Situational awareness is the ability to understand what is happening in the surrounding environment, what that information means, and what may happen next. In defense and security settings, it depends on receiving timely, relevant information from cameras, sensors, vehicles, personnel, and other sources.
Understanding situational awareness is important because visibility alone is not enough. A system may collect large amounts of video and sensor data, but that information only becomes useful when operators can perceive important details, understand their significance, and use them to anticipate how a situation may develop.
The Three Levels of Situational Awareness
The commonly used levels of situational awareness are perception, comprehension, and projection. Together, they describe the progression from seeing information to understanding it and considering what may happen next.
Perception is the first level. It involves noticing relevant elements in the environment, such as a person, vehicle, object, movement, or change in conditions. Cameras and other sensors can expand what an operator is able to see, including areas outside the direct line of sight.
Comprehension is the second level. The operator connects the information being received and determines what it means in context. Using multiple video feeds, sensor inputs, metadata, and AI-supported analysis can help make activity easier to interpret.
Projection is the third level. Based on the current situation and how it is changing, the operator considers what may happen next. Reliable, low-latency information is important because delayed or incomplete video can affect that assessment.
Why Situational Awareness Matters in Defense and Security
Defense and security environments can change quickly. Operators may need to monitor several directions, follow moving objects, or work from inside a vehicle where direct visibility is limited. Situational awareness systems help extend the operator’s view beyond what can be seen directly.
The value comes from having current information that can be understood in context. Video from several cameras can provide broader visual coverage, while onboard processing can prepare those feeds for display, transmission, recording, or analysis. AI can add information such as object detection, classification, and tracking where the application requires it.
How Maris-Tech Supports Situational Awareness
Maris-Tech develops video and edge-computing systems for defense platforms, including armored vehicles, drones, unmanned systems, and surveillance applications. Its technology supports real-time video processing, low-latency streaming, recording, AI processing, and multi-sensor coverage.
These capabilities can support each of the three levels of situational awareness. Multiple camera feeds help operators perceive more of the environment. Video processing and AI-supported analytics can provide additional context for comprehension. Low-latency delivery helps keep the information current as operators assess how the situation may change.
More specific applications have their own requirements. Open-terrain operations may emphasize long-range observation and changing terrain. Vehicle systems can use 360-degree camera coverage to improve visibility around the platform. Drone-based systems can extend observation beyond the immediate area. Each applies the same core situational awareness concept in a different operational setting.
Related Maris-Tech Resources
Open Terrain Combat | 360 3D Monitoring | Situational Awareness Products
Frequently Asked Questions
What is situational awareness?
Situational awareness is the ability to perceive important elements in the surrounding environment, understand what they mean, and use that understanding to consider what may happen next.
What are the three levels of situational awareness?
The three levels are perception, comprehension, and projection. They move from noticing relevant information, to understanding its significance, to anticipating how the situation may develop.
How does video technology improve situational awareness?
Video technology can expand an operator’s view, provide feeds from multiple cameras or sensors, and deliver current imagery for monitoring and analysis. Low-latency processing and AI-supported analytics can add context and help operators interpret changing conditions.