is used to address performance improvement. To achieve such i mprovements, efficient utilization of thread-level parallelism is elemental. In fact, the ability to divide the tasks among a multicore or multiprocessor system is sub-linear, linear, or superliner speedups. A multicore system adds processing power with minimal latency which delivers significant performance benefits for software. This trend is shaping the future of software development toward parallel programming [1]. This benefit will be clear in applications which have huge input data and work in real time. Parallelism can be used at the system level by spreading the workload of the handling requests among the processors and disks. Data level parallelism (DLP) is enabled data parallel reads and writes via distributing data across many disks. Taking advantage of instruction level parallelism (ILP) via an individual processor is also critical to achieving high performance, and pipelining is the simplest way to do this. Parallelism can also be employed at the level of detailed digital design; for example, modern all-