How Detection Works
An overview of Grillo's earthquake detection system and how it identifies seismic events from your sensor network.
Detection overview
Grillo's detection system uses data from multiple sensors to:
- Identify potential earthquake signals
- Confirm events across multiple stations
- Calculate event parameters
- Generate alerts
The detection process
Step 1: Continuous monitoring
Each sensor in your network continuously streams data to Grillo Cloud:
- Real-time accelerometer data
- Typically 100 samples per second
- Data arrives with minimal latency
Step 2: Signal detection
Algorithms analyze incoming data for earthquake signatures:
P-wave detection:
- First seismic wave to arrive
- Faster but weaker
- Enables early warning
S-wave detection:
- Second wave type
- Slower but stronger
- More damaging
Step 3: Multi-station confirmation
A single sensor trigger isn't enough—confirmation requires multiple sensors:
| Sensors triggered | Action |
|---|---|
| 1 | Monitor, no event |
| 2-3 | Possible event, continue monitoring |
| 4+ | Likely event, begin characterization |
This multi-station approach:
- Reduces false positives
- Improves location accuracy
- Increases confidence
Step 4: Event characterization
Once confirmed, the system calculates:
Location (epicenter):
- Triangulation from multiple stations
- Uses arrival time differences
- Accuracy depends on network geometry
Depth:
- Estimated from arrival patterns
- May be constrained for shallow networks
Magnitude:
- Calculated from amplitude
- Multiple magnitude types possible
- Refined as more data arrives
Origin time:
- When the earthquake occurred
- Back-calculated from detections
Step 5: Alert generation
Based on event parameters:
- Event compared against alert thresholds
- Notifications sent to configured channels
- Event added to catalog
Detection parameters
Sensitivity
How sensitive the detection is to ground motion:
| Setting | Effect |
|---|---|
| High | More detections, more false positives |
| Medium | Balanced approach |
| Low | Fewer detections, fewer false positives |
Trigger threshold
The minimum signal level to consider:
- Lower = more sensitive
- Higher = fewer triggers
- Adjusted based on local noise
Confirmation requirements
How many sensors must trigger:
- More sensors = higher confidence
- Fewer sensors = faster detection
- Trade-off between speed and accuracy
Detection latency
Time from earthquake to detection:
| Stage | Typical time |
|---|---|
| Wave travel to first sensor | Varies by distance |
| First sensor trigger | Under 1 second |
| Multi-station confirmation | 2-5 seconds |
| Event characterization | 5-15 seconds |
| Alert delivery | Under 1 second |
Total time: Typically 5-20 seconds from earthquake origin
Early warning time
The warning time before strong shaking:
- Depends on distance from epicenter
- P-wave arrives before damaging S-wave
- Seconds to tens of seconds possible
What affects detection quality
Network factors
| Factor | Impact |
|---|---|
| Number of sensors | More sensors = better detection |
| Sensor spacing | Affects location accuracy |
| Geographic coverage | Larger area = detect more events |
| Online percentage | More sensors online = better coverage |
Data quality factors
| Factor | Impact |
|---|---|
| Installation quality | Poor mounting = noisy data |
| Site conditions | Soft soil can amplify noise |
| Local vibrations | Traffic, machinery interfere |
| Signal strength | Weak connectivity = gaps |
Event factors
| Factor | Impact |
|---|---|
| Magnitude | Larger events detected more easily |
| Distance | Closer events detected faster |
| Depth | Very deep events harder to locate |
Limitations
What we can detect
- Earthquakes within/near your network
- Events producing ground motion above noise
- Events triggering multiple sensors
What we cannot detect
- Very small earthquakes (below network threshold)
- Distant earthquakes (insufficient signal)
- Events during network outages
- Non-earthquake events (explosions, etc.) may trigger
False positives
Some non-earthquake events may trigger:
- Large vehicle traffic
- Industrial activity
- Weather (wind, thunder)
- Sensor malfunction
The multi-station confirmation reduces but doesn't eliminate false positives.
Improving detection
Optimize your network
- Add more sensors - Improves detection and accuracy
- Better distribution - Even spacing helps location
- Quality installations - Reduce noise
- Maintain sensors - Keep high online percentage
Fine-tune settings
- Adjust sensitivity - Based on false positive rate
- Set appropriate thresholds - Match your needs
- Review detections - Learn what triggers your network