When a Fire Can Cost $80M, Every Second Matters.
We built a custom AI fire detection system that helps an industrial manufacturer spot danger earlier, respond faster, and protect valuable products.
A small fire can become a massive loss.
In a tissue factory, fire can spread quickly. It can destroy finished products, damage machinery, and stop production.
A major fire at a tissue factory in Bangladesh in November 2024 showed just how costly an industrial fire can be. Media reports cited potential losses of up to $82 million.
That figure reflects reported losses associated with the historical fire. It is not money saved by our system.
After the factory was rebuilt, the need for better fire monitoring remained.
Traditional CCTV cameras let people see what is happening. But someone still has to notice the danger.
And when nobody spots a fire in time, the damage can grow before anyone reacts.
Relying purely on human operators watching live screens meant early smoke or small flames could easily go unnoticed until damage escalated.
We made the cameras smarter.
We developed a custom AI model that looks for signs of fire and smoke in live camera footage, then connected it to a monitoring system that helps people act on what the AI detects. When the system identifies a potential fire, it sends an alert so the team can open the relevant camera feed, see where the incident is happening, and assess the situation. We designed the entire experience around one goal: help people move from a warning to informed action, with less guesswork.
"The solution works with existing and new cameras, bringing AI detection and everyday monitoring into one connected system"
Everything the team needs to see, understand, and respond.
Custom AI detection
We built a custom AI model to identify visual signs of fire and smoke in live camera feeds.
A web monitoring dashboard
The team can monitor cameras, review alerts, and see incidents from one central place.
Live camera feeds
When an alert appears, the team can open the relevant footage to understand what is happening.
Instant notifications
The system alerts the team when it detects a potential fire or smoke incident.
Incident tracking
Each detected event can be reviewed with details such as its location, time, and status.
Visual location mapping
The team can see which camera detected the event and where that camera is located in the facility.
A mobile monitoring app
Authorized users can access monitoring information and alerts beyond the control room.
Camera and system integration
We connected the AI solution to existing and new cameras to fit the factory's needs.
Together, these features connect detection, alerts, live footage, and incident review in one workflow.
Four problems, four fixes.
Operators could not watch every camera feed simultaneously for early signs of smoke.
Trained a custom AI model to continuously inspect live camera feeds for fire and smoke signatures.
Detection delays left teams reacting after damage had already spread.
Integrated instant automated notifications alerting personnel the moment potential hazards appear.
Finding the exact physical location of a hazard during panic caused response delays.
Added visual location mapping matching camera triggers directly to facility blueprints.
Control room staff lacked remote visibility when away from physical monitors.
Developed a companion mobile monitoring app to deliver alerts and camera feeds on the go.
An alert is only useful when people know what to do next.
We designed the monitoring experience to make critical information easy to find.
The dashboard brings together camera activity, incident alerts, live footage, and facility locations.
When a potential fire is detected, the team can find the affected camera, check the footage, and assess the situation without searching through multiple screens.
The mobile app extends that access to authorized users outside the control room.
The goal was not to add more information to the screen. It was to make the right information easier to find when it matters most.
See camera activity and potential incidents in one place.
Inspect the camera feed associated with a potential fire or smoke event.
Access monitoring and alerts beyond the control room.
Multiple incidents. Less damage. A safer way to monitor.
Since implementation, the client has reported several occasions when the system helped prevent fire incidents from causing major product damage.
The system continues to support the factory's monitoring operations, with ongoing support from our team.
What the project has achieved:
- Multiple incidents addressed: The system has helped prevent major product damage on several occasions.
- Continuous AI monitoring: Live camera feeds are analyzed for potential signs of fire and smoke.
- Earlier warnings: Automated alerts help the team identify potential hazards without relying entirely on someone watching a screen.
- Clearer incident visibility: Camera locations and live footage help the team assess where an incident is happening.
- One connected experience: Web and mobile applications bring monitoring, alerts, and incident information together.
Why this matters to the business
A serious industrial fire can put millions of dollars in products, machinery, and operations at risk. The reported $82 million figure from the historical fire shows the scale of that risk. It does not represent savings generated by our solution. Our system is designed to help reduce that risk through earlier detection and better incident visibility. The client has reported real instances of prevented product damage. We have not assigned a dollar value to those outcomes because the financial savings have not been independently measured.
What changed
for MGI, Bangladesh.
Potential fire incidents addressed before major damage occurred
Continuous automated surveillance for smoke and fire signatures
Mobile and web alerts sent directly to responsible teams
Integrated web and mobile monitoring architecture
“They have described the product as fantastic and life-saving because it has helped prevent major damage to products.”
Technology that makesa real difference.
We worked directly with the client's internal IT team throughout the project.
Their feedback has been consistently positive. They have described the product as fantastic and life-saving because it has helped prevent major damage to products.
We cannot publish their exact statements or identify individual team members under our confidentiality agreement.
For us, the most meaningful outcome is simple: the system is being used to address a real business risk, and the client continues to receive support from our team.
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