See, Hear, and Respond to Threats in Real-Time
Multi-modal AI that fuses audio, video, and sensor data to detect emergencies before they escalate.
Protecting Communities Through Intelligent Monitoring
Urban safety and disaster prevention require comprehensive, real-time monitoring that goes beyond traditional visual surveillance. SteadyBeat’s multi-modal AI solution fuses acoustic, visual, and environmental sensing to detect earthquakes, gas leaks, explosions, and other threats with unprecedented speed and accuracy. By processing data at the edge, the system remains operational even when network infrastructure fails—precisely when it’s needed most.
Challenges in Urban Safety Monitoring
Understanding the limitations of traditional monitoring approaches
Delayed Incident Detection
Traditional monitoring systems rely primarily on visual surveillance, missing critical acoustic and environmental indicators that could provide earlier warning of emergencies.
Impact
- Slower emergency response times
- Increased casualties and property damage
- Limited situational awareness
Network Dependency Risks
Cloud-based monitoring systems become unreliable during disasters when network infrastructure is compromised, precisely when they’re needed most.
Impact
- System failures during critical events
- Data transmission delays
- Dependency on external infrastructure
Urban Complexity
Dense urban environments generate constant background noise and activity, making it challenging to distinguish normal patterns from genuine threats or emergencies.
Impact
- High false alarm rates
- Alert fatigue for operators
- Missed genuine threats
Multi-Modal AI Fusion for Comprehensive Threat Detection
SteadyBeat’s public safety solution combines acoustic, visual, and environmental sensors with edge AI processing to create a comprehensive, network-independent monitoring system for urban environments.
Advanced ANC
Real-time analysis and adaptive noise cancellation algorithms
Multi-Modal Fusion
Acoustic, visual, physiological, and environmental sensors
Edge AI Processing
On-chip inference with <10ms latency, privacy-preserving
How It Works
Key Benefits
Real-Time Multi-Modal Detection
Fusion of acoustic, visual, and environmental sensors enables comprehensive threat detection—earthquakes, gas leaks, explosions, gunshots, abnormal crowd movements—with higher accuracy than single-modal systems.
Technical Achievement
Edge AI sensor fusion with sub-second detection latency
Network-Independent Operation
Edge AI processing ensures the system continues functioning during network outages or disasters, with local alerting and decision-making capabilities that don’t rely on cloud connectivity.
Technical Achievement
Autonomous edge processing with optional cloud synchronization
Intelligent Alert Prioritization
AI algorithms analyze context and patterns to reduce false alarms, prioritizing genuine threats and providing operators with actionable intelligence rather than raw sensor data.
Technical Achievement
Machine learning-based anomaly detection with confidence scoring
Enhanced Urban Safety
Comprehensive monitoring of public spaces, transportation hubs, and critical infrastructure creates safer urban environments with faster emergency response and better resource allocation.
Technical Achievement
Scalable deployment across distributed sensor networks
Real-World Applications
See how our technology enhances safety in different urban scenarios
Earthquake Early Warning
Situation
Seismic activity generates acoustic and vibration signatures seconds before destructive waves arrive, but traditional systems may not provide sufficient warning time.
Solution
- Multi-modal sensors detect P-waves and acoustic precursors in real-time
- Immediate local alerts trigger automated safety responses (elevator stops, gas shutoffs)
- Network-independent operation ensures reliability during infrastructure disruption
Outcome
Critical seconds of warning time enable automated safety measures and give people time to take protective action, potentially saving lives.
Gas Leak Detection
Situation
Gas leaks in urban areas pose explosion and health risks, but may go undetected until dangerous concentrations accumulate.
Solution
- Distributed acoustic sensors detect characteristic hissing sounds of gas leaks
- Environmental sensors confirm gas presence for multi-modal validation
- Rapid response alerts enable intervention before dangerous concentrations accumulate
Outcome
Early detection prevents explosions and evacuations, protecting public safety and critical infrastructure.
Crowd Monitoring & Incident Detection
Situation
Large public gatherings, transportation hubs, and entertainment venues require monitoring for safety threats, crowd crushes, and emergency situations.
Solution
- Multi-modal AI analyzes acoustic patterns (screams, gunshots, crowd panic)
- Visual data processing monitors crowd density and movement patterns
- Environmental factor analysis provides comprehensive real-time situational awareness
Outcome
Faster emergency response, prevention of crowd crushes, and enhanced security through comprehensive situational awareness.
Ready to Enhance Urban Safety?
Discover how SteadyBeat’s multi-modal AI can protect your community with faster, more accurate threat detection.