The integration of computer vision and automation into Concentrated Solar Power (CSP) systems marks a transformative shift in how solar thermal plants are monitored, controlled, and maintained. Computer vision technologies, ranging from infrared thermography to drone-based imaging and machine vision, enable non-invasive, real-time analysis of optical and thermal performance across heliostat fields, receivers, and thermal energy storage units. Combined with automated control systems, these tools offer unparalleled accuracy, reduced operational costs, and enhanced safety. This chapter presents an in-depth analysis of the role of computer vision and automation in CSP operations. It explores various vision-based techniques for heliostat calibration, receiver flux monitoring, fault detection, and maintenance scheduling. The chapter also highlights the use of robotics, UAVs, and sensor networks in field automation. Case studies and implementations from commercial and pilot CSP plants are reviewed to demonstrate practical effectiveness. The synergy between real-time imaging, AI-based decision systems, and automated control frameworks is explored, showcasing how they collectively drive the future of smart CSP operations.