How Little Angel by PAN Runs AI Fire Detection Across 250 CCTV Cameras
Two on-site AI Bot Eye devices provide the local processing capacity for this large manufacturing deployment while alerts remain coordinated through one site-level workflow – including WhatsApp.
Customer deployment
Little Angel by PAN
Large manufacturing facility | 250 CCTV cameras | 2 on-site AI devices
- On-premise processing in the data-centre room
- Coordinated notification workflow, including WhatsApp
- Monthly controlled fire-detection tests
Verified deployment at a glance
250
CCTV cameras covered
2
AI Bot Eye devices installed
On-site
Local AI processing
Monthly
Controlled validation tests
| Deployment detail | Verified context |
|---|---|
| Customer | Little Angel by PAN |
| Facility | Large manufacturing facility |
| Primary application | AI fire detection |
| Camera coverage | 250 CCTV cameras |
| Edge infrastructure | 2 on-site AI Bot Eye devices |
| Processing location | On-site data-centre room |
| Alerting | Coordinated notification workflow, including WhatsApp |
| Operational assurance | Camera Health active |
| Validation | Monthly controlled fire tests at selected locations |
250 cameras required more local AI capacity than one device
Covering 250 CCTV cameras for AI fire detection requires more local processing capacity than a single edge device should handle.
At Little Angel by PAN, AI Bot Eye uses two on-site devices within the same on-premise deployment. Camera processing is distributed across the two devices, while alerting remains coordinated for the site team through one notification workflow.
The result is a system that can expand locally without turning each device into a separate operational silo.
250 cameras. Two edge devices. One coordinated deployment.
The Little Angel by PAN deployment covers 250 CCTV cameras through two AI Bot Eye devices installed on-site. Camera processing is distributed across the two devices, providing the local AI capacity required for the facility while keeping alerting coordinated for the site team.
This allows the deployment to scale its processing capacity without turning each device into a separate operational system.
250 camera feeds enter the AI layer
Feeds from the facility’s existing CCTV or NVR infrastructure are used for AI fire detection across the 250-camera deployment.
Processing is distributed across two local devices
The camera feeds are assigned across two AI Bot Eye edge devices installed in the on-site data-centre room.
Detection runs on the facility
Video is analysed locally, keeping AI processing close to the customer’s infrastructure and operations.
Alerts follow one coordinated notification workflow
When the system identifies a possible fire event, configured notifications – including WhatsApp alerts – reach the relevant site team through a coordinated notification workflow.
Scale the AI capacity – not the operational complexity
Add processing capacity for 250 cameras
Two on-site AI Bot Eye devices provide the local edge capacity required to support AI fire detection across the facility’s 250 CCTV cameras.
Keep processing on-site
AI analysis runs on infrastructure located at the facility, supporting customers that prefer local video processing and control.
Keep alerting coordinated
Two processing devices do not require the site team to manage separate alert experiences. Notifications continue through one coordinated notification workflow.
Tested regularly in the actual facility environment
Installation is only the beginning. Controlled fire-detection tests are conducted every month across selected locations at the facility. These tests allow the team to observe AI detection under the actual camera views, distances and environmental conditions present at the site.
- Monthly controlled fire tests
- Multiple facility locations
- Actual installed camera views
- Real site conditions
Monthly controlled testing
Fire detection depends on available camera feeds
AI fire detection cannot monitor a view when its camera feed is unavailable. Camera Health helps identify feed interruptions so the responsible team can investigate cameras that may no longer be available for AI analysis.
At Little Angel by PAN, Camera Health is active as part of the deployment’s operational assurance – not presented as a separate fire-detection method.
What the Little Angel by PAN deployment demonstrates
This deployment shows how AI Bot Eye can support AI fire detection across a large existing CCTV installation without forcing the customer to manage each edge device as a separate system.
- 250 existing CCTV cameras supported across one facility
- AI processing distributed across two on-site devices
- Video analysis kept within the customer’s facility
- Notifications coordinated through one site-level workflow
- Camera-feed availability monitored through Camera Health
- Controlled fire tests conducted monthly under real site conditions
Frequently asked questions
Why would one facility use multiple AI Bot Eye devices?
A deployment covering 250 CCTV cameras may require more local processing capacity than a single edge device should handle. At Little Angel by PAN, two on-site devices distribute the processing load while remaining part of one site-level solution.
Do multiple devices create separate alerts?
They do not have to. In this deployment, the two devices participate in a coordinated notification workflow, including WhatsApp alerts for configured recipients.
Does the video need to be processed in the cloud?
No. In this deployment, the two AI Bot Eye devices run on-site in the facility’s data-centre room.
Is every CCTV camera automatically suitable for fire detection?
No. Camera views should be assessed for factors such as location, visibility, distance, obstruction and scene conditions. This deployment covers 250 CCTV cameras selected for the facility’s fire-detection plan.
What does Camera Health do?
Camera Health identifies feed-availability issues so the team can investigate cameras that may no longer be available for AI analysis.
Does AI Bot Eye replace the facility’s fire-alarm system?
No. AI Bot Eye is an additional visual early-warning layer. It complements certified fire-safety systems and the facility’s response procedures.
Planning AI fire detection across a large CCTV facility?
AI Bot Eye can help assess camera suitability, local processing requirements and the alert workflow required for your facility.
Share your approximate camera count and facility type to begin the assessment.
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