In simple terms: Sentinel watches noise, flights, runway use, and weather together so that patterns which might bother communities are spotted and explained earlier.
This card shows how early Sentinel can see a developing airport noise or impact pattern compared with conventional reporting thresholds, giving operators extra time to investigate.
"Detected" shows when Sentinel first saw the pattern forming. "Threshold" is when a typical reporting limit or rule of thumb would notice the same thing. "Lead" is the extra warning time Sentinel provides.
Use this table to see where Sentinel gives you meaningful extra time to investigate, and where traditional triggers already catch issues quickly.
| Event | Threshold | Sentinel | Lead | Confidence |
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This card summarises Sentinel’s best guess about why the pattern looks abnormal, combining noise measurements, flight activity, runway mode, and weather context.
Each line here reads like a short case note: what changed, which part of the airport is involved, and a practical starting point for investigation.
These are structured hypotheses, not legal findings. They are designed to guide operator judgement, not replace it.
This card is a live snapshot of key airport noise and operational measurements, so you can see what is driving the current picture at a glance.
Think of this card as the cockpit view for the environment team: how loud it is, how many events there are, and what the runway and movements are doing right now.
The driver metric tells you which measure (for example SEL at night) is currently shaping the overall picture the most.
This card shows which influences—such as runway mode, track concentration, arrivals, departures, or wind-related propagation—look normal and which are behaving unusually.
Each row represents one influence on impact. If it shows "alert", that influence is currently making things worse; if it shows "healthy", it is behaving as expected.
Propagation captures how weather and wind direction are helping or hindering noise as it travels from the airport to communities.
This card breaks operations into states such as arrival-heavy, departure-heavy, night period, easterly operations, and westerly operations, then shows which states are most often linked to elevated impact.
States are the main "modes" the airport runs in, such as busy arrival banks, quieter periods, or specific runway configurations.
An anomaly rate closer to 1 means that, when Sentinel sees that state, it very often also sees unusual impact at one or more receptors.
This card looks at alert patterns over time and helps distinguish genuinely useful warnings from repeated noise chatter or one-off events.
Over time, this helps you see which alert patterns are genuinely worth acting on, and which ones mostly add noise or repeat information you already know.
Use this table to decide which alert codes should stay live, which might be downgraded, and where smarter grouping could reduce alarm fatigue.
| Severity | Pattern | Code | Freq | Outcome |
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This card shows how healthy each monitor and linked data feed is, so you can quickly see whether an unusual signal is likely to be real or a data issue.
If a monitor or feed is not "healthy", treat unusual readings from that source with caution until the issue is checked.
This helps separate real environmental change from sensor, processing, or communication problems.
This card summarises recent aircraft activity, including arrivals, departures, movement intensity, and track concentration, to help explain airport-related environmental impact.
More movements, more heavy jets, or tighter track patterns usually mean more potential for noticeable noise, especially when combined with certain runway modes and wind directions.
This card shows runway use and weather conditions such as wind direction and speed, helping explain why impact may be stronger in some locations or periods than others.
Wind direction is given as the direction the wind is coming from. Westerly sectors often line up with westerly runway use and can increase downwind impact for some receptors.
This card links what pilots and air traffic control are doing with how sound is likely to travel on the ground.
This card compares monitoring points or community zones, highlighting where impact is consistently better or worse and helping prioritise attention and action.
Each row is a place where sound is being measured. Higher levels or more events mean that community is currently experiencing more of the impact.
Use this card to see which areas are persistently hardest hit and whether that lines up with known routes and runway modes.
| Receptor | Location | Avg LAeq | Avg SEL | Night events/wk | Exceedance-like/wk | Status |
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