SEE THE RISK
BEFORE THE
INCIDENT.
HyperQ AI Safety converts existing camera infrastructure into a real-time monitoring layer for PPE compliance, zone violations, falls, fire events, and abnormal worker behavior.
Active Awareness.
Not Passive Record.
HyperQ AI Safety is a vision-based monitoring system for industrial environments where human attention alone cannot cover every zone, every shift, and every risk condition. It detects critical safety events as they form and routes alerts before delay becomes injury.
PPE Compliance Monitoring
Detects missing helmets, vests, harnesses, and gloves. Coverage per zone, per shift, continuously.
Restricted Zone Detection
Flags unauthorized personnel in exclusion zones, around machinery, or in high-risk maintenance areas.
Fire, Fall & Behavior Detection
Context-aware detection of fire and smoke events, falls, worker collapse, and abnormal activity patterns.
Real-Time Alert Delivery
Instant notifications to mobile and web dashboard. Routed by zone, shift, and severity level.
From Camera Feed
to Actionable Alert.
This is not passive recording. It is active facility awareness.
Observe
Existing CCTV feeds stream live to the edge device. No new cameras required in most setups.
Interpret
Context-aware AI understands what is happening — not just what is visible. Welding is not fire.
Prioritize
Events ranked by risk level. Low-confidence events filtered before alert dispatch.
Respond
Alerts routed instantly to mobile, dashboard, or PLC integration. This is not passive recording.
Where Safety Blind Spots
Become Expensive.
Manufacturing Floors
PPE compliance, collision risk between forklifts and pedestrians, fire detection in high-heat zones.
Warehouses & Logistics
Zone management, high-traffic pedestrian monitoring, equipment proximity, and behavioral alerts.
Construction Sites
Fall detection, harness verification at heights, restricted zone enforcement, PPE audit per area.
Restricted Maintenance Areas
Monitor access to confined spaces, high-voltage zones, and authorized maintenance work areas.
What Improves Before
and After Deployment.
Faster Response to Risk Events
Incidents detected in real time, not discovered on footage review. Alert reaches the right person before delay becomes injury.
Broader Visual Coverage
AI covers every camera, every zone, every shift simultaneously. No human monitor can match that span without fatigue.
Lower Monitoring Fatigue
Context-aware AI reduces false positives. Teams see credible alerts — not noise — which means they act on them.
Stronger Safety Discipline
Continuous, visible monitoring changes behavior. PPE compliance improves when workers know the system is always watching.
Beyond Passive CCTV
and Rule-Only Systems.
| Feature | HyperQ AI Safety | Passive CCTV | Manual Supervision |
|---|---|---|---|
| Deployment Speed | ~1 hour in suitable environments | Days to install and calibrate | Immediate, but coverage is limited |
| Context Awareness | Situation-aware — welding ≠ fire | No AI interpretation | Human judgment, shift-variable |
| False Positive Load | Reduced by context-aware filtering | None (no alerts generated) | Alert fatigue common |
| Existing Camera Use | Integrates with existing CCTV | Recording only, no analysis | No integration needed |
| Alerting Speed | Real-time to mobile and dashboard | No alerts — review only | Delayed by human response time |
| Zone Scalability | Scales across all camera feeds | Coverage limited by cameras | Constrained by headcount |
Fast to Start.
Practical to Scale.
HyperQ AI Safety is designed to start with what you already have. Where existing cameras meet the required quality and angle, deployment is a configuration exercise — not an infrastructure project.
Uses Existing CCTV Infrastructure
Connects to any camera where angle and image quality support detection. No replacement required in most deployments.
RTSP / ONVIF / Proprietary Protocol Support
Connects to cameras via standard protocols. Proprietary camera formats supported where protocol documentation is available.
On-Premise Edge Deployment
Runs on NVIDIA Jetson or industrial PC. Sub-10ms inference on-device. Air-gapped environments fully supported.
MQTT, Modbus, and PLC Integration
Alerts and event data push directly to MES, safety dashboards, or existing control systems via OT-native protocols.
Staged Rollout by Zone
Start with highest-risk zones. Validate detection confidence and alert routing before expanding facility-wide.
Common Questions.
Can HyperQ AI Safety use our existing cameras?
In most cases, yes. The system integrates with existing CCTV where the camera angle, resolution, and image quality are sufficient for the detection task. Hypernology will evaluate your current camera setup during scoping and identify where replacements or additions are necessary.
What events can it detect?
HyperQ AI Safety detects PPE violations (missing helmet, vest, harness, gloves), restricted zone intrusions, falls and worker collapse, fire and smoke events, abnormal worker behavior, and forklift/pedestrian proximity violations. Detection categories are configured per deployment.
How are alerts delivered?
Alerts are delivered in real time to a mobile app, web dashboard, and optionally integrated with existing control systems via MQTT, Modbus, or PLC protocols. Alert routing is configurable by zone, event type, and severity level.
Can it work without cloud connectivity?
Yes. HyperQ AI Safety runs fully on-premise on edge devices. No internet connection required. All AI inference happens on-device. Data stays within the facility unless explicitly configured otherwise.
How long does deployment take?
In suitable environments — with existing cameras that meet the required angle and image quality — HyperQ AI Safety can be operational in approximately 1 hour. Environments requiring camera upgrades or significant infrastructure work will take longer, and we scope this clearly before starting.
How do you control false alarms?
The system uses context-aware AI to interpret what is actually happening in the scene, not just pattern-match pixels. A welding arc is not classified as fire. A worker kneeling is not flagged as a fall. Confidence thresholds are tunable per zone and event type to match your operational environment.
If the Risk Is Visible, It Should Be Actionable.
Tell us where safety incidents have occurred or where blind spots exist in your facility. We will scope a deployment that covers those zones first.