From Manual Inspection to AI Detection – SingTown Technology Enables Instruments to "Read Their Own Dials

During the operation of industrial equipment, mechanical dials such as air pressure gauges and water pressure gauges are widely used to monitor the system's pressure status.

然而，人手檢查不僅耗時且容易出錯，更難以實現持續監測。

To enhance equipment safety and management efficiency, instrument manufacturing enterprises have introduced SingTown's OpenMV intelligent camera recognition technology, which utilises AI machine vision and image recognition algorithms for automatic identification and analysis of dial pointers.

The system can determine in real-time whether the pressure gauge pointer is within the safe (green) zone, enabling automatic detection, anomaly alerts, and remote monitoring. It is widely applied in scenarios such as industrial pressure vessels, air compressors, and water treatment systems.

儀器儀表製造企業已建立一套基於SingTown Technology OpenMV智能相機識別技術的錶盤狀態識別系統，實現對壓力錶指針狀態的自動檢測與警報反饋。

The camera is fixed directly in front of the instrument, capturing real-time images of the pressure gauge. By utilising computer vision and image recognition technology, it automatically detects the pointer angle and the distribution of the dial area.

The system employs colour segmentation, edge detection, and the Hough circle detection algorithm to extract the centre of the dial, the position of the scale ring, and the pointer. It then utilises an angle calculation module to determine whether the pointer is pointing to the green safety zone.

當偵測到指針落入紅色或黃色區域時，OpenMV模組會立即輸出高電平信號或透過串列埠發送異常標誌，從而實現自動警報或連鎖停機。

AI algorithms can perform targeted automated learning based on actual conditions to adapt to the colour schemes and pointer shapes of different instrument models, as well as complex environments such as varying lighting, angles, and reflections.

所有識別與判斷均在攝影機端本地完成，無需外部電腦。邊緣人工智能實現實時狀態識別與控制反饋。

透過此解決方案，企業已由人手檢查轉為AI視覺自動化監控，顯著提升設備安全及監管效率。