This paper presents a system for quality control of real-time panoramic views generated from the novel smart panorama camera 360SCAN. The system makes use of the modern image processing library OpenIMAJ and state-of-the-art features extraction and clustering methods. We compare a real-time frame collection recorded by the camera to a reference image collection in order to determine camera readiness. We conducted several experiments that verify the methods that demonstrate smart camera operational status and evaluate changes in the position or number of objects in the working location. All evaluations were performed in the natural environment with ambient illumination of 200 lux, which demonstrates high camera reliability in difficult light conditions. The system can be optimized for embedded applications by applying additional filters and features algorithms and by decreasing the rotational speed of the camera. The presented quality control system is a building block for a rich and qualitative expert system for the efficient control and support of the smart camera.