Medigus Ltd. announced that ScoutCam Inc. and Elbit Systems Ltd. successfully completed a major development stage in the use of ScoutCam's real time video monitoring (RTVM) system. During the development stage, the RTVM system used on Elbit Systems' UAS platform acted as a replacement of manual pre and post flight visualization inspections of the aerial platform and provided clear visibility of areas that had previously been inaccessible to maintenance and operations teams. In addition, ScoutCam's RTVM provided visibility even when the operating ambience was not suitable for continuous real-time monitoring. ScoutCam's unique video-based sensors, embedded software, machine vision and algorithms support a variety of predictive maintenance and condition-based monitoring use cases for unmanned aerial vehicles in harsh environments and hard-to-reach locations.

ScoutCam's RTVM system features a modular open system architecture, enabling seamless integration with advanced unmanned aerial platforms. The RTVM system's size, weight, and power (SWaP) are small, making the system a suitable choice for most aerial applications. ScoutCam's RTVM offers a modular design solution based on the principles of open system architecture, and it consists of multiple highly resilient cameras installed in various locations around the UAS that are connected to an advanced central processing unit. The multi-camera system ensures critical flight safety in a UAS, supporting the identification and real-time analysis of failure modes.

The RTVM system allows for real-time monitoring of the health and condition of the UAS's mechanisms and components. Visual information is saved and processed using dedicated AI-based algorithms designed to recognize and alert for anomalies that deviate from the standard working nature of the monitored components. The system's built-in software supports a range of advanced applications including big data, AI, and image processing.

The data saved in the system supports the identification of failure modes, analysis of trends, and proactive prediction of failures.