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GithubSingTown基於OpenMV嘅AI智能相機系統,能夠實現實時火源識別同自動滅火控制。系統利用機器視覺同圖像識別算法,檢測火焰特徵,判斷火源位置同範圍,並驅動車輛或機械人自主接近火點進行滅火作業。廣泛應用於安防、實驗室同工業安全監控場景。

火災嘅危險同突然性令逃生變得極其困難,因此早期偵測同快速應對對於生命安全同滅火工作都至關重要。
To this end, SingTown Technology offers an AI smart camera solution based on OpenMV, designed to achieve efficient early fire detection and alarm functionality. This solution utilises computer vision and image recognition algorithms for real-time flame detection and localisation, empowering mobile fire suppression systems with embedded vision capabilities.
當系統嘅鏡頭捕捉到光譜特性同亮度變化時,邊緣人工智能會迅速識別火焰嘅顏色、閃爍頻率同形態特徵,從而區分真實火源同反射干擾。一旦系統確定存在火焰,就會自動計算火源座標並發出控制指令,令消防車或機械人能夠自主調整方向並加速駛向起火點。
到達指定位置後,系統可協調噴灑裝置或滅火模組實現自動滅火。透過攝像頭實時監測滅火效果,判斷火勢是否完全撲滅。AI模型亦可透過樣本學習適應不同類型嘅火焰(如酒精燈火焰、明火、電弧火等),提升識別嘅實用性同準確度。
This solution adopts an edge deployment architecture, featuring fast response, low power consumption, and easy scalability, making it particularly suitable for applications such as laboratory safety monitoring, warehouse fire prevention, and unmanned inspection vehicles. With the OpenMV smart camera as its core, SingTown deeply integrates edge AI and machine vision technologies, endowing devices with the autonomous capability to "see fire and extinguish fire," providing a flexible and efficient machine vision solution for fire prevention and rescue operations.

AI Sentinel Based on OpenMV: Automatic Alert for Unattended Key Locations
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Personnel crossing boundary triggers an alarm; OpenMV interprets the “sense of security boundary”
Detecting personnel or equipment crossing virtual perimeter lines.

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Automatically identifies illegal street vending activities to support daily urban governance.

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Automatically identifies non-compliant placement positions of gas cylinders to proactively detect potential gas safety hazards.

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Automatically identifies whether workers are wearing insulating gloves to assist in safe operations.

Utilising the OpenMV smart camera to identify surface defects on aluminium plates in real time
Online identification of defects on aluminium plate surfaces, such as scratches and dents, to support quality control.