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GithubThe presence of fire extinguishers is often only discovered to be problematic when they are actually needed—by which time it is already too late. Relying on manual inspections results in low frequency and frequent omissions, making it difficult to achieve continuous and effective monitoring. OpenMV transforms fire safety inspections into an “always-on” process through visual means.

In public and industrial locations—such as shopping malls, industrial parks, factory workshops, and office buildings—the proper placement of fire extinguishers in accordance with regulations, whether they have been moved without authorization, and whether they are obstructed by杂物, directly affects the efficiency of emergency response during unexpected fire incidents. Should a fire extinguisher be missing or unavailable for immediate use, the critical window for initial firefighting is often missed, resulting in greater safety losses.
Traditional fire inspection primarily relies on manual periodic checks, which not only limits inspection frequency but also heavily depends on inspectors’ sense of responsibility and experience, making it prone to omissions, misjudgments, or situations where items pass inspection but are subsequently removed—thus hindering continuous and effective supervision.
Introducing SingTown’s OpenMV smart camera, which upgrades fire extinguisher inspections from manual patrols to round-the-clock, automated visual inspections.
The camera is permanently installed at the designated location corresponding to the fire-fighting equipment, operating stably over the long term to continuously capture on-site images of the fire extinguisher area without human intervention. OpenMV runs object recognition algorithms on the camera side to accurately identify the fire extinguisher itself and, in conjunction with pre-defined installation area rules, determines whether it is positioned as required. Additionally, through shape integrity and occlusion detection, the system can also identify whether the fire extinguisher is obstructed, toppled, or exhibits abnormal appearance, thereby assessing its operational readiness from multiple dimensions.
Once OpenMV detects anomalies such as missing fire extinguishers, positional displacement, or obstruction, it can immediately generate an alert signal at the edge side, trigger on-site audible and visual alarm devices, or upload the event information to the management platform—achieving true “immediate anomaly detection and instant issue notification.”
Leveraging an edge deployment architecture and on-device AI capabilities, OpenMV can perform recognition and decision-making without continuously uploading video streams—reducing network and storage costs while significantly enhancing system stability and response speed.
Fire inspection has thus been upgraded from “periodic manual inspection” to “7×24-hour online monitoring,” effectively reducing fire safety risks and enhancing overall emergency response capabilities.

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