<p>Recent advances in artificial intelligence-based object detection and multi-sensor fusion have significantly improved the performance of Situational Awareness (SA) systems for Maritime Autonomous Surface Ships (MASS). However, it cannot yet be guaranteed that the performance of these sensors is equivalent to or surpasses the SA which have done by the Officer of the Watch (OOW). This paper analyzes recent studies and ongoing research to identify aspects that have not been sufficiently addressed and presents key considerations for the design of SA systems for MASS. First, based on the analysis of the human SA model, it is explained that the main difference between humans and current sensor-based systems lies in active information acquisition and the integration of heterogeneous information. Most of the current research mainly focuses on data processing and fusion after data acquisition, while various types of information provided by operational support systems tend to increase system complexity without sufficient consideration of reliable integration. To address these limitations, two key design directions are proposed in this study. The first is an active sensing-based data acquisition structure, where sensors and algorithms are adaptively adjusted at the moment of object detection to obtain higher quality data. The second is the use of external information from operational support systems to compensate for the physical limitations of onboard sensors, with emphasis on clear and reliable data rather than complex information. In conclusion, future SA system design should consider not only detection and fusion techniques but also high-quality data acquisition. In particular, improving information at the time of detection and ensuring reliability are expected to play an important role in achieving safer MASS operation.</p>